1
|
Hembert P, Ghnatios C, Cotton J, Chinesta F. Assessing Sensor Integrity for Nuclear Waste Monitoring Using Graph Neural Networks. Sensors (Basel) 2024; 24:1580. [PMID: 38475116 DOI: 10.3390/s24051580] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/19/2023] [Revised: 02/23/2024] [Accepted: 02/25/2024] [Indexed: 03/14/2024]
Abstract
A deep geological repository for radioactive waste, such as Andra's Cigéo project, requires long-term (persistent) monitoring. To achieve this goal, data from a network of sensors are acquired. This network is subject to deterioration over time due to environmental effects (radioactivity, mechanical deterioration of the cell, etc.), and it is paramount to assess each sensor's integrity and ensure data consistency to enable the precise monitoring of the facilities. Graph neural networks (GNNs) are suitable for detecting faulty sensors in complex networks because they accurately depict physical phenomena that occur in a system and take the sensor network's local structure into consideration in the predictions. In this work, we leveraged the availability of the experimental data acquired in Andra's Underground Research Laboratory (URL) to train a graph neural network for the assessment of data integrity. The experiment considered in this work emulated the thermal loading of a high-level waste (HLW) demonstrator cell (i.e., the heating of the containment cell by nuclear waste). Using real experiment data acquired in Andra's URL in a deep geological layer was one of the novelties of this work. The used model was a GNN that inputted the temperature field from the sensors (at the current and past steps) and returned the state of each individual sensor, i.e., faulty or not. The other novelty of this work lay in the application of the GraphSAGE model which was modified with elements of the Graph Net framework to detect faulty sensors, with up to half of the sensors in the network being faulty at once. This proportion of faulty sensors was explained by the use of distributed sensors (optic fiber) and the environmental effects on the cell. The GNNs trained on the experimental data were ultimately compared against other standard classification methods (thresholding, artificial neural networks, etc.), which demonstrated their effectiveness in the assessment of data integrity.
Collapse
Affiliation(s)
- Pierre Hembert
- PIMM Laboratory, Arts et Métiers Institute of Technology, Centre National de la Recherche Scientifique (CNRS), 151 Boulevard de l'Hôpital, 75013 Paris, France
- Andra, French National Radioactive Waste Management Agency, 92298 Châtenay-Malabry, France
| | - Chady Ghnatios
- PIMM Laboratory, Arts et Métiers Institute of Technology, Centre National de la Recherche Scientifique (CNRS), 151 Boulevard de l'Hôpital, 75013 Paris, France
| | - Julien Cotton
- Andra, French National Radioactive Waste Management Agency, 92298 Châtenay-Malabry, France
| | - Francisco Chinesta
- PIMM Laboratory, Arts et Métiers Institute of Technology, Centre National de la Recherche Scientifique (CNRS), 151 Boulevard de l'Hôpital, 75013 Paris, France
| |
Collapse
|
2
|
Sirimorok N, Paweroi RM, Arsyad AA, Köppen M. Smart Farm Security by Combining IoT Sensor Network and Virtualized Mycelium Network. Sensors (Basel) 2023; 23:8689. [PMID: 37960389 PMCID: PMC10648404 DOI: 10.3390/s23218689] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/14/2023] [Revised: 10/17/2023] [Accepted: 10/23/2023] [Indexed: 11/15/2023]
Abstract
In today's world, merging sensor-based security systems with contemporary principles has become crucial. As we witness the ever-growing number of interconnected devices in the Internet of Things (IoT), it is imperative to have robust and trustworthy security measures in place. In this paper, we examine the idea of virtualizing the communication infrastructure for smart farming in the context of IoT. Our approach utilizes a metaverse-based framework that mimics natural processes such as mycelium network growth communication with a security-concept-based srtificial immune system (AIS) and transaction models of a multi-agent system (MAS). The mycelium, a bridge that transfers nutrients from one plant to another, is an underground network (IoT below ground) that can interconnect multiple plants. Our objective is to study and simulate the mycelium's behavior, which serves as an underground IoT, and we anticipate that the simulation results, supported by diverse aspects, can be a reference for future IoT network development. A proof of concept is presented, demonstrating the capabilities of such a virtualized network for dedicated sensor communication and easy reconfiguration for various needs.
Collapse
Affiliation(s)
- Nurdiansyah Sirimorok
- Department of Computer Science and Systems Engineering (CSSE), Graduate School of Computer Science and Systems Engineering, Kyushu Institute of Technology, 680-4 Kawazu, Fukuoka 820-8502, Japan; (R.M.P.); (A.A.A.); (M.K.)
| | | | | | | |
Collapse
|
3
|
Płaczek B. A Multi-Agent Prediction Method for Data Sampling and Transmission Reduction in Internet of Things Sensor Networks. Sensors (Basel) 2023; 23:8478. [PMID: 37896571 PMCID: PMC10611001 DOI: 10.3390/s23208478] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/12/2023] [Revised: 10/11/2023] [Accepted: 10/13/2023] [Indexed: 10/29/2023]
Abstract
Sensor networks can provide valuable real-time data for various IoT applications. However, the amount of sensed and transmitted data should be kept at a low level due to the limitations imposed by network bandwidth, data storage, processing capabilities, and finite energy resources. In this paper, a new method is introduced that uses the predicted intervals of possible sensor readings to efficiently suppress unnecessary transmissions and decrease the amount of data samples collected by a sensor node. In the proposed method, the intervals of possible sensor readings are determined with a multi-agent system, where each agent independently explores a historical dataset and evaluates the similarity between past and current sensor readings to make predictions. Based on the predicted intervals, it is determined whether the real sensed data can be useful for a given IoT application and when the next data sample should be transmitted. The prediction algorithm is executed by the IoT gateway or in the cloud. The presented method is applicable to IoT sensor networks that utilize low-end devices with limited processing power, memory, and energy resources. During the experiments, the advantages of the introduced method were demonstrated by considering the criteria of prediction interval width, coverage probability, and transmission reduction. The experimental results confirm that the introduced method improves the accuracy of prediction intervals and achieves a higher rate of transmission reduction compared with state-of-the-art prediction methods.
Collapse
Affiliation(s)
- Bartłomiej Płaczek
- Institute of Computer Science, University of Silesia, Będzińska 39, 41-200 Sosnowiec, Poland
| |
Collapse
|
4
|
Larocca G, Contrafatto D, Cannata A, Giudice G. Multiparametric Monitoring System of Mt. Melbourne Volcano (Victoria Land, Antarctica). Sensors (Basel) 2023; 23:7594. [PMID: 37688049 PMCID: PMC10490633 DOI: 10.3390/s23177594] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/11/2023] [Revised: 08/28/2023] [Accepted: 08/30/2023] [Indexed: 09/10/2023]
Abstract
Volcano monitoring is the key approach in mitigating the risks associated with volcanic phenomena. Although Antarctic volcanoes are characterized by remoteness, the 2010 Eyjafjallajökull eruption and the 2022 Hunga eruption have reminded us that even the farthest and/or least-known volcanoes can pose significant hazards to large and distant communities. Hence, it is important to also develop monitoring systems in the Antarctic volcanoes, which involves installing and maintaining multiparametric instrument networks. These tasks are particularly challenging in polar regions as the instruments have to face the most extreme climate on the Earth, characterized by very low temperatures and strong winds. In this work, we describe the multiparametric monitoring system recently deployed on the Melbourne volcano (Victoria Land, Antarctica), consisting of seismic, geochemical and thermal sensors together with powering, transmission and acquisition systems. Particular strategies have been applied to make the monitoring stations efficient despite the extreme weather conditions. Fumarolic ice caves, located on the summit area of the Melbourne volcano, were chosen as installation sites as they are protected places where no storm can damage the instruments and temperatures are close to 0 °C all year round. In addition, the choice of instruments and their operating mode has also been driven by the necessity to reduce energy consumption. Indeed, one of the most complicated tasks in Antarctica is powering a remote instrument year-round. The technological solutions found to implement the monitoring system of the Melbourne volcano and described in this work can help create volcano monitoring infrastructures in other polar environments.
Collapse
Affiliation(s)
- Graziano Larocca
- Istituto Nazionale di Geofisica e Vulcanologia, Osservatorio Etneo, Piazza Roma 2, 95123 Catania, Italy; (G.L.); (D.C.); (A.C.)
| | - Danilo Contrafatto
- Istituto Nazionale di Geofisica e Vulcanologia, Osservatorio Etneo, Piazza Roma 2, 95123 Catania, Italy; (G.L.); (D.C.); (A.C.)
| | - Andrea Cannata
- Istituto Nazionale di Geofisica e Vulcanologia, Osservatorio Etneo, Piazza Roma 2, 95123 Catania, Italy; (G.L.); (D.C.); (A.C.)
- Dipartimento di Scienze Biologiche, Geologiche e Ambientali-Sezione di Scienze della Terra, Università degli Studi di Catania, Corso Italia 57, 95129 Catania, Italy
| | - Gaetano Giudice
- Istituto Nazionale di Geofisica e Vulcanologia, Osservatorio Etneo, Piazza Roma 2, 95123 Catania, Italy; (G.L.); (D.C.); (A.C.)
| |
Collapse
|
5
|
Chen Q, Shi W, Sui D, Leng S. Distributed Consensus Algorithms in Sensor Networks with Higher-Order Topology. Entropy (Basel) 2023; 25:1200. [PMID: 37628230 PMCID: PMC10453068 DOI: 10.3390/e25081200] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Revised: 08/02/2023] [Accepted: 08/08/2023] [Indexed: 08/27/2023]
Abstract
Information aggregation in distributed sensor networks has received significant attention from researchers in various disciplines. Distributed consensus algorithms are broadly developed to accelerate the convergence to consensus under different communication and/or energy limitations. Non-Bayesian social learning strategies are representative algorithms for distributed agents to learn progressively an underlying state of nature by information communications and evolutions. This work designs a new non-Bayesian social learning strategy named the hypergraph social learning by introducing the higher-order topology as the underlying communication network structure, with its convergence as well as the convergence rate theoretically analyzed. Extensive numerical examples are provided to demonstrate the effectiveness of the framework and reveal its superior performance when applying to sensor networks in tasks such as cooperative positioning. The designed framework can assist sensor network designers to develop more efficient communication topology, which can better resist environmental obstructions, and also has theoretical and applied values in broad areas such as distributed parameter estimation, dispersed information aggregation and social networks.
Collapse
Affiliation(s)
- Qianyi Chen
- School of Information Science and Technology, Fudan University, Shanghai 200433, China
| | - Wenyuan Shi
- School of Mathematical Sciences, Fudan University, Shanghai 200433, China
| | - Dongyan Sui
- Institute of AI and Robotics, Academy for Engineering and Technology, Fudan University, Shanghai 200433, China;
| | - Siyang Leng
- Institute of AI and Robotics, Academy for Engineering and Technology, Fudan University, Shanghai 200433, China;
- Research Institute of Intelligent Complex Systems, Fudan University, Shanghai 200433, China
| |
Collapse
|
6
|
Raheja G, Nimo J, Appoh EKE, Essien B, Sunu M, Nyante J, Amegah M, Quansah R, Arku RE, Penn SL, Giordano MR, Zheng Z, Jack D, Chillrud S, Amegah K, Subramanian R, Pinder R, Appah-Sampong E, Tetteh EN, Borketey MA, Hughes AF, Westervelt DM. Low-Cost Sensor Performance Intercomparison, Correction Factor Development, and 2+ Years of Ambient PM 2.5 Monitoring in Accra, Ghana. Environ Sci Technol 2023; 57:10708-10720. [PMID: 37437161 PMCID: PMC10373484 DOI: 10.1021/acs.est.2c09264] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/07/2022] [Revised: 06/01/2023] [Accepted: 06/02/2023] [Indexed: 07/14/2023]
Abstract
Particulate matter air pollution is a leading cause of global mortality, particularly in Asia and Africa. Addressing the high and wide-ranging air pollution levels requires ambient monitoring, but many low- and middle-income countries (LMICs) remain scarcely monitored. To address these data gaps, recent studies have utilized low-cost sensors. These sensors have varied performance, and little literature exists about sensor intercomparison in Africa. By colocating 2 QuantAQ Modulair-PM, 2 PurpleAir PA-II SD, and 16 Clarity Node-S Generation II monitors with a reference-grade Teledyne monitor in Accra, Ghana, we present the first intercomparisons of different brands of low-cost sensors in Africa, demonstrating that each type of low-cost sensor PM2.5 is strongly correlated with reference PM2.5, but biased high for ambient mixture of sources found in Accra. When compared to a reference monitor, the QuantAQ Modulair-PM has the lowest mean absolute error at 3.04 μg/m3, followed by PurpleAir PA-II (4.54 μg/m3) and Clarity Node-S (13.68 μg/m3). We also compare the usage of 4 statistical or machine learning models (Multiple Linear Regression, Random Forest, Gaussian Mixture Regression, and XGBoost) to correct low-cost sensors data, and find that XGBoost performs the best in testing (R2: 0.97, 0.94, 0.96; mean absolute error: 0.56, 0.80, and 0.68 μg/m3 for PurpleAir PA-II, Clarity Node-S, and Modulair-PM, respectively), but tree-based models do not perform well when correcting data outside the range of the colocation training. Therefore, we used Gaussian Mixture Regression to correct data from the network of 17 Clarity Node-S monitors deployed around Accra, Ghana, from 2018 to 2021. We find that the network daily average PM2.5 concentration in Accra is 23.4 μg/m3, which is 1.6 times the World Health Organization Daily PM2.5 guideline of 15 μg/m3. While this level is lower than those seen in some larger African cities (such as Kinshasa, Democratic Republic of the Congo), mitigation strategies should be developed soon to prevent further impairment to air quality as Accra, and Ghana as a whole, rapidly grow.
Collapse
Affiliation(s)
- Garima Raheja
- Department
of Earth and Environmental Sciences, Columbia
University, New York, New York 10027, United States
- Lamont-Doherty
Earth Observatory of Columbia University, Palisades, New York 10964, United States
| | - James Nimo
- Department
of Physics, University of Ghana, Legon, Ghana, Ghana
- African
Institute of Mathematical Sciences, Kigali, Rwanda
| | | | | | - Maxwell Sunu
- Ghana
Environmental Protection Agency, Accra, Ghana
| | - John Nyante
- Ghana
Environmental Protection Agency, Accra, Ghana
| | | | | | - Raphael E. Arku
- Department
of Environmental Health Sciences, School of Public Health and Health
Sciences, University of Massachusetts, Amherst, Massachusetts 01003, United States
| | - Stefani L. Penn
- Industrial
Economics, Inc, Cambridge, Massachusetts 02140, United States
| | - Michael R. Giordano
- Univ
Paris Est Creteil, CNRS UMS 3563, Ecole Nationale des Ponts et Chaussés,
Université de Paris, OSU-EFLUVE—Observatoire Sciences
de L’Univers-Envelopes Fluides de La Ville à L’Exobiologie, F-94010 Créteil, France
| | - Zhonghua Zheng
- Department
of Earth and Environmental Sciences, The
University of Manchester, Manchester M13 9PL, U.K.
| | - Darby Jack
- Department of Environmental Health Sciences, Mailman
School of Public
Health, Columbia University, New York, New York 10032, United States
| | - Steven Chillrud
- Department of Environmental Health Sciences, Mailman
School of Public
Health, Columbia University, New York, New York 10032, United States
| | | | - R. Subramanian
- Univ
Paris Est Creteil, CNRS UMS 3563, Ecole Nationale des Ponts et Chaussés,
Université de Paris, OSU-EFLUVE—Observatoire Sciences
de L’Univers-Envelopes Fluides de La Ville à L’Exobiologie, F-94010 Créteil, France
- Kigali Collaborative
Research Centre, Kigali, Rwanda
| | - Robert Pinder
- Environmental Protection Agency, Raleigh, North Carolina 27709, United States
| | | | | | | | | | - Daniel M. Westervelt
- Lamont-Doherty
Earth Observatory of Columbia University, Palisades, New York 10964, United States
- NASA Goddard Institute for Space Science, New York, New York 10025, United States
| |
Collapse
|
7
|
Donati M, Olivelli M, Giovannini R, Fanucci L. ECG-Based Stress Detection and Productivity Factors Monitoring: The Real-Time Production Factory System. Sensors (Basel) 2023; 23:5502. [PMID: 37420669 DOI: 10.3390/s23125502] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Revised: 05/31/2023] [Accepted: 06/08/2023] [Indexed: 07/09/2023]
Abstract
Productivity and production quality have become primary goals for the success of companies in all industrial and manufacturing sectors. Performance in terms of productivity is influenced by several factors including machinery efficiency, work environment and safety conditions, production processes organization, and aspects related to workers' behavior (human factors). In particular, work-related stress is among the human factors that are most impactful and difficult to capture. Thus, optimizing productivity and quality in an effective way requires considering all these factors simultaneously. The proposed system aims to detect workers' stress and fatigue in real time using wearable sensors and machine learning techniques and also integrate all data regarding the monitoring of production processes and the work environment into a single platform. This allows comprehensive multidimensional data analysis and correlation research, enabling organizations to improve productivity through appropriate work environments and sustainable processes for workers. The on-field trial demonstrated the technical and operational feasibility of the system, its high degree of usability, and the ability to detect stress from ECG signals exploiting a 1D Convolutional Neural Network (accuracy 88.4%, F1-score 0.90).
Collapse
Affiliation(s)
- Massimiliano Donati
- Department of Information Engineering, University of Pisa, 56122 Pisa, Italy
| | - Martina Olivelli
- Department of Information Engineering, University of Pisa, 56122 Pisa, Italy
| | | | - Luca Fanucci
- Department of Information Engineering, University of Pisa, 56122 Pisa, Italy
| |
Collapse
|
8
|
Cheng X, Bao B, Cui W, Liu S, Zhong J, Cai L, Yang H. Classification and Analysis of Human Body Movement Characteristics Associated with Acrophobia Induced by Virtual Reality Scenes of Heights. Sensors (Basel) 2023; 23:5482. [PMID: 37420652 DOI: 10.3390/s23125482] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/18/2023] [Revised: 05/26/2023] [Accepted: 06/08/2023] [Indexed: 07/09/2023]
Abstract
Acrophobia (fear of heights), a prevalent psychological disorder, elicits profound fear and evokes a range of adverse physiological responses in individuals when exposed to heights, which will lead to a very dangerous state for people in actual heights. In this paper, we explore the behavioral influences in terms of movements in people confronted with virtual reality scenes of extreme heights and develop an acrophobia classification model based on human movement characteristics. To this end, we used wireless miniaturized inertial navigation sensors (WMINS) network to obtain the information of limb movements in the virtual environment. Based on these data, we constructed a series of data feature processing processes, proposed a system model for the classification of acrophobia and non-acrophobia based on human motion feature analysis, and realized the classification recognition of acrophobia and non-acrophobia through the designed integrated learning model. The final accuracy of acrophobia dichotomous classification based on limb motion information reached 94.64%, which has higher accuracy and efficiency compared with other existing research models. Overall, our study demonstrates a strong correlation between people's mental state during fear of heights and their limb movements at that time.
Collapse
Affiliation(s)
- Xiankai Cheng
- School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230026, China
- Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, China
| | - Benkun Bao
- School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230026, China
- Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, China
| | - Weidong Cui
- Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, China
| | - Shuai Liu
- School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230026, China
- Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, China
| | - Jun Zhong
- School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230026, China
- Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, China
| | - Liming Cai
- Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, China
| | - Hongbo Yang
- School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230026, China
- Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, China
| |
Collapse
|
9
|
Parri L, Tani M, Baldo D, Parrino S, Landi E, Mugnaini M, Fort A. A Distributed IoT Air Quality Measurement System for High-Risk Workplace Safety Enhancement. Sensors (Basel) 2023; 23:s23115060. [PMID: 37299787 DOI: 10.3390/s23115060] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Revised: 05/11/2023] [Accepted: 05/21/2023] [Indexed: 06/12/2023]
Abstract
The safety of an operator working in a hazardous environment is a recurring topic in the technical literature of recent years, especially for high-risk environments such as oil and gas plants, refineries, gas depots, or chemical industries. One of the highest risk factors is constituted by the presence of gaseous substances such as toxic compounds such as carbon monoxide and nitric oxides, particulate matter or indoors, in closed spaces, low oxygen concentration atmospheres, and high concentrations of CO2 that can represent a risk for human health. In this context, there exist many monitoring systems for lots of specific applications where gas detection is required. In this paper, the authors present a distributed sensing system based on commercial sensors aimed at monitoring the presence of toxic compounds generated by a melting furnace with the aim of reliably detecting the insurgence of dangerous conditions for workers. The system is composed of two different sensor nodes and a gas analyzer, and it exploits commercial low-cost commercially available sensors.
Collapse
Affiliation(s)
- Lorenzo Parri
- Department of Information Engineering and Mathematics, University of Siena, 53100 Siena, Italy
| | - Marco Tani
- Department of Information Engineering and Mathematics, University of Siena, 53100 Siena, Italy
| | - David Baldo
- Department of Information Engineering and Mathematics, University of Siena, 53100 Siena, Italy
| | - Stefano Parrino
- Department of Information Engineering and Mathematics, University of Siena, 53100 Siena, Italy
| | - Elia Landi
- Department of Information Engineering and Mathematics, University of Siena, 53100 Siena, Italy
| | - Marco Mugnaini
- Department of Information Engineering and Mathematics, University of Siena, 53100 Siena, Italy
| | - Ada Fort
- Department of Information Engineering and Mathematics, University of Siena, 53100 Siena, Italy
| |
Collapse
|
10
|
Liu Z, Zhou W. Energy-Efficient Algorithms for Path Coverage in Sensor Networks. Sensors (Basel) 2023; 23:s23115026. [PMID: 37299754 DOI: 10.3390/s23115026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/13/2023] [Revised: 05/14/2023] [Accepted: 05/23/2023] [Indexed: 06/12/2023]
Abstract
Path coverage attracts many interests in some scenarios, such as object tracing in sensor networks. However, the problem of how to conserve the constrained energy of sensors is rarely considered in existing research. This paper studies two problems in the energy conservation of sensor networks that have not been addressed before. The first problem is called the least movement of nodes on path coverage. It first proves the problem as NP-hard, and then uses curve disjunction to separate each path into some discrete points, and ultimately moves nodes to new positions under some heuristic regulations. The utilized curve disjunction technique makes the proposed mechanism unrestricted by the linear path. The second problem is called the largest lifetime on path coverage. It first separates all nodes into independent partitions by utilizing the method of largest weighted bipartite matching, and then schedules these partitions to cover all paths in the network by turns. We eventually analyze the energy cost of the two proposed mechanisms, and evaluate the effects of some parameters on performance through extensive experiments, respectively.
Collapse
Affiliation(s)
- Zhixiong Liu
- School of Computer Science and Engineering, Changsha University, Changsha 410022, China
| | - Wei Zhou
- Department of Computer Science and Software Engineering, Swinburne University of Technology, Hawthorn 3122, Australia
| |
Collapse
|
11
|
Aimasso A, Ferro CG, Bertone M, Dalla Vedova MDL, Maggiore P. Fiber Bragg Grating Sensor Networks Enhance the In Situ Real-Time Monitoring Capabilities of MLI Thermal Blankets for Space Applications. Micromachines (Basel) 2023; 14:mi14050926. [PMID: 37241550 DOI: 10.3390/mi14050926] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/04/2023] [Revised: 04/20/2023] [Accepted: 04/23/2023] [Indexed: 05/28/2023]
Abstract
The utilization of Fiber Bragg Grating (FBG) sensors in innovative optical sensor networks has displayed remarkable potential in providing precise and dependable thermal measurements in hostile environments on Earth. Multi-Layer Insulation (MLI) blankets serve as critical components of spacecraft and are employed to regulate the temperature of sensitive components by reflecting or absorbing thermal radiation. To enable accurate and continuous monitoring of temperature along the length of the insulative barrier without compromising its flexibility and low weight, FBG sensors can be embedded within the thermal blanket, thereby enabling distributed temperature sensing. This capability can aid in optimizing the thermal regulation of the spacecraft and ensuring the reliable and safe operation of vital components. Furthermore, FBG sensors offer sev eral advantages over traditional temperature sensors, including high sensitivity, immunity to electromagnetic interference, and the ability to operate in harsh environments. These properties make FBG sensors an excellent option for thermal blankets in space applications, where precise temperature regulation is crucial for mission success. Nevertheless, the calibration of temperature sensors in vacuum conditions poses a significant challenge due to the lack of an appropriate calibration reference. Therefore, this paper aimed to investigate innovative solutions for calibrating temperature sensors in vacuum conditions. The proposed solutions have the potential to enhance the accuracy and reliability of temperature measurements in space applications, which can enable engineers to develop more resilient and dependable spacecraft systems.
Collapse
Affiliation(s)
- Alessandro Aimasso
- Department of Mechanical and Aerospace Engineering, Politecnico di Torino, 10129 Turin, Italy
| | - Carlo Giovanni Ferro
- Department of Mechanical and Aerospace Engineering, Politecnico di Torino, 10129 Turin, Italy
| | - Matteo Bertone
- Department of Mechanical and Aerospace Engineering, Politecnico di Torino, 10129 Turin, Italy
| | - Matteo D L Dalla Vedova
- Department of Mechanical and Aerospace Engineering, Politecnico di Torino, 10129 Turin, Italy
| | - Paolo Maggiore
- Department of Mechanical and Aerospace Engineering, Politecnico di Torino, 10129 Turin, Italy
| |
Collapse
|
12
|
Xue D, Chi Y, Wu B, Zhao L. APT Attack Detection Scheme Based on CK Sketch and DNS Traffic. Sensors (Basel) 2023; 23:2217. [PMID: 36850815 PMCID: PMC9964868 DOI: 10.3390/s23042217] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/30/2022] [Revised: 02/05/2023] [Accepted: 02/13/2023] [Indexed: 06/18/2023]
Abstract
In recent years, Advanced Persistent Threat (APT) attacks against sensors have emerged as a prominent security concern. Due to the low level of protection provided by sensors, APT attack organizations are able to develop intrusion schemes that allow them to infiltrate, attack, lurk, spread, and steal information from the target over an extended period of time. Through extensive research on the APT attack process and current defense mechanisms, it has been found that analyzing Domain Name Server (DNS) traffic in the communication control phase is an effective way of detecting APT attacks. However, analyzing APT attacks based on traffic usually involves the detection of a vast amount of DNS traffic, and current data preprocessing methods do not scale down data effectively, leading to low detection efficiency. In previous work, most efforts have been focused on calculating the features of request messages or corresponding messages without considering the association between request messages and corresponding messages. To address these issues, we propose a sketch-based APT attack traffic detection scheme. The scheme leverages the sketch structure to count and compress network traffic, improving the efficiency of APT detection. Our work also analyzes the limitations of traditional sketches in network traffic and proposes an improved sketch scheme. In addition, we propose several effective features for detecting APT attacks. We validate and evaluate our solution using 1,088,280 DNS traffic from a lab network and APT suspicious traffic from netresec and contagio, using eight machine learning models. The experimental results show that for the ExtraTrees model, our solution has a processing time of 0.0638 s and an accuracy of 0.97920, reducing the processing time by approximately 50 times and improving detection accuracy by a small margin compared to a dataset without sketch processing.
Collapse
Affiliation(s)
- Defan Xue
- Beijing Electronic Science and Technology Institute, Beijing 100070, China
| | - Yaping Chi
- Beijing Electronic Science and Technology Institute, Beijing 100070, China
- School of Telecommunications Engineering, Xidian University, Xi’an 710071, China
| | - Bing Wu
- Beijing Electronic Science and Technology Institute, Beijing 100070, China
- School of Telecommunications Engineering, Xidian University, Xi’an 710071, China
| | - Lun Zhao
- Beijing Electronic Science and Technology Institute, Beijing 100070, China
- School of Telecommunications Engineering, Xidian University, Xi’an 710071, China
| |
Collapse
|
13
|
Alexandrescu A. Parallel Processing of Sensor Data in a Distributed Rules Engine Environment through Clustering and Data Flow Reconfiguration. Sensors (Basel) 2023; 23:1543. [PMID: 36772584 PMCID: PMC9919915 DOI: 10.3390/s23031543] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/30/2022] [Revised: 01/27/2023] [Accepted: 01/28/2023] [Indexed: 06/18/2023]
Abstract
An emerging reality is the development of smart buildings and cities, which improve residents' comfort. These environments employ multiple sensor networks, whose data must be acquired and processed in real time by multiple rule engines, which trigger events that enable specific actuators. The problem is how to handle those data in a scalable manner by using multiple processing instances to maximize the system throughput. This paper considers the types of sensors that are used in these scenarios and proposes a model for abstracting the information flow as a weighted dependency graph. Two parallel computing methods are then proposed for obtaining an efficient data flow: a variation of the parallel k-means clustering algorithm and a custom genetic algorithm. Simulation results show that the two proposed flow reconfiguration algorithms reduce the rule processing times and provide an efficient solution for increasing the scalability of the considered environment. Another aspect being discussed is using an open-source cloud solution to manage the system and how to use the two algorithms to increase efficiency. These methods allow for a seamless increase in the number of sensors in the environment by making smart use of the available resources.
Collapse
Affiliation(s)
- Adrian Alexandrescu
- Department of Computer Science and Engineering, Faculty of Automatic Control and Computer Engineering, Gheorghe Asachi Technical University of Iaşi, Str. Prof. dr. doc. Dimitrie Mangeron, nr. 27, 700050 Iași, Romania
| |
Collapse
|
14
|
Volpi A, Tebaldi L, Matrella G, Montanari R, Bottani E. Low-Cost UWB Based Real-Time Locating System: Development, Lab Test, Industrial Implementation and Economic Assessment. Sensors (Basel) 2023; 23:1124. [PMID: 36772163 PMCID: PMC9921910 DOI: 10.3390/s23031124] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/27/2022] [Revised: 01/11/2023] [Accepted: 01/14/2023] [Indexed: 06/18/2023]
Abstract
This paper presents the technical development and subsequent testing of a Real-Time Locating System based on Ultra-Wideband signals, with the aim to appraise its potential implementation in a real industrial case. The system relies on a commercial Radio Indoor Positioning System, called Qorvo MDEK1001, which makes use of UWB RF technology to determine the position of RF-tags placed on an item of interest, which in turn is located in an area covered by specific fixed antennas (anchors). Testing sessions were carried out both in an Italian laboratory and in a real industrial environment, to determine the best configurations according to some selected performance indicators. The results support the adoption of the proposed solution in industrial environments to track assets and work in progress. Moreover, most importantly, the solution developed is cheap in nature: indeed, normally tracking solutions involve a huge investment, quite often not affordable above all by small-, medium- and micro-sized enterprises. The proposed low-cost solution instead, as demonstrated by the economic assessment completing the work, justifies the feasibility of the investment. Hence, results of this paper ultimately constitute a guidance for those practitioners who intend to adopt a similar system in their business.
Collapse
|
15
|
Chikamoto Y, Tsutsumi Y, Sawano H, Ishihara S. Design and Implementation of a Video-Frame Localization System for a Drifting Camera-Based Sewer Inspection System. Sensors (Basel) 2023; 23:793. [PMID: 36679597 PMCID: PMC9861745 DOI: 10.3390/s23020793] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Revised: 01/04/2023] [Accepted: 01/05/2023] [Indexed: 06/17/2023]
Abstract
To reduce the cost of inspecting old sewer pipes, we have been developing a low-cost sewer inspection system that uses drifting wireless cameras to record videos of the interior of a sewer pipe while drifting. The video's data are transmitted to access points placed in utility holes and further transmitted to a video server where each video frame is linked to its capturing position so that users can identify the damaged areas. However, in small-diameter sewer pipes, locating drifting nodes over the full extent of the pipeline using Wi-Fi-based localization is difficult due to the limited reach of radio waves. In addition, there is the unavailability of a GNSS signal. We propose a function to link each video frame to a position based on linear interpolation using landmarks detected by the camera and image processing. Experiments for testing the accuracy of the localization in an underground sewer pipe showed that all utility holes were successfully detected as landmarks, and the maximum location estimation accuracy was less than 11.5% of the maximum interval of landmarks.
Collapse
Affiliation(s)
- Yusuke Chikamoto
- Graduate School of Integrated Science and Technology, Shizuoka University, Hamamatsu 432-8011, Japan
| | - Yuki Tsutsumi
- Graduate School of Integrated Science and Technology, Shizuoka University, Hamamatsu 432-8011, Japan
| | - Hiroaki Sawano
- Department of Information Science, Aichi Institute of Technology, Toyota 470-0392, Japan
| | - Susumu Ishihara
- College of Engineering, Academic Institute, Shizuoka University, Hamamatsu 432-8011, Japan
| |
Collapse
|
16
|
Zhang YW, Han XF, Xiao GQ. An Efficient CRT Based Algorithm for Frequency Determination from Undersampled Real Waveform. Sensors (Basel) 2023; 23:452. [PMID: 36617049 PMCID: PMC9824408 DOI: 10.3390/s23010452] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/14/2022] [Revised: 12/20/2022] [Accepted: 12/27/2022] [Indexed: 06/17/2023]
Abstract
The Chinese Remainder Theorem (CRT) based frequency estimation has been widely studied during the past two decades. It enables one to estimate frequencies by sub-Nyquist sampling rates, which reduces the cost of hardware in a sensor network. Several studies have been done on the complex waveform; however, few works studied its applications in the real waveform case. Different from the complex waveform, existing CRT methods cannot be straightforwardly applied to handle a real waveform's spectrum due to the spurious peaks. To tackle the ambiguity problem, in this paper, we propose the first polynomial-time closed-form Robust CRT (RCRT) for the single-tone real waveform, which can be considered as a special case of RCRT for arbitrary two numbers. The time complexity of the proposed algorithm is O(L), where L is the number of samplers. Furthermore, our algorithm also matches the optimal error-tolerance bound.
Collapse
|
17
|
Ngnamsie Njimbouom S, Lee K, Lee H, Kim J. Predicting Site Energy Usage Intensity Using Machine Learning Models. Sensors (Basel) 2022; 23:82. [PMID: 36616680 PMCID: PMC9823370 DOI: 10.3390/s23010082] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/18/2022] [Revised: 12/13/2022] [Accepted: 12/20/2022] [Indexed: 06/17/2023]
Abstract
Climate change is a shift in nature yet a devastating phenomenon, mainly caused by human activities, sometimes with the intent to generate usable energy required in humankind's daily life. Addressing this alarming issue requires an urge for energy consumption evaluation. Predicting energy consumption is essential for determining what factors affect a site's energy usage and in turn, making actionable suggestions to reduce wasteful energy consumption. Recently, a rising number of researchers have applied machine learning in various fields, such as wind turbine performance prediction, energy consumption prediction, thermal behavior analysis, and more. In this research study, using data publicly made available by the Women in Data Science (WiDS) Datathon 2022 (contains data on building characteristics and information collected by sensors), after appropriate data preparation, we experimented four main machine learning methods (random forest (RF), gradient boost decision tree (GBDT), support vector regressor (SVR), and decision tree for regression (DT)). The most performant model was selected using evaluation metrics: root mean square error (RMSE) and mean absolute error (MAE). The reported results proved the robustness of the proposed concept in capturing the insight and hidden patterns in the dataset, and effectively predicting the energy usage of buildings.
Collapse
Affiliation(s)
| | - Kwonwoo Lee
- Department of Computer Science and Electronic Engineering, Sun Moon University, Asan 31460, Republic of Korea
| | - Hyun Lee
- Department of Computer Science and Electronic Engineering, Sun Moon University, Asan 31460, Republic of Korea
- Division of Computer Science and Engineering, Sun Moon University, Asan 31460, Republic of Korea
| | - Jeongdong Kim
- Department of Computer Science and Electronic Engineering, Sun Moon University, Asan 31460, Republic of Korea
- Division of Computer Science and Engineering, Sun Moon University, Asan 31460, Republic of Korea
- Genome-Based BioIT Convergence Institute, Sun Moon University, Asan 31460, Republic of Korea
| |
Collapse
|
18
|
Bures M, Neumannova K, Blazek P, Klima M, Schvach H, Nema J, Kopecky M, Dygryn J, Koblizek V. A Sensor Network Utilizing Consumer Wearables for Telerehabilitation of Post-Acute COVID-19 Patients. IEEE Internet Things J 2022; 9:23795-23809. [PMID: 36514319 PMCID: PMC9728539 DOI: 10.1109/jiot.2022.3188914] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/27/2022] [Revised: 04/27/2022] [Accepted: 06/30/2022] [Indexed: 06/17/2023]
Abstract
A considerable number of patients with COVID-19 suffer from respiratory problems in the post-acute phase of the disease (the second-third month after disease onset). Individual telerehabilitation and telecoaching are viable, effective options for treating these patients. To treat patients individually, medical staff must have detailed knowledge of their physical activity and condition. A sensor network that utilizes medical-grade devices can be created to collect these data, but the price and availability of these devices might limit such a network's scalability to larger groups of patients. Hence, the use of low-cost commercial fitness wearables is an option worth exploring. This article presents the concept and technical infrastructure of such a telerehabilitation program that started in April 2021 in the Czech Republic. A pilot controlled study with 14 patients with COVID-19 indicated the program's potential to improve patients' physical activity, (85.7% of patients in telerehabilitation versus 41.9% educational group) and exercise tolerance (71.4% of patients in telerehabilitation versus 42.8% of the educational group). Regarding the accuracy of collected data, the used commercial wristband was compared with the medical-grade device in a separate test. Evaluating [Formula: see text]-scores of the intensity of participants' physical activity in this test, the difference in data is not statistically significant at level [Formula: see text]. Hence, the used infrastructure can be considered sufficiently accurate for the telerehabilitation program examined in this study. The technical and medical aspects of the problem are discussed, as well as the technical details of the solution and the lessons learned, regarding using this approach to treat COVID-19 patients in the post-acute phase.
Collapse
Affiliation(s)
- Miroslav Bures
- Department of Computer ScienceFaculty of Electrical EngineeringCzech Technical University in Prague121 35PragueCzechia
| | - Katerina Neumannova
- Department of PhysiotherapyFaculty of Physical CulturePalacký University Olomouc771 47OlomoucCzechia
| | - Pavel Blazek
- Military Medical Management DepartmentFaculty of Military Health SciencesUniversity of Defence500 01Hradec KraloveCzechia
| | - Matej Klima
- Department of Computer ScienceFaculty of Electrical EngineeringCzech Technical University in Prague121 35PragueCzechia
| | - Hynek Schvach
- Military Medical Management DepartmentFaculty of Military Health SciencesUniversity of Defence500 01Hradec KraloveCzechia
| | - Jiri Nema
- Military Medical Management DepartmentFaculty of Military Health SciencesUniversity of Defence500 01Hradec KraloveCzechia
| | - Michal Kopecky
- Faculty of Medicine in Hradec KraloveCharles University110 00PragueCzechia
| | - Jan Dygryn
- Institute of Active Lifestyle, Faculty of Physical Culture, Palacký University Olomouc771 47OlomoucCzechia
| | - Vladimir Koblizek
- Department of PneumologyUniversity Hospital Hradec Kralove500 05Hradec KraloveCzechia
| |
Collapse
|
19
|
Naheem K, Kim MS. A Low-Cost Foot-Placed UWB and IMU Fusion-Based Indoor Pedestrian Tracking System for IoT Applications. Sensors (Basel) 2022; 22:8160. [PMID: 36365858 PMCID: PMC9657577 DOI: 10.3390/s22218160] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/28/2022] [Revised: 10/19/2022] [Accepted: 10/21/2022] [Indexed: 06/16/2023]
Abstract
Among existing wireless and wearable indoor pedestrian tracking solutions, the ultra-wideband (UWB) and inertial measurement unit (IMU) sensors are the popular options due to their accurate and globally referenced positioning, and low-cost and compact size, respectively. However, the UWB position accuracy is compromised by the indoor non-line of sight (NLOS) and the IMU estimation suffers from orientation drift as well as requiring position initialization. To overcome these limitations, this paper proposes a low-cost foot-placed UWB and IMU fusion-based indoor pedestrian tracking system. Our data fusion model is an improved loosely coupled Kalman filter with the inclusion of valid UWB observation detection. In this manner, the proposed system not only adjusts the consumer-grade IMU's accumulated drift but also filters out any NLOS instances in the UWB observation. We validated the performance of the proposed system with two experimental scenarios in a complex indoor environment. The root mean square (RMS) positioning accuracy of our data fusion model is enhanced by 60%, 53%, and 27% compared to that of the IMU-based pedestrian dead reckoning, raw UWB position, and conventional fusion model, respectively, in the single-lap NLOS scenario, and by 70%, 34%, and 12%, respectively, in the multi-lap LOS+NLOS scenario.
Collapse
|
20
|
Zhu J, Sun J. Ecotourism design and plant protection based on sensor network. Front Plant Sci 2022; 13:993838. [PMID: 36172563 PMCID: PMC9510704 DOI: 10.3389/fpls.2022.993838] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/14/2022] [Accepted: 08/03/2022] [Indexed: 06/16/2023]
Abstract
National Forest Park is an important place for the public to carry out forest recreation activities and recognize natural habitats. With the popularization of forest tourism and the increase of forest recreational activities, the pressure on forest habitats has increased. The development of national forest parks is accompanied by opportunities and challenges. The main purpose of this paper is to analyze and study the impact of ecotourism design on plant protection based on sensor network technology. This paper analyzes the impact of tourism on the ecological environment, establishes an ecological environment monitoring system and an ecological tourism resource evaluation system, and studies the functional division of forest parks. Experimental research shows that, as a strictly protected area, the ecological conservation area basically does not conduct scenic spot development and resource mining, nor is it open to tourists. The total area is 852.92 ha, accounting for 22.31% of the total area of the forest park, allowing the ecology of the ecological conservation area to achieve sustainable and healthy development.
Collapse
Affiliation(s)
- Jiang Zhu
- School of Management, Xi’an Jiaotong University, Xi’an, China
- Department of Design, Taiyuan Normal University, Taiyuan, China
| | - JinChun Sun
- School of Management, Xi’an Jiaotong University, Xi’an, China
| |
Collapse
|
21
|
Pittella E, Schiavoni R, Monti G, Masciullo A, Scarpetta M, Cataldo A, Piuzzi E. Split Ring Resonator Network and Diffused Sensing Element Embedded in a Concrete Beam for Structural Health Monitoring. Sensors (Basel) 2022; 22:s22176398. [PMID: 36080855 PMCID: PMC9460216 DOI: 10.3390/s22176398] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/19/2022] [Revised: 08/08/2022] [Accepted: 08/23/2022] [Indexed: 06/01/2023]
Abstract
The aim of this work is to propose two different and integrated sensors for the structural health monitoring of concrete beams. In particular, a diffused sensing element and a split ring resonator network are presented. The first sensor is able to detect the variations in the dielectric properties of the concrete along the whole beam length, for a diffuse monitoring both during the important concrete curing phase and also for the entire life cycle of the concrete beams. The resonators instead work punctually, in their surroundings, allowing an accurate evaluation of the permittivity both during the drying phase and after. This allows the continuous monitoring of any presence of water both inside the concrete beam and at points that can be critical, in the case of beams in dams, bridges or in any case subject to a strong presence of water which could lead to deterioration, or worse, cause serious accidents. Moreover, the punctual sensors are able to detect the presence of cracks in the structure and to localize them.
Collapse
Affiliation(s)
- Erika Pittella
- Department of Information Engineering, Electronics and Telecommunications (DIET), Sapienza University of Rome, 00184 Roma, Italy
| | - Raissa Schiavoni
- Department of Engineering for Innovation, Complesso Ecotekne-Corpo O, University of Salento, 73100 Lecce, Italy
| | - Giuseppina Monti
- Department of Engineering for Innovation, Complesso Ecotekne-Corpo O, University of Salento, 73100 Lecce, Italy
| | - Antonio Masciullo
- Department of Engineering for Innovation, Complesso Ecotekne-Corpo O, University of Salento, 73100 Lecce, Italy
| | - Marco Scarpetta
- Department of Electrical and Information Engineering, Politecnico di Bari, Via E. Orabona 4, 70125 Bari, Italy
| | - Andrea Cataldo
- Department of Engineering for Innovation, Complesso Ecotekne-Corpo O, University of Salento, 73100 Lecce, Italy
| | - Emanuele Piuzzi
- Department of Information Engineering, Electronics and Telecommunications (DIET), Sapienza University of Rome, 00184 Roma, Italy
| |
Collapse
|
22
|
Ransom E, Chen X, Chang FK. Design of a Robust Tool for Deploying Large-Area Stretchable Sensor Networks from Microscale to Macroscale. Sensors (Basel) 2022; 22:4856. [PMID: 35808351 PMCID: PMC9269494 DOI: 10.3390/s22134856] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/15/2022] [Revised: 06/14/2022] [Accepted: 06/17/2022] [Indexed: 06/15/2023]
Abstract
An investigation was conducted to develop an effective automated tool to deploy micro-fabricated stretchable networks of distributed sensors onto the surface of large structures at macroscale to create "smart" structures with embedded distributed sensor networks. Integrating a large network of distributed sensors with structures has been a major challenge in the design of so-called smart structures or devices for cyber-physical applications where a large amount of usage data from structures or devices can be generated for artificial intelligence applications. Indeed, many "island-and-serpentine"-type distributed sensor networks, while promising, remain difficult to deploy. This study aims to enable such networks to be deployed in a safe, automated, and efficient way. To this end, a scissor-hinge controlled system was proposed as the basis for a deployment mechanism for such stretchable sensor networks (SSNs). A model based on a kinematic scissor-hinge mechanism was developed to simulate and design the proposed system to automatically stretch a micro-scaled square network with uniformly distributed sensor nodes. A prototype of an automatic scissor-hinge stretchable tool was constructed during the study with an array of four scissor-hinge mechanisms, each belt-driven by a single stepper motor. Two micro-fabricated SSNs from a 100 mm wafer were fabricated at the Stanford Nanofabrication Facility for this deployment study. The networks were designed to be able to cover an area 100 times their manufacturing size (from a 100 mm diameter wafer to a 1 m2 active area) once stretched. It was demonstrated that the proposed deployment tool could place sensor nodes in prescribed locations efficiently within a drastically shorter time than in current labor-intensive manual deployment methods.
Collapse
Affiliation(s)
- Elliot Ransom
- Department of Aeronautics and Astronautics, Stanford University, Durand Building, 496 Lomita Mall, Stanford, CA 94305, USA; (E.R.); (F.-K.C.)
| | - Xiyuan Chen
- Department of Mechanical Engineering, Stanford University, Building 530, 440 Escondido Mall, Stanford, CA 94305, USA
| | - Fu-Kuo Chang
- Department of Aeronautics and Astronautics, Stanford University, Durand Building, 496 Lomita Mall, Stanford, CA 94305, USA; (E.R.); (F.-K.C.)
| |
Collapse
|
23
|
Wei Z, Wang L, Sun SC, Li B, Guo W. Graph Layer Security: Encrypting Information via Common Networked Physics. Sensors (Basel) 2022; 22:3951. [PMID: 35632362 DOI: 10.3390/s22103951] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/27/2022] [Revised: 05/19/2022] [Accepted: 05/20/2022] [Indexed: 02/01/2023]
Abstract
The proliferation of low-cost Internet of Things (IoT) devices has led to a race between wireless security and channel attacks. Traditional cryptography requires high computational power and is not suitable for low-power IoT scenarios. Whilst recently developed physical layer security (PLS) can exploit common wireless channel state information (CSI), its sensitivity to channel estimation makes them vulnerable to attacks. In this work, we exploit an alternative common physics shared between IoT transceivers: the monitored channel-irrelevant physical networked dynamics (e.g., water/oil/gas/electrical signal-flows). Leveraging this, we propose, for the first time, graph layer security (GLS), by exploiting the dependency in physical dynamics among network nodes for information encryption and decryption. A graph Fourier transform (GFT) operator is used to characterise such dependency into a graph-bandlimited subspace, which allows the generation of channel-irrelevant cipher keys by maximising the secrecy rate. We evaluate our GLS against designed active and passive attackers, using IEEE 39-Bus system. Results demonstrate that GLS is not reliant on wireless CSI, and can combat attackers that have partial networked dynamic knowledge (realistic access to full dynamic and critical nodes remains challenging). We believe this novel GLS has widespread applicability in secure health monitoring and for digital twins in adversarial radio environments.
Collapse
|
24
|
Kim YE, Kim YS, Kim H. Effective Feature Selection Methods to Detect IoT DDoS Attack in 5G Core Network. Sensors (Basel) 2022; 22:3819. [PMID: 35632228 PMCID: PMC9144786 DOI: 10.3390/s22103819] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/30/2022] [Revised: 05/13/2022] [Accepted: 05/16/2022] [Indexed: 06/15/2023]
Abstract
The 5G networks aim to realize a massive Internet of Things (IoT) environment with low latency. IoT devices with weak security can cause Tbps-level Distributed Denial of Service (DDoS) attacks on 5G mobile networks. Therefore, interest in automatic network intrusion detection using machine learning (ML) technology in 5G networks is increasing. ML-based DDoS attack detection in a 5G environment should provide ultra-low latency. To this end, utilizing a feature-selection process that reduces computational complexity and improves performance by identifying features important for learning in large datasets is possible. Existing ML-based DDoS detection technology mostly focuses on DDoS detection learning models on the wired Internet. In addition, studies on feature engineering related to 5G traffic are relatively insufficient. Therefore, this study performed feature selection experiments to reduce the time complexity of detecting and analyzing large-capacity DDoS attacks in real time based on ML in a 5G core network environment. The results of the experiment showed that the performance was maintained and improved when the feature selection process was used. In particular, as the size of the dataset increased, the difference in time complexity increased rapidly. The experiments show that the real-time detection of large-scale DDoS attacks in 5G core networks is possible using the feature selection process. This demonstrates the importance of the feature selection process for removing noisy features before training and detection. As this study conducted a feature study to detect network traffic passing through the 5G core with low latency using ML, it is expected to contribute to improving the performance of the 5G network DDoS attack automation detection technology using AI technology.
Collapse
Affiliation(s)
- Ye-Eun Kim
- Department of Electronics Information and System Engineering, Sangmyung University, Cheonan 31066, Korea; (Y.-E.K.); (Y.-S.K.)
| | - Yea-Sul Kim
- Department of Electronics Information and System Engineering, Sangmyung University, Cheonan 31066, Korea; (Y.-E.K.); (Y.-S.K.)
| | - Hwankuk Kim
- Department of Information Security Engineering, Sangmyung University, Cheonan 31066, Korea
| |
Collapse
|
25
|
Sulzer M, Christen A, Matzarakis A. A Low-Cost Sensor Network for Real-Time Thermal Stress Monitoring and Communication in Occupational Contexts. Sensors (Basel) 2022; 22:s22051828. [PMID: 35270974 PMCID: PMC8914846 DOI: 10.3390/s22051828] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/18/2022] [Revised: 02/18/2022] [Accepted: 02/22/2022] [Indexed: 02/06/2023]
Abstract
The MoBiMet (Mobile Biometeorology System) is a low-cost device for thermal comfort monitoring, designed for long-term deployment in indoor or semi-outdoor occupational contexts. It measures air temperature, humidity, globe temperature, brightness temperature, light intensity, and wind, and is capable of calculating thermal indices (e.g., physiologically equivalent temperature (PET)) on site. It visualizes its data on an integrated display and sends them continuously to a server, where web-based visualizations are available in real-time. Data from many MoBiMets deployed in real occupational settings were used to demonstrate their suitability for large-scale and continued monitoring of thermal comfort in various contexts (industrial, commercial, offices, agricultural). This article describes the design and the performance of the MoBiMet. Alternative methods to determine mean radiant temperature (Tmrt) using a light intensity sensor and a contactless infrared thermopile were tested next to a custom-made black globe thermometer. Performance was assessed by comparing the MoBiMet to an independent mid-cost thermal comfort sensor. It was demonstrated that networked MoBiMets can detect differences of thermal comfort at different workplaces within the same building, and between workplaces in different companies in the same city. The MoBiMets can capture spatial and temporal differences of thermal comfort over the diurnal cycle, as demonstrated in offices with different stories and with different solar irradiances in a single high-rise building. The strongest sustained heat stress was recorded at industrial workplaces with heavy machinery.
Collapse
Affiliation(s)
- Markus Sulzer
- Chair of Environmental Meteorology, Department of Earth and Environmental Sciences, Faculty of Environment and Natural Resources, University of Freiburg, D-79085 Freiburg, Germany; (A.C.); (A.M.)
- Correspondence: ; Tel.: +49-761-203-6822
| | - Andreas Christen
- Chair of Environmental Meteorology, Department of Earth and Environmental Sciences, Faculty of Environment and Natural Resources, University of Freiburg, D-79085 Freiburg, Germany; (A.C.); (A.M.)
| | - Andreas Matzarakis
- Chair of Environmental Meteorology, Department of Earth and Environmental Sciences, Faculty of Environment and Natural Resources, University of Freiburg, D-79085 Freiburg, Germany; (A.C.); (A.M.)
- Research Centre Human Biometeorology, German Meteorological Service, Stefan-Meier-Str. 4, D-79104 Freiburg, Germany
| |
Collapse
|
26
|
Singh RK, Rahmani MH, Weyn M, Berkvens R. Joint Communication and Sensing: A Proof of Concept and Datasets for Greenhouse Monitoring Using LoRaWAN. Sensors (Basel) 2022; 22:1326. [PMID: 35214228 DOI: 10.3390/s22041326] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/30/2021] [Revised: 01/28/2022] [Accepted: 02/01/2022] [Indexed: 11/24/2022]
Abstract
In recent years, greenhouse-based precision agriculture (PA) has been strengthened by utilization of Internet of Things applications and low-power wide area network communication. The advancements in multidisciplinary technologies such as artificial intelligence (AI) have created opportunities to assist farmers further in detecting disease and poor nutrition of plants. Neural networks and other AI techniques need an initial set of measurement campaigns along with extensive datasets as a training set to baseline and evolve different applications. This paper presents LoRaWAN-based greenhouse monitoring datasets over a period of nine months. The dataset has both the network and sensing information from multiple sensor nodes for tomato crops in two different greenhouse environments. The goal is to provide the research community with a dataset to evaluate performance of LoRaWAN inside a greenhouse and develop more efficient PA monitoring techniques. In this paper, we carried out an exploratory data analysis to infer crop growth by analyzing just the LoRaWAN signals and without inclusion of any extra hardware. This work uses a multilayer perceptron artificial neural network to predict the weekly plant growth, trained using RSSI value from sensor data and manual measurement of plant height from the greenhouse. We developed this proof of concept of joint communication and sensing by using generated dataset from the “Proefcentrum Hoogstraten” greenhouse in Belgium. Results for the proposed method yield a root mean square error of 10% in detecting the average plant height inside a greenhouse. In future, we can use this concept of landscape sensing for different supplementary use-cases and to develop optimized methods.
Collapse
|
27
|
Friedrich B, Lübbe C, Steen EE, Bauer JM, Hein A. Using Sensor Graphs for Monitoring the Effect on the Performance of the OTAGO Exercise Program in Older Adults. Sensors (Basel) 2022; 22:493. [PMID: 35062453 PMCID: PMC8780838 DOI: 10.3390/s22020493] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/05/2021] [Revised: 01/03/2022] [Accepted: 01/07/2022] [Indexed: 06/14/2023]
Abstract
The OTAGO exercise program is effective in decreasing the risk for falls of older adults. This research investigated if there is an indication that the OTAGO exercise program has a positive effect on the capacity and as well as on the performance in mobility. We used the data of the 10-months observational OTAGO pilot study with 15 (m = 1, f = 14) (pre-)frail participants aged 84.60 y (SD: 5.57 y). Motion sensors were installed in the flats of the participants and used to monitor their activity as a surrogate variable for performance. We derived a weighted directed multigraph from the physical sensor network, subtracted the weights of one day from a baseline, and used the difference in percent to quantify the change in performance. Least squares was used to compute the overall progress of the intervention (n = 9) and the control group (n = 6). In accordance with previous studies, we found indication for a positive effect of the OTAGO program on the capacity in both groups. Moreover, we found indication that the OTAGO program reduces the decline in performance of older adults in daily living. However, it is too early to conclude causalities from our findings because the data was collected during a pilot study.
Collapse
Affiliation(s)
- Björn Friedrich
- Assistance Systems and Medical Device Technology, Carl von Ossietzky University, Ammerländer Heerstraße 114-118, 26129 Oldenburg, Germany; (C.L.); (E.-E.S.); (A.H.)
| | - Carolin Lübbe
- Assistance Systems and Medical Device Technology, Carl von Ossietzky University, Ammerländer Heerstraße 114-118, 26129 Oldenburg, Germany; (C.L.); (E.-E.S.); (A.H.)
| | - Enno-Edzard Steen
- Assistance Systems and Medical Device Technology, Carl von Ossietzky University, Ammerländer Heerstraße 114-118, 26129 Oldenburg, Germany; (C.L.); (E.-E.S.); (A.H.)
| | - Jürgen Martin Bauer
- Center for Geriatric Medicine, Agaplesion Bethanien Hospital, University of Heidelberg, Rohrbacher Straße 149, 69126 Heidelberg, Germany;
| | - Andreas Hein
- Assistance Systems and Medical Device Technology, Carl von Ossietzky University, Ammerländer Heerstraße 114-118, 26129 Oldenburg, Germany; (C.L.); (E.-E.S.); (A.H.)
| |
Collapse
|
28
|
Marrazzo VR, Laudati A, Vitale M, Fienga F, Iagulli G, Raffone M, Cusano A, Giordano M, Cutolo A, Breglio G. Liquid Resin Infusion Process Validation through Fiber Optic Sensor Technology. Sensors (Basel) 2022; 22:508. [PMID: 35062466 DOI: 10.3390/s22020508] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/22/2021] [Revised: 12/23/2021] [Accepted: 01/07/2022] [Indexed: 11/17/2022]
Abstract
In the proposed work, a fiber-optic-based sensor network was employed for the monitoring of the liquid resin infusion process. The item under test was a panel composed by a skin and four stringers, sensorized in such a way that both the temperature and the resin arrival could be monitored. The network was arranged with 18 Fiber Bragg Gratings (FBGs) working as temperature sensors and 22 fiber optic probes with a modified front-end in order to detect the resin presence. After an in-depth study to find a better solution to install the sensors without affecting the measurements, the system was investigated using a commercial Micron Optics at 0.5 Hz, with a passive split-box connected in order to be able to sense all the sensors simultaneously. The obtained results in terms of resin arrival detection at different locations and the relative temperature trend allowed us to validate an infusion process numerical model, giving us better understanding of what the actual resin flow was and the time needed to dry preform filling during the infusion process.
Collapse
|
29
|
Lapusan C, Hancu O, Rad C. Shape Sensing of Hyper-Redundant Robots Using an AHRS IMU Sensor Network. Sensors (Basel) 2022; 22:373. [PMID: 35009919 PMCID: PMC8749592 DOI: 10.3390/s22010373] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/18/2021] [Revised: 12/30/2021] [Accepted: 01/02/2022] [Indexed: 06/14/2023]
Abstract
The paper proposes a novel approach for shape sensing of hyper-redundant robots based on an AHRS IMU sensor network embedded into the structure of the robot. The proposed approach uses the data from the sensor network to directly calculate the kinematic parameters of the robot in modules operational space reducing thus the computational time and facilitating implementation of advanced real-time feedback system for shape sensing. In the paper the method is applied for shape sensing and pose estimation of an articulated joint-based hyper-redundant robot with identical 2-DoF modules serially connected. Using a testing method based on HIL techniques the authors validate the computed kinematic model and the computed shape of the robot prototype. A second testing method is used to validate the end effector pose using an external sensory system. The experimental results obtained demonstrate the feasibility of using this type of sensor network and the effectiveness of the proposed shape sensing approach for hyper-redundant robots.
Collapse
|
30
|
Khan MN, Rahman HU, Faisal M, Khan F, Ahmad S. An IoT-Enabled Information System for Smart Navigation in Museums. Sensors (Basel) 2021; 22:s22010312. [PMID: 35009853 PMCID: PMC8749525 DOI: 10.3390/s22010312] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/27/2021] [Revised: 11/18/2021] [Accepted: 11/26/2021] [Indexed: 11/24/2022]
Abstract
The Internet of Things (IoT) is a new paradigm that connects objects to provide seamless communication and contextual information to anyone, anywhere, at any time (AAA). These Internet-of-Things-enabled automated objects interact with visitors to present a variety of information during museum navigation and exploration. In this article, a smart navigation and information system (SNIS) prototype for museum navigation and exploration is developed, which delivers an interactive and more exciting museum exploration experience based on the visitor’s personal presence. The objects inside a museum share the information that assist and navigate the visitors about the different sections and objects of the museum. The system was deployed inside Chakdara Museum and experimented with 381 users to achieve the results. For results, different users marked the proposed system in terms of parameters such as interesting, reality, ease of use, satisfaction, usefulness, and user friendly. Of these 381 users, 201 marked the system as most interesting, 138 marked most realistic, 121 marked it as easy-in-use, 219 marked it useful, and 210 marked it as user friendly. These statistics prove the efficiency of SNIS and its usefulness in smart cultural heritage, including smart museums, exhibitions and cultural sites.
Collapse
Affiliation(s)
- Muhammad Nawaz Khan
- Network System & Security Research Group, Department of Computer Science & IT, University of Malakand, Chakdara 18800, Pakistan; (M.N.K.); (H.U.R.); (M.F.)
| | - Haseeb Ur Rahman
- Network System & Security Research Group, Department of Computer Science & IT, University of Malakand, Chakdara 18800, Pakistan; (M.N.K.); (H.U.R.); (M.F.)
| | - Mohammad Faisal
- Network System & Security Research Group, Department of Computer Science & IT, University of Malakand, Chakdara 18800, Pakistan; (M.N.K.); (H.U.R.); (M.F.)
| | - Faheem Khan
- Department of Computer Engineering, Gachon University, Seongnam 13120, Korea;
- Correspondence:
| | - Shabir Ahmad
- Department of Computer Engineering, Gachon University, Seongnam 13120, Korea;
| |
Collapse
|
31
|
Afghantoloee A, Mostafavi MA. A Local 3D Voronoi-Based Optimization Method for Sensor Network Deployment in Complex Indoor Environments. Sensors (Basel) 2021; 21:s21238011. [PMID: 34884013 PMCID: PMC8659870 DOI: 10.3390/s21238011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/27/2021] [Revised: 11/15/2021] [Accepted: 11/25/2021] [Indexed: 11/16/2022]
Abstract
Optimal sensor network deployment in built environments for tracking, surveillance, and monitoring of dynamic phenomena is one of the most challenging issues in sensor network design and applications (e.g., people movement). Most of the current methods for sensor network deployment and optimization are empirical and they often result in important coverage gaps in the monitored areas. To overcome these limitations, several optimization methods have been proposed in the recent years. However, most of these methods oversimplify the environment and do not consider the complexity of 3D architectural nature of the built environments specially for indoor applications (e.g., indoor navigation, evacuation, etc.). In this paper, we propose a novel local optimization algorithm based on a 3D Voronoi diagram, which allows a clear definition of the proximity relations between sensors in 3D indoor environments. This proposed structure is integrated with an IndoorGML model to efficiently manage indoor environment components and their relations as well as the sensors in the network. To evaluate the proposed method, we compared our results with the Genetic Algorithm (GA) and the Covariance Matrix Adaptation Evolution Strategy (CMA-ES) algorithms. The results show that the proposed method achieved 98.86% coverage which is comparable to GA and CMA-ES algorithms, while also being about six times more efficient.
Collapse
Affiliation(s)
- Ali Afghantoloee
- Center for Research in Geospatial Data and Intelligence, Laval University, Quebec City, QC G1V 0A6, Canada;
- Center for Interdisciplinary Research in Rehabilitation and Social Integration, Laval University, Quebec City, QC G1V 0A6, Canada
- Correspondence:
| | - Mir Abolfazl Mostafavi
- Center for Research in Geospatial Data and Intelligence, Laval University, Quebec City, QC G1V 0A6, Canada;
- Center for Interdisciplinary Research in Rehabilitation and Social Integration, Laval University, Quebec City, QC G1V 0A6, Canada
| |
Collapse
|
32
|
Coccia M, Roshani S, Mosleh M. Scientific Developments and New Technological Trajectories in Sensor Research. Sensors (Basel) 2021; 21:7803. [PMID: 34883807 DOI: 10.3390/s21237803] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/23/2021] [Revised: 11/12/2021] [Accepted: 11/12/2021] [Indexed: 02/06/2023]
Abstract
Scientific developments and new technological trajectories in sensors play an important role in understanding technological and social change. The goal of this study is to develop a scientometric analysis (using scientific documents and patents) to explain the evolution of sensor research and new sensor technologies that are critical to science and society. Results suggest that new directions in sensor research are driving technological trajectories of wireless sensor networks, biosensors and wearable sensors. These findings can help scholars to clarify new paths of technological change in sensors and policymakers to allocate research funds towards research fields and sensor technologies that have a high potential of growth for generating a positive societal impact.
Collapse
|
33
|
Waqar S, Pätzold M. Interchannel Interference and Mitigation in Distributed MIMO RF Sensing. Sensors (Basel) 2021; 21:7496. [PMID: 34833570 DOI: 10.3390/s21227496] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/14/2021] [Revised: 11/04/2021] [Accepted: 11/09/2021] [Indexed: 11/24/2022]
Abstract
In this paper, we analyze and mitigate the cross-channel interference, which is found in multiple-input multiple-output (MIMO) radio frequency (RF) sensing systems. For a millimeter wave (mm-Wave) MIMO system, we present a geometrical three-dimensional (3D) channel model to simulate the time-variant (TV) trajectories of a moving scatterer. We collected RF data using a state-of-the-art radar known as Ancortek SDR-KIT 2400T2R4, which is a frequency-modulated continuous wave (FMCW) MIMO radar system operating in the K-band. The Ancortek radar is currently the only K-band MIMO commercial radar system that offers customized antenna configurations. It is shown that this radar system encounters the problem of interference between the various subchannels. We propose an optimal approach to mitigate the problem of cross-channel interference by inducing a propagation delay in one of the channels and apply range gating. The measurement results prove the effectiveness of the proposed approach by demonstrating a complete elimination of the interference problem. The application of the proposed solution on Ancortek’s SDR-KIT 2400T2R4 allows resolving all subchannel links in a distributed MIMO configuration. This allows using MIMO RF sensing techniques to track a moving scatterer (target) regardless of its direction of motion.
Collapse
|
34
|
Palumbo F, Crivello A, Furfari F, Girolami M, Mastropietro A, Manferdelli G, Röcke C, Guye S, Salvá Casanovas A, Caon M, Carrino F, Abou Khaled O, Mugellini E, Denna E, Mauri M, Ward D, Subías-Beltrán P, Orte S, Candea C, Candea G, Rizzo G. "Hi This Is NESTORE, Your Personal Assistant": Design of an Integrated IoT System for a Personalized Coach for Healthy Aging. Front Digit Health 2021; 2:545949. [PMID: 34713033 PMCID: PMC8521925 DOI: 10.3389/fdgth.2020.545949] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2020] [Accepted: 08/28/2020] [Indexed: 11/18/2022] Open
Abstract
In the context of the fourth revolution in healthcare technologies, leveraging monitoring and personalization across different domains becomes a key factor for providing useful services to maintain and promote well-being. This is even more crucial for older people, with aging being a complex multi-dimensional and multi-factorial process which can lead to frailty. The NESTORE project was recently funded by the EU Commission with the aim of supporting healthy older people to sustain their well-being and capacity to live independently. It is based on a multi-dimensional model of the healthy aging process that covers physical activity, nutrition, cognition, and social activity. NESTORE is based on the paradigm of the human-in-the-loop cyber-physical system that, exploiting the availability of Internet of Things technologies combined with analytics in the cloud, provides a virtual coaching system to support healthy aging. This work describes the design of the NESTORE methodology and its IoT architecture. We first model the end-user under several domains, then we present the NESTORE system that, analyzing relevant key-markers, provides coaching activities and personalized feedback to the user. Finally, we describe the validation strategy to assess the effectiveness of NESTORE as a coaching platform for healthy aging.
Collapse
Affiliation(s)
- Filippo Palumbo
- Institute of Information Science and Technologies of the National Research Council of Italy (ISTI-CNR), Pisa, Italy
| | - Antonino Crivello
- Institute of Information Science and Technologies of the National Research Council of Italy (ISTI-CNR), Pisa, Italy
| | - Francesco Furfari
- Institute of Information Science and Technologies of the National Research Council of Italy (ISTI-CNR), Pisa, Italy
| | - Michele Girolami
- Institute of Information Science and Technologies of the National Research Council of Italy (ISTI-CNR), Pisa, Italy
| | - Alfonso Mastropietro
- Institute of Biomedical Technologies of the National Research Council of Italy (ITB-CNR), Segrate, Italy
| | - Giorgio Manferdelli
- Institute of Biomedical Technologies of the National Research Council of Italy (ITB-CNR), Segrate, Italy
| | - Christina Röcke
- University Research Priority Program "Dynamics of Healthy Aging" of the University of Zurich, Zurich, Switzerland
| | - Sabrina Guye
- University Research Priority Program "Dynamics of Healthy Aging" of the University of Zurich, Zurich, Switzerland
| | | | - Maurizio Caon
- University of Applied Sciences and Arts of Western Switzerland HES-SO, Fribourg, Switzerland
| | - Francesco Carrino
- University of Applied Sciences and Arts of Western Switzerland HES-SO, Fribourg, Switzerland
| | - Omar Abou Khaled
- University of Applied Sciences and Arts of Western Switzerland HES-SO, Fribourg, Switzerland
| | - Elena Mugellini
- University of Applied Sciences and Arts of Western Switzerland HES-SO, Fribourg, Switzerland
| | | | | | | | | | - Silvia Orte
- eHealth Unit, Eurecat, Center Tecnològic de Catalunya, Barcelona, Spain
| | | | | | - Giovanna Rizzo
- Institute of Biomedical Technologies of the National Research Council of Italy (ITB-CNR), Segrate, Italy
| |
Collapse
|
35
|
Argañarás JG, Wong YT, Begg R, Karmakar NC. State-of-the-Art Wearable Sensors and Possibilities for Radar in Fall Prevention. Sensors (Basel) 2021; 21:6836. [PMID: 34696046 PMCID: PMC8539234 DOI: 10.3390/s21206836] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/22/2021] [Revised: 10/11/2021] [Accepted: 10/11/2021] [Indexed: 11/25/2022]
Abstract
Radar technology is constantly evolving, and new applications are arising, particularly for the millimeter wave bands. A novel application for radar is gait monitoring for fall prevention, which may play a key role in maintaining the quality of life of people as they age. Alarming statistics indicate that one in three adults aged 65 years or older will experience a fall every year. A review of the sensors used for gait analysis and their applications to technology-based fall prevention interventions was conducted, focusing on wearable devices and radar technology. Knowledge gaps were identified, such as wearable radar development, application specific signal processing and the use of machine learning algorithms for classification and risk assessment. Fall prevention through gait monitoring in the natural environment presents significant opportunities for further research. Wearable radar could be useful for measuring gait parameters and performing fall risk-assessment using statistical methods, and could also be used to monitor obstacles in real-time.
Collapse
Affiliation(s)
- José Gabriel Argañarás
- Electric and Computer Systems Engineering Department, Monash University, Clayton, VIC 3800, Australia; (Y.T.W.); (N.C.K.)
| | - Yan Tat Wong
- Electric and Computer Systems Engineering Department, Monash University, Clayton, VIC 3800, Australia; (Y.T.W.); (N.C.K.)
- Physiology Department, Monash University, Clayton, VIC 3168, Australia
| | - Rezaul Begg
- Institute for Health & Sport, Victoria University, Melbourne, VIC 3032, Australia;
| | - Nemai Chandra Karmakar
- Electric and Computer Systems Engineering Department, Monash University, Clayton, VIC 3800, Australia; (Y.T.W.); (N.C.K.)
| |
Collapse
|
36
|
Kalita H, Thangavelautham J. Strategies for Deploying a Sensor Network to Explore Planetary Lava Tubes. Sensors (Basel) 2021; 21:s21186203. [PMID: 34577410 PMCID: PMC8469258 DOI: 10.3390/s21186203] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/30/2021] [Revised: 08/24/2021] [Accepted: 09/13/2021] [Indexed: 11/27/2022]
Abstract
Recently discovered pits on the surface of the Moon and Mars are theorized to be remnants of lava tubes, and their interior may be in pristine condition. Current landers and rovers are unable to access these areas of high interest. However, multiple small, low-cost robots that can utilize unconventional mobility through ballistic hopping can work as a team to explore these environments. In this work, we propose strategies for exploring these newly discovered Lunar and Martian pits with the help of a mother-daughter architecture for exploration. In this architecture, a highly capable rover or lander would tactically deploy several spherical robots (SphereX) that would hop into the rugged pit environments without risking the rover or lander. The SphereX robots would operate autonomously and perform science tasks, such as getting inside the pit entrance, obtaining high-resolution images, and generating 3D maps of the environment. The SphereX robot utilizes the rover or lander’s resources, including the power to recharge and a long-distance communication link to Earth. Multiple SphereX robots would be placed along the theorized caves/lava tube to maintain a direct line-of-sight connection link from the rover/lander to the team of robots inside. This direct line-of-sight connection link can be used for multi-hop communication and wireless power transfer to sustain the exploration mission for longer durations and even lay a foundation for future high-risk missions.
Collapse
|
37
|
Mertens M, Debard G, Davis J, Devriendt E, Milisen K, Tournoy J, Croonenborghs T, Vanrumste B. Motion Sensor-Based Detection of Outlier Days Supporting Continuous Health Assessment for Single Older Adults. Sensors (Basel) 2021; 21:6080. [PMID: 34577295 PMCID: PMC8472855 DOI: 10.3390/s21186080] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/29/2021] [Revised: 09/03/2021] [Accepted: 09/04/2021] [Indexed: 12/19/2022]
Abstract
The aging population has resulted in interest in remote monitoring of elderly individuals' health and well being. This paper describes a simple unsupervised monitoring system that can automatically detect if an elderly individual's pattern of presence deviates substantially from the recent past. The proposed system uses a small set of low-cost motion sensors and analyzes the produced data to establish an individual's typical presence pattern. Then, the algorithm uses a distance function to determine whether the individual's observed presence for each day significantly deviates from their typical pattern. Empirically, the algorithm is validated on both synthetic data and data collected by installing our system in the residences of three older individuals. In the real-world setting, the system detected, respectively, five, four, and one deviating days in the three locations. The deviating days detected by the system could result from a health issue that requires attention. The information from the system can aid caregivers in assessing the subject's health status and allows for a targeted intervention. Although the system can be refined, we show that otherwise hidden but relevant events (e.g., fall incident and irregular sleep patterns) are detected and reported to the caregiver.
Collapse
Affiliation(s)
- Marc Mertens
- Mobilab & Care, Thomas More University of Applied Sciences Kempen, Kleinhoefstraat 4, 2440 Geel, Belgium;
- Department of Computer Science, KU Leuven, 3001 Heverlee, Belgium; (J.D.); (T.C.)
| | - Glen Debard
- Mobilab & Care, Thomas More University of Applied Sciences Kempen, Kleinhoefstraat 4, 2440 Geel, Belgium;
| | - Jesse Davis
- Department of Computer Science, KU Leuven, 3001 Heverlee, Belgium; (J.D.); (T.C.)
| | - Els Devriendt
- Department of Public Health and Primary Care, Academic Centre for Nursing and Midwifery, KU Leuven, 3000 Leuven, Belgium; (E.D.); (K.M.)
- Department of Geriatric Medicine, University Hospitals Leuven, 3000 Leuven, Belgium;
| | - Koen Milisen
- Department of Public Health and Primary Care, Academic Centre for Nursing and Midwifery, KU Leuven, 3000 Leuven, Belgium; (E.D.); (K.M.)
- Department of Geriatric Medicine, University Hospitals Leuven, 3000 Leuven, Belgium;
| | - Jos Tournoy
- Department of Geriatric Medicine, University Hospitals Leuven, 3000 Leuven, Belgium;
- Department of Public Health and Primary Care, Gerontology and Geriatrics, University of Leuven, 3000 Leuven, Belgium
| | - Tom Croonenborghs
- Department of Computer Science, KU Leuven, 3001 Heverlee, Belgium; (J.D.); (T.C.)
| | - Bart Vanrumste
- eMedia ResearchLab and STADIUS, Department of Electrical Engineering (ESAT), KU Leuven, 3001 Heverlee, Belgium;
| |
Collapse
|
38
|
De Vito S, Esposito E, Massera E, Formisano F, Fattoruso G, Ferlito S, Del Giudice A, D’Elia G, Salvato M, Polichetti T, D’Auria P, Ionescu AM, Di Francia G. Crowdsensing IoT Architecture for Pervasive Air Quality and Exposome Monitoring: Design, Development, Calibration, and Long-Term Validation. Sensors (Basel) 2021; 21:s21155219. [PMID: 34372456 PMCID: PMC8348778 DOI: 10.3390/s21155219] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/12/2021] [Accepted: 07/20/2021] [Indexed: 11/16/2022]
Abstract
A pervasive assessment of air quality in an urban or mobile scenario is paramount for personal or city-wide exposure reduction action design and implementation. The capability to deploy a high-resolution hybrid network of regulatory grade and low-cost fixed and mobile devices is a primary enabler for the development of such knowledge, both as a primary source of information and for validating high-resolution air quality predictive models. The capability of real-time and cumulative personal exposure monitoring is also considered a primary driver for exposome monitoring and future predictive medicine approaches. Leveraging on chemical sensing, machine learning, and Internet of Things (IoT) expertise, we developed an integrated architecture capable of meeting the demanding requirements of this challenging problem. A detailed account of the design, development, and validation procedures is reported here, along with the results of a two-year field validation effort.
Collapse
Affiliation(s)
- Saverio De Vito
- ENEA CR-Portici, TERIN-FSD Division, P. le E. Fermi 1, 80055 Portici, Italy; (E.M.); (F.F.); (G.F.); (S.F.); (A.D.G.); (G.D.); (M.S.); (T.P.); (G.D.F.)
- Correspondence: (S.D.V.); (E.E.)
| | - Elena Esposito
- ENEA CR-Portici, TERIN-FSD Division, P. le E. Fermi 1, 80055 Portici, Italy; (E.M.); (F.F.); (G.F.); (S.F.); (A.D.G.); (G.D.); (M.S.); (T.P.); (G.D.F.)
- Correspondence: (S.D.V.); (E.E.)
| | - Ettore Massera
- ENEA CR-Portici, TERIN-FSD Division, P. le E. Fermi 1, 80055 Portici, Italy; (E.M.); (F.F.); (G.F.); (S.F.); (A.D.G.); (G.D.); (M.S.); (T.P.); (G.D.F.)
| | - Fabrizio Formisano
- ENEA CR-Portici, TERIN-FSD Division, P. le E. Fermi 1, 80055 Portici, Italy; (E.M.); (F.F.); (G.F.); (S.F.); (A.D.G.); (G.D.); (M.S.); (T.P.); (G.D.F.)
| | - Grazia Fattoruso
- ENEA CR-Portici, TERIN-FSD Division, P. le E. Fermi 1, 80055 Portici, Italy; (E.M.); (F.F.); (G.F.); (S.F.); (A.D.G.); (G.D.); (M.S.); (T.P.); (G.D.F.)
| | - Sergio Ferlito
- ENEA CR-Portici, TERIN-FSD Division, P. le E. Fermi 1, 80055 Portici, Italy; (E.M.); (F.F.); (G.F.); (S.F.); (A.D.G.); (G.D.); (M.S.); (T.P.); (G.D.F.)
| | - Antonio Del Giudice
- ENEA CR-Portici, TERIN-FSD Division, P. le E. Fermi 1, 80055 Portici, Italy; (E.M.); (F.F.); (G.F.); (S.F.); (A.D.G.); (G.D.); (M.S.); (T.P.); (G.D.F.)
| | - Gerardo D’Elia
- ENEA CR-Portici, TERIN-FSD Division, P. le E. Fermi 1, 80055 Portici, Italy; (E.M.); (F.F.); (G.F.); (S.F.); (A.D.G.); (G.D.); (M.S.); (T.P.); (G.D.F.)
| | - Maria Salvato
- ENEA CR-Portici, TERIN-FSD Division, P. le E. Fermi 1, 80055 Portici, Italy; (E.M.); (F.F.); (G.F.); (S.F.); (A.D.G.); (G.D.); (M.S.); (T.P.); (G.D.F.)
| | - Tiziana Polichetti
- ENEA CR-Portici, TERIN-FSD Division, P. le E. Fermi 1, 80055 Portici, Italy; (E.M.); (F.F.); (G.F.); (S.F.); (A.D.G.); (G.D.); (M.S.); (T.P.); (G.D.F.)
| | - Paolo D’Auria
- ARPA Campania, Via Vicinale Santa Maria del Pianto Centro Polifunzionale, Torre 1, 80143 Napoli, Italy;
| | - Adrian M. Ionescu
- NanoLab, EPFL-Ecole Politechnique Federal de Lausanne, 1015 Lausanne, Switzerland;
| | - Girolamo Di Francia
- ENEA CR-Portici, TERIN-FSD Division, P. le E. Fermi 1, 80055 Portici, Italy; (E.M.); (F.F.); (G.F.); (S.F.); (A.D.G.); (G.D.); (M.S.); (T.P.); (G.D.F.)
| |
Collapse
|
39
|
Słowikowski M, Kaźmierczak A, Stopiński S, Bieniek M, Szostak S, Matuk K, Augustin L, Piramidowicz R. Photonic Integrated Interrogator for Monitoring the Patient Condition during MRI Diagnosis. Sensors (Basel) 2021; 21:4238. [PMID: 34205594 DOI: 10.3390/s21124238] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/20/2021] [Revised: 06/08/2021] [Accepted: 06/14/2021] [Indexed: 11/17/2022]
Abstract
In this work, we discuss the idea and practical implementation of an integrated photonic circuit-based interrogator of fiber Bragg grating (FBG) sensors dedicated to monitoring the condition of the patients exposed to Magnetic Resonance Imaging (MRI) diagnosis. The presented solution is based on an Arrayed Waveguide Grating (AWG) demultiplexer fabricated in generic indium phosphide technology. We demonstrate the consecutive steps of development of the device from design to demonstrator version of the system with confirmed functionality of monitoring the respiratory rate of the patient. The results, compared to those obtained using commercially available bulk interrogator, confirmed both the general concept and proper operation of the device.
Collapse
|
40
|
Zuidema C, Schumacher CS, Austin E, Carvlin G, Larson TV, Spalt EW, Zusman M, Gassett AJ, Seto E, Kaufman JD, Sheppard L. Deployment, Calibration, and Cross-Validation of Low-Cost Electrochemical Sensors for Carbon Monoxide, Nitrogen Oxides, and Ozone for an Epidemiological Study. Sensors (Basel) 2021; 21:s21124214. [PMID: 34205429 PMCID: PMC8234435 DOI: 10.3390/s21124214] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/26/2021] [Revised: 06/16/2021] [Accepted: 06/16/2021] [Indexed: 11/30/2022]
Abstract
We designed and built a network of monitors for ambient air pollution equipped with low-cost gas sensors to be used to supplement regulatory agency monitoring for exposure assessment within a large epidemiological study. This paper describes the development of a series of hourly and daily field calibration models for Alphasense sensors for carbon monoxide (CO; CO-B4), nitric oxide (NO; NO-B4), nitrogen dioxide (NO2; NO2-B43F), and oxidizing gases (OX-B431)—which refers to ozone (O3) and NO2. The monitor network was deployed in the Puget Sound region of Washington, USA, from May 2017 to March 2019. Monitors were rotated throughout the region, including at two Puget Sound Clean Air Agency monitoring sites for calibration purposes, and over 100 residences, including the homes of epidemiological study participants, with the goal of improving long-term pollutant exposure predictions at participant locations. Calibration models improved when accounting for individual sensor performance, ambient temperature and humidity, and concentrations of co-pollutants as measured by other low-cost sensors in the monitors. Predictions from the final daily models for CO and NO performed the best considering agreement with regulatory monitors in cross-validated root-mean-square error (RMSE) and R2 measures (CO: RMSE = 18 ppb, R2 = 0.97; NO: RMSE = 2 ppb, R2 = 0.97). Performance measures for NO2 and O3 were somewhat lower (NO2: RMSE = 3 ppb, R2 = 0.79; O3: RMSE = 4 ppb, R2 = 0.81). These high levels of calibration performance add confidence that low-cost sensor measurements collected at the homes of epidemiological study participants can be integrated into spatiotemporal models of pollutant concentrations, improving exposure assessment for epidemiological inference.
Collapse
Affiliation(s)
- Christopher Zuidema
- Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, WA 98195, USA; (C.Z.); (C.S.S.); (E.A.); (G.C.); (T.V.L.); (E.W.S.); (M.Z.); (A.J.G.); (E.S.); (J.D.K.)
| | - Cooper S. Schumacher
- Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, WA 98195, USA; (C.Z.); (C.S.S.); (E.A.); (G.C.); (T.V.L.); (E.W.S.); (M.Z.); (A.J.G.); (E.S.); (J.D.K.)
| | - Elena Austin
- Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, WA 98195, USA; (C.Z.); (C.S.S.); (E.A.); (G.C.); (T.V.L.); (E.W.S.); (M.Z.); (A.J.G.); (E.S.); (J.D.K.)
| | - Graeme Carvlin
- Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, WA 98195, USA; (C.Z.); (C.S.S.); (E.A.); (G.C.); (T.V.L.); (E.W.S.); (M.Z.); (A.J.G.); (E.S.); (J.D.K.)
| | - Timothy V. Larson
- Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, WA 98195, USA; (C.Z.); (C.S.S.); (E.A.); (G.C.); (T.V.L.); (E.W.S.); (M.Z.); (A.J.G.); (E.S.); (J.D.K.)
- Department of Civil & Environmental Engineering, University of Washington, Seattle, WA 18195, USA
| | - Elizabeth W. Spalt
- Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, WA 98195, USA; (C.Z.); (C.S.S.); (E.A.); (G.C.); (T.V.L.); (E.W.S.); (M.Z.); (A.J.G.); (E.S.); (J.D.K.)
| | - Marina Zusman
- Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, WA 98195, USA; (C.Z.); (C.S.S.); (E.A.); (G.C.); (T.V.L.); (E.W.S.); (M.Z.); (A.J.G.); (E.S.); (J.D.K.)
| | - Amanda J. Gassett
- Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, WA 98195, USA; (C.Z.); (C.S.S.); (E.A.); (G.C.); (T.V.L.); (E.W.S.); (M.Z.); (A.J.G.); (E.S.); (J.D.K.)
| | - Edmund Seto
- Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, WA 98195, USA; (C.Z.); (C.S.S.); (E.A.); (G.C.); (T.V.L.); (E.W.S.); (M.Z.); (A.J.G.); (E.S.); (J.D.K.)
| | - Joel D. Kaufman
- Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, WA 98195, USA; (C.Z.); (C.S.S.); (E.A.); (G.C.); (T.V.L.); (E.W.S.); (M.Z.); (A.J.G.); (E.S.); (J.D.K.)
- Department of Medicine, University of Washington, Seattle, WA 18195, USA
- Department of Epidemiology, University of Washington, Seattle, WA 18195, USA
| | - Lianne Sheppard
- Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, WA 98195, USA; (C.Z.); (C.S.S.); (E.A.); (G.C.); (T.V.L.); (E.W.S.); (M.Z.); (A.J.G.); (E.S.); (J.D.K.)
- Department of Biostatistics, University of Washington, Seattle, WA 18795, USA
- Correspondence:
| |
Collapse
|
41
|
Makhsous S, Segovia JM, He J, Chan D, Lee L, Novosselov IV, Mamishev AV. Methodology for Addressing Infectious Aerosol Persistence in Real-Time Using Sensor Network. Sensors (Basel) 2021; 21:3928. [PMID: 34200380 DOI: 10.3390/s21113928] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/25/2021] [Revised: 05/28/2021] [Accepted: 05/29/2021] [Indexed: 01/31/2023]
Abstract
Human exposure to infectious aerosols results in the transmission of diseases such as influenza, tuberculosis, and COVID-19. Most dental procedures generate a significant number of aerosolized particles, increasing transmission risk in dental settings. Since the generation of aerosols in dentistry is unavoidable, many clinics have started using intervention strategies such as area-filtration units and extraoral evacuation equipment, especially under the relatively recent constraints of the pandemic. However, the effectiveness of these devices in dental operatories has not been studied. Therefore, the ability of dental personnel to efficiently position and operate such instruments is also limited. To address these challenges, we utilized a real-time sensor network for assessment of aerosol dynamics during dental restoration and cleaning producers with and without intervention. The strategies tested during the procedures were (i) local area High-Efficiency Particle Air (HEPA) filters and (ii) Extra-Oral Suction Device (EOSD). The study was conducted at the University of Washington School of Dentistry using a network of 13 fixed sensors positioned within the operatory and one wearable sensor worn by the dental operator. The sensor network provides time and space-resolved particulate matter (PM) data. Three-dimensional (3D) visualization informed aerosol persistence in the operatory. It was found that area filters did not improve the overall aerosol concentration in dental offices in a significant way. A decrease in PM concentration by an average of 16% was observed when EOSD equipment was used during the procedures. The combination of real-time sensors and 3D visualization can provide dental personnel and facility managers with actionable feedback to effectively assess aerosol transmission in medical settings and develop evidence-based intervention strategies.
Collapse
|
42
|
Simonetti E, Bergamini E, Vannozzi G, Bascou J, Pillet H. Estimation of 3D Body Center of Mass Acceleration and Instantaneous Velocity from a Wearable Inertial Sensor Network in Transfemoral Amputee Gait: A Case Study. Sensors (Basel) 2021; 21:3129. [PMID: 33946325 PMCID: PMC8125485 DOI: 10.3390/s21093129] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/30/2021] [Revised: 04/23/2021] [Accepted: 04/27/2021] [Indexed: 12/04/2022]
Abstract
The analysis of the body center of mass (BCoM) 3D kinematics provides insights on crucial aspects of locomotion, especially in populations with gait impairment such as people with amputation. In this paper, a wearable framework based on the use of different magneto-inertial measurement unit (MIMU) networks is proposed to obtain both BCoM acceleration and velocity. The proposed framework was validated as a proof of concept in one transfemoral amputee against data from force plates (acceleration) and an optoelectronic system (acceleration and velocity). The impact in terms of estimation accuracy when using a sensor network rather than a single MIMU at trunk level was also investigated. The estimated velocity and acceleration reached a strong agreement (ρ > 0.89) and good accuracy compared to reference data (normalized root mean square error (NRMSE) < 13.7%) in the anteroposterior and vertical directions when using three MIMUs on the trunk and both shanks and in all three directions when adding MIMUs on both thighs (ρ > 0.89, NRMSE ≤ 14.0% in the mediolateral direction). Conversely, only the vertical component of the BCoM kinematics was accurately captured when considering a single MIMU. These results suggest that inertial sensor networks may represent a valid alternative to laboratory-based instruments for 3D BCoM kinematics quantification in lower-limb amputees.
Collapse
Affiliation(s)
- Emeline Simonetti
- INI/CERAH, 47 Rue de l’Echat, 94000 Créteil, France;
- Institut de Biomécanique Humaine Georges Charpak, Arts et Métiers, 151 Boulevard de l’Hôpital, 75013 Paris, France;
- Department of Movement, Human and Health Sciences, Interuniversity Centre of Bioengineering of the Human Neuromusculoskeletal System, University of Rome “Foro Italico”, Piazza Lauro de Bosis 15, 00135 Roma, Italy; (E.B.); (G.V.)
| | - Elena Bergamini
- Department of Movement, Human and Health Sciences, Interuniversity Centre of Bioengineering of the Human Neuromusculoskeletal System, University of Rome “Foro Italico”, Piazza Lauro de Bosis 15, 00135 Roma, Italy; (E.B.); (G.V.)
| | - Giuseppe Vannozzi
- Department of Movement, Human and Health Sciences, Interuniversity Centre of Bioengineering of the Human Neuromusculoskeletal System, University of Rome “Foro Italico”, Piazza Lauro de Bosis 15, 00135 Roma, Italy; (E.B.); (G.V.)
| | - Joseph Bascou
- INI/CERAH, 47 Rue de l’Echat, 94000 Créteil, France;
- Institut de Biomécanique Humaine Georges Charpak, Arts et Métiers, 151 Boulevard de l’Hôpital, 75013 Paris, France;
| | - Hélène Pillet
- Institut de Biomécanique Humaine Georges Charpak, Arts et Métiers, 151 Boulevard de l’Hôpital, 75013 Paris, France;
| |
Collapse
|
43
|
Chatzopoulos G, Papadopoulos I, Vallianatos F, Makris JP, Kouli M. Strong Ground Motion Sensor Network for Civil Protection Rapid Decision Support Systems. Sensors (Basel) 2021; 21:s21082833. [PMID: 33920574 PMCID: PMC8073029 DOI: 10.3390/s21082833] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/20/2021] [Revised: 04/05/2021] [Accepted: 04/14/2021] [Indexed: 11/16/2022]
Abstract
Strong motion sensor networks deployed in metropolitan areas are able to provide valuable information for civil protection Decision Support Systems (DSSs) aiming to mitigate seismic risk and earthquake social-economic impact. To this direction, such a network is installed and real-time operated in Chania (Crete Island, Greece), city located in the vicinity of the seismically active south front of the Hellenic Subduction Zone. A blend of both traditional and advanced analysis techniques and interpretation methods of strong ground motion data are presented, studying indicative cases of Chania shaking due to earthquakes in the last couple years. The orientation independent spectral acceleration as well as the spatial distribution of the strong ground motion parameters such as the Peak Ground Acceleration (PGA), Peak Ground Velocity (PGV), Peak Ground Displacement (PGD) and Arias Ιntensity observed at the urban area of Chania are presented with the use of a Geographic Information System (GIS) environment. The results point to the importance of the strong ground motion networks as they can provide valuable information on earthquake hazards prior to and after detrimental seismic events to feed rapid systems supporting civil protection decisions for prevention and emergency response.
Collapse
Affiliation(s)
- Georgios Chatzopoulos
- Institute of Physics of the Earth’s Interior and Geohazards, UNESCO Chair on Solid Earth Physics and Geohazards Risk Reduction, Hellenic Mediterranean University Research Center, 73133 Crete, Greece; (G.C.); (I.P.); (F.V.); (M.K.)
| | - Ilias Papadopoulos
- Institute of Physics of the Earth’s Interior and Geohazards, UNESCO Chair on Solid Earth Physics and Geohazards Risk Reduction, Hellenic Mediterranean University Research Center, 73133 Crete, Greece; (G.C.); (I.P.); (F.V.); (M.K.)
- Seismic Research Centre, University of West Indies, St. Augustine, Trinidad and Tobago
| | - Filippos Vallianatos
- Institute of Physics of the Earth’s Interior and Geohazards, UNESCO Chair on Solid Earth Physics and Geohazards Risk Reduction, Hellenic Mediterranean University Research Center, 73133 Crete, Greece; (G.C.); (I.P.); (F.V.); (M.K.)
- Section of Geophysics–Geothermics, Department of Geology and Geoenvironment, National and Kapodistrian University of Athens, Panepistimiopolis, 15784 Athens, Greece
| | - John P. Makris
- Institute of Physics of the Earth’s Interior and Geohazards, UNESCO Chair on Solid Earth Physics and Geohazards Risk Reduction, Hellenic Mediterranean University Research Center, 73133 Crete, Greece; (G.C.); (I.P.); (F.V.); (M.K.)
- Correspondence: ; Tel.: +30-282-102-3028
| | - Maria Kouli
- Institute of Physics of the Earth’s Interior and Geohazards, UNESCO Chair on Solid Earth Physics and Geohazards Risk Reduction, Hellenic Mediterranean University Research Center, 73133 Crete, Greece; (G.C.); (I.P.); (F.V.); (M.K.)
| |
Collapse
|
44
|
Eichstädt S, Gruber M, Vedurmudi AP, Seeger B, Bruns T, Kok G. Toward Smart Traceability for Digital Sensors and the Industrial Internet of Things. Sensors (Basel) 2021; 21:2019. [PMID: 33809296 DOI: 10.3390/s21062019] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/30/2021] [Revised: 03/03/2021] [Accepted: 03/04/2021] [Indexed: 11/25/2022]
Abstract
The Internet of Things (IoT) is characterized by a large number of interconnected devices or assets. Measurement instruments in the IoT are typically digital in the sense that their indications are available only as digital output. Moreover, a growing number of IoT sensors contain a built-in pre-processing system, e.g., for compensating unwanted effects. This paper considers the application of metrological principles to such so-called “smart sensors” in the IoT. It addresses the calibration of digital sensors, mathematical and semantic approaches, the communication of data quality and the meaning of traceability for the IoT in general.
Collapse
|
45
|
Li W, Jelfs B, Kealy A, Wang X, Moran B. Cooperative Localization Using Distance Measurements for Mobile Nodes. Sensors (Basel) 2021; 21:1507. [PMID: 33671554 DOI: 10.3390/s21041507] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/07/2021] [Revised: 02/11/2021] [Accepted: 02/12/2021] [Indexed: 11/22/2022]
Abstract
This paper considers the two-dimensional (2D) anchorless localization problem for sensor networks in global positioning system (GPS)-denied environments. We present an efficient method, based on the multidimensional scaling (MDS) algorithm, in order to estimate the positions of the nodes in the network using measurements of the inter-node distances. The proposed method takes advantage of the mobility of the nodes to address the location ambiguity problem, i.e., rotation and flip ambiguity, which arises in the anchorless MDS algorithm. Knowledge of the displacement of the moving node is used to produce an analytical solution for the noise-free case. Subsequently, a least squares estimator is presented for the noisy scenario and the associated closed-form solution derived. The simulations show that the proposed algorithm accurately and efficiently estimates the locations of nodes, outperforming alternative methods.
Collapse
|
46
|
Yuan C, Tony A, Yin R, Wang K, Zhang W. Tactile and Thermal Sensors Built from Carbon-Polymer Nanocomposites-A Critical Review. Sensors (Basel) 2021; 21:s21041234. [PMID: 33572485 PMCID: PMC7916377 DOI: 10.3390/s21041234] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/09/2021] [Revised: 02/01/2021] [Accepted: 02/03/2021] [Indexed: 12/16/2022]
Abstract
This paper provides a critical review of tactile and thermal sensors which are built from carbon nanomaterial-filled polymer composites (CNPCs). To make the review more comprehensive and systematic, the sensors are viewed as a system, and a general knowledge architecture for a system called function-context-behavior-principle-state-structure (FCBPSS) is employed to classify information as well as knowledge related to CNPC sensors. FCBPSS contains six basic concepts, namely, F: function, C: context, B: behavior, P: principle, and SS: state and structure. As such, the principle that explains why such composites can work as temperature and pressure sensors, various structures of the CNPC sensor, which realize the principle, and the behavior and performance of CNPC sensors are discussed in this review. This review also discusses the fabrication of the CNPC sensor. Based on the critical review and analysis, the future directions of research on the CNPC sensor are discussed; in particular, the need to have a network of CNPC sensors that can be installed on curved bodies such as those of robots is elaborated.
Collapse
Affiliation(s)
- Chenwang Yuan
- Department of Mechanical Engineering, University of Saskatchewan, Saskatoon, SK S7N 5A9, Canada; (C.Y.); (A.T.)
| | - Anthony Tony
- Department of Mechanical Engineering, University of Saskatchewan, Saskatoon, SK S7N 5A9, Canada; (C.Y.); (A.T.)
| | - Ruixue Yin
- School of Mechanical and Power Engineering, East China University of Science and Technology, Shanghai 200237, China;
| | - Kemin Wang
- School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200444, China;
| | - Wenjun Zhang
- Department of Mechanical Engineering, University of Saskatchewan, Saskatoon, SK S7N 5A9, Canada; (C.Y.); (A.T.)
- Correspondence: ; Tel.: +1-3069665478
| |
Collapse
|
47
|
Zempo K, Arai T, Aoki T, Okada Y. Sensing Framework for the Internet of Actors in the Value Co-Creation Process with a Beacon-Attachable Indoor Positioning System. Sensors (Basel) 2020; 21:s21010083. [PMID: 33375596 PMCID: PMC7795509 DOI: 10.3390/s21010083] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/17/2020] [Revised: 12/19/2020] [Accepted: 12/22/2020] [Indexed: 01/10/2023]
Abstract
To evaluate and improve the value of a service, it is important to measure not only the outcomes, but also the process of the service. Value co-creation (VCC) is not limited to outcomes, especially in interpersonal services based on interactions between actors. In this paper, a sensing framework for a VCC process in retail stores is proposed by improving an environment recognition based indoor positioning system with high positioning performance in a metal shelf environment. The conventional indoor positioning systems use radio waves; therefore, errors are caused by reflection, absorption, and interference from metal shelves. An improvement in positioning performance was achieved in the proposed method by using an IR (infrared) slit and IR light, which avoids such errors. The system was designed to recognize many and unspecified people based on the environment recognition method that the receivers had installed, in the service environment. In addition, sensor networking was also conducted by adding a function to transmit payload and identification simultaneously to the beacons that were attached to positioning objects. The effectiveness of the proposed method was verified by installing it not only in an experimental environment with ideal conditions, but posteriorly, the system was tested in real conditions, in a retail store. In our experimental setup, in a comparison with equal element numbers, positioning identification was possible within an error of 96.2 mm in a static environment in contrast to the radio wave based method where an average positioning error of approximately 648 mm was measured using the radio wave based method (Bluetooth low-energy fingerprinting technique). Moreover, when multiple beacons were used simultaneously in our system within the measurement range of one receiver, the appropriate setting of the pulse interval and jitter rate was implemented by simulation. Additionally, it was confirmed that, in a real scenario, it is possible to measure the changes in movement and positional relationships between people. This result shows the feasibility of measuring and evaluating the VCC process in retail stores, although it was difficult to measure the interaction between actors.
Collapse
Affiliation(s)
- Keiichi Zempo
- Faculty of Engineering, Information and Systems, University of Tsukuba, Tsukuba 305-8573, Ibaraki, Japan;
- Correspondence:
| | - Taiga Arai
- Graduate School of Systems and Information Engineering, University of Tsukuba, Tsukuba 305-8573, Ibaraki, Japan; (T.A.); (T.A.)
| | - Takuya Aoki
- Graduate School of Systems and Information Engineering, University of Tsukuba, Tsukuba 305-8573, Ibaraki, Japan; (T.A.); (T.A.)
| | - Yukihiko Okada
- Faculty of Engineering, Information and Systems, University of Tsukuba, Tsukuba 305-8573, Ibaraki, Japan;
| |
Collapse
|
48
|
Cofta P, Orłowski C, Lebiedź J. Trust-Based Model for the Assessment of the Uncertainty of Measurements in Hybrid IoT Networks. Sensors (Basel) 2020; 20:E6956. [PMID: 33291417 PMCID: PMC7730054 DOI: 10.3390/s20236956] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/28/2020] [Revised: 11/26/2020] [Accepted: 12/03/2020] [Indexed: 11/16/2022]
Abstract
The aim of this paper is to introduce a NUT model (NUT: network-uncertainty-trust) that aids the decrease of the uncertainty of measurements in autonomous hybrid Internet of Things sensor networks. The problem of uncertainty in such networks is a consequence of various operating conditions and varied quality of measurement nodes, making statistical approach less successful. This paper presents a model for decreasing the uncertainty through the use of socially inspired metaphors of reputation, trust, and confidence that are the untapped latent information. The model described in the paper shows how the individual reputation of each node can be assessed on the basis of opinions provided by other nodes of the hybrid measurement network, and that this method allows to assess the extent of uncertainty the node introduces to the network. This, in turn, allows nodes of low uncertainty to have a greater impact on the reconstruction of values. The verification of the model, as well as examples of its applicability to air quality measurements are presented as well. Simulations demonstrate that the use of the model can decrease the uncertainty by up to 55% while using the EWMA (exponentially weighted moving average) algorithm, as compared to the reference one.
Collapse
Affiliation(s)
- Piotr Cofta
- Faculty of Telecommunications, Computer Science and Technology, UTP University of Science and Technology, 85-796 Bydgoszcz, Poland
| | - Cezary Orłowski
- Institute of Management and Finance, WSB University in Gdansk, 80-266 Gdansk, Poland;
| | - Jacek Lebiedź
- Faculty of ETI, Gdansk University of Technology, 80-233 Gdansk, Poland;
| |
Collapse
|
49
|
Alanezi MA, Bouchekara HREH, Javaid MS. Optimizing Router Placement of Indoor Wireless Sensor Networks in Smart Buildings for IoT Applications. Sensors (Basel) 2020; 20:s20216212. [PMID: 33143362 PMCID: PMC7663200 DOI: 10.3390/s20216212] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/10/2020] [Revised: 10/10/2020] [Accepted: 10/27/2020] [Indexed: 06/11/2023]
Abstract
Internet of Things (IoT) is characterized by a system of interconnected devices capable of communicating with each other to carry out specific useful tasks. The connection between these devices is ensured by routers distributed in a network. Optimizing the placement of these routers in a distributed wireless sensor network (WSN) in a smart building is a tedious task. Computer-Aided Design (CAD) programs and software can simplify this task since they provide a robust and efficient tool. At the same time, experienced engineers from different backgrounds must play a prominent role in the abovementioned task. Therefore, specialized companies rely on both; a useful CAD tool along with the experience and the flair of a sound expert/engineer to optimally place routers in a WSN. This paper aims to develop a new approach based on the interaction between an efficient CAD tool and an experienced engineer for the optimal placement of routers in smart buildings for IoT applications. The approach follows a step-by-step procedure to weave an optimal network infrastructure, having both automatic and designer-intervention modes. Several case studies have been investigated, and the obtained results show that the developed approach produces a synthesized network with full coverage and a reduced number of routers.
Collapse
Affiliation(s)
- Mohammed A. Alanezi
- Department of Computer Science and Engineering Technology, University of Hafr Al Batin, Hafr Al Batin 31991, Saudi Arabia;
| | | | - Muhammad S. Javaid
- Department of Electrical Engineering, University of Hafr Al Batin, Hafr Al Batin 31991, Saudi Arabia;
| |
Collapse
|
50
|
Peng H, Liu C, Zhao D, Hu Z, Han J. Security Evaluation under Different Exchange Strategies Based on Heterogeneous CPS Model in Interdependent Sensor Networks. Sensors (Basel) 2020; 20:E6123. [PMID: 33126431 PMCID: PMC7662949 DOI: 10.3390/s20216123] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/13/2020] [Revised: 10/19/2020] [Accepted: 10/22/2020] [Indexed: 11/24/2022]
Abstract
In the real Internet of Everything scenario, many large-scale information systems can be converted into interdependent sensor networks, such as smart grids, smart medical systems, and industrial Internet systems. These complex systems usually have multiple interdependent sensor networks. Small faults or failure behaviors between networks may cause serious cascading failure effects of the entire system. Therefore, in this paper, we will focus on the security of interdependent sensor networks. Firstly, by calculating the size of the largest functional component in the entire network, the impact of random attacks on the security of interdependent sensor networks is analyzed. Secondly, it compares and analyzes the impact of cascading failures between interdependent sensor networks under different switching edge strategies. Finally, the simulation results verify the effect of the security of the system under different strategies, and give a better exchange strategy to enhance the security of the system. In addition, the research work in this article can help design how to further optimize the topology of interdependent sensor networks by reducing the impact of cascading failures.
Collapse
Affiliation(s)
| | | | - Dandan Zhao
- College of Mathematics and Computer Science, Zhejiang Normal University, Jinhua 321004, China; (H.P.); (C.L.); (Z.H.); (J.H.)
| | | | | |
Collapse
|