Smart Air Quality Monitoring IoT-Based Infrastructure for Industrial Environments

Deficient air quality in industrial environments creates a number of problems that affect both the staff and the ecosystems of a particular area. To address this, periodic measurements must be taken to monitor the pollutant substances discharged into the atmosphere. However, the deployed system should also be adapted to the specific requirements of the industry. This paper presents a complete air quality monitoring infrastructure based on the IoT paradigm that is fully integrable into current industrial systems. It includes the development of two highly precise compact devices to facilitate real-time monitoring of particulate matter concentrations and polluting gases in the air. These devices are able to collect other information of interest, such as the temperature and humidity of the environment or the Global Positioning System (GPS) location of the device. Furthermore, machine learning techniques have been applied to the Big Data collected by this system. The results identify that the Gaussian Process Regression is the technique with the highest accuracy among the air quality data sets gathered by the devices. This provides our solution with, for instance, the intelligence to predict when safety levels might be surpassed.

An Analytical Approach to Flow-Guided Nanocommunication Networks

Continuous progress of nanocommunications and nano-networking is opening the door to the development of innovative yet unimaginable services, with a special focus on medical applications. Among several nano-network topologies, flow-guided nanocommunication networks have recently emerged as a promising solution to monitoring, gathering information, and data communication inside the human body. In particular, flow-guided nano-networks display a number of specific characteristics, such as the type of nodes comprising the network or the ability of a nano-node to transmit successfully, which significantly differentiates them from other types of networks, both at the nano and larger scales. This paper presents the first analytical study on the behavior of these networks, with the objective of evaluating their metrics mathematically. To this end, a theoretical framework of the flow-guided nano-networks is developed and an analytical model derived. The main results reveal that, due to frame collisions, there is an optimal number of nano-nodes for any flow-guided network, which, as a consequence, limits the maximum achievable throughput. Finally, the analytical results obtained are validated through simulations and are further discussed.

A Prototype Framework Design for Assisting the Detection of Atrial Fibrillation Using a Generic Low-Cost Biomedical Sensor

Cardiovascular diseases are the leading cause of death around the world. As a result, low-cost biomedical sensors have been gaining importance in business and research over the last few decades. Their main benefits include their small size, light weight, portability and low power consumption. Despite these advantages, they are not generally used for clinical monitoring mainly because of their low accuracy in data acquisition. In this emerging technological context, this paper contributes by discussing a methodology to help practitioners build a prototype framework based on a low-cost commercial sensor. The resulting application consists of four modules; namely, a digitalization module whose input is an electrocardiograph signal in portable document format (PDF) or joint photographic expert group format (JPEG), a module to further process and filter the digitalized signal, a selectable data calibration module and, finally, a module implementing a classification algorithm to distinguish between individuals with normal sinus rhythms and those with atrial fibrillation. This last module employs our recently published symbolic recurrence quantification analysis (SRQA) algorithm on a time series of RR intervals. Moreover, we show that the algorithm applies to any biomedical low-cost sensor, achieving good results without requiring.

Machine Learning Techniques Applied to Dose Prediction in Computed Tomography Tests

Increasingly more patients exposed to radiation from computed axial tomography (CT) will have a greater risk of developing tumors or cancer that are caused by cell mutation in the future. A minor dose level would decrease the number of these possible cases. However, this framework can result in medical specialists (radiologists) not being able to detect anomalies or lesions. This work explores a way of addressing these concerns, achieving the reduction of unnecessary radiation without compromising the diagnosis. We contribute with a novel methodology in the CT area to predict the precise radiation that a patient should be given to accomplish this goal. Specifically, from a real dataset composed of the dose data of over fifty thousand patients that have been classified into standardized protocols (skull, abdomen, thorax, pelvis, etc.), we eliminate atypical information (outliers), to later generate regression curves employing diverse well-known Machine Learning techniques. As a result, we have chosen the best analytical technique per protocol; a selection that was thoroughly carried out according to traditional dosimetry parameters to accurately quantify the dose level that the radiologist should apply in each CT test.

Determination of progesterone in saliva using an electrochemical immunosensor and a COTS-based portable potentiostat

This paper describes the reliable determination of progesterone (P4) in undiluted saliva making use of a disposable amperometric immunosensors implemented on low-cost and portable device/potentiostat constructed with commercial-off-the-shelf (COTS) components. The immunosensor allows the fast (45 min), selective and sensitive determination (5 pg mL^-1 LOD) of P4 using amperometry in stirred solutions. The immunosensor was coupled to the COTS-based potentiostat and amperometry was made into drops of quiescent solutions. No significant differences were apparent between the analytical performance achieved with the immunosensor for P4 using both a conventional and the COST-based potentiostats. The practical applicability of the immunosensor coupled with the COTS-based potentiostat was demonstrated by determining the endogenous P4 content in different undiluted saliva samples with highly variable endogenous contents of the target hormone. The obtained results were in good agreement with those provided by the conventional ELISA methodology and with the contents reported in the literature for samples with similar characteristics. This validated the combined device for the reliable and minimally invasive determination of the target hormone involving a very simple protocol and taking only 45 min.

On the Nature of Energy-Feasible Wireless Nanosensor Networks

Electromagnetic nanocommunications, understood as the communication between electronic nanoscale devices through electromagnetic waves in the terahertz band, has attracted increasing attention in recent years. In this regard, several solutions have already been proposed. However, many of them do not sufficiently capture the significance of the limitations in nanodevice energy-gathering and storing capacity. In this paper, we address key factors affecting the energy consumption of nanodevices, highlighting the effect of the communication scheme employed. Then, we also examine how nanodevices are powered, focusing on the main parameters governing the powering nanosystem. Different mathematical expressions are derived to analyze the impact of these parameters on its performance. Based on these expressions, the functionality of a nanogenerator is evaluated to gain insight into the conditions under which a wireless nanosensor network (WNSN) is viable from the energetic point of view. The results reveal that a micrometer-sized piezoelectric system in high-lossy environments (exceeding 100 dB/mm) becomes inoperative for transmission distances over 1.5 mm by its inability to harvest and store the amount of energy required to overcome the path loss.

Evaluating the More Suitable ISM Frequency Band for IoT-Based Smart Grids: A Quantitative Study of 915 MHz vs. 2400 MHz

IoT has begun to be employed pervasively in industrial environments and critical infrastructures thanks to its positive impact on performance and efficiency. Among these environments, the Smart Grid (SG) excels as the perfect host for this technology, mainly due to its potential to become the motor of the rest of electrically-dependent infrastructures. To make this SG-oriented IoT cost-effective, most deployments employ unlicensed ISM bands, specifically the 2400 MHz one, due to its extended communication bandwidth in comparison with lower bands. This band has been extensively used for years by Wireless Sensor Networks (WSN) and Mobile Ad-hoc Networks (MANET), from which the IoT technologically inherits. However, this work questions and evaluates the suitability of such a “default” communication band in SG environments, compared with the 915 MHz ISM band. A comprehensive quantitative comparison of these bands has been accomplished in terms of: power consumption, average network delay, and packet reception rate. To allow such a study, a dual-band propagation model specifically designed for the SG has been derived, tested, and incorporated into the well-known TOSSIM simulator. Simulation results reveal that only in the absence of other 2400 MHz interfering devices (such as WiFi or Bluetooth) or in small networks, is the 2400 MHz band the best option. In any other case, SG-oriented IoT quantitatively perform better if operating in the 915 MHz band.

Conceptual Design of a Nano-Networking Device

Nanotechnology is an emerging scientific area whose advances, among many others, have a positive direct impact on the miniaturization of electronics. This unique technology enables the possibility to design and build electronic components as well as complete devices (called nanomachines or nanodevices) at the nano scale. A nanodevice is expected to be an essential element able to operate in a nanonetwork, where a huge number of them would coordinate to acquire data, process the information gathered, and wirelessly transmit those data to end-points providing innovative services in many key scenarios, such as the human body or the environment. This paper is aimed at studying the feasibility of this type of device by carefully examining their main component parts, namely the nanoprocessor, nanomemory, nanoantenna, and nanogenerator. To this end, a thorough state-of-the-art review is conveyed to discuss, substantiate, and select the most suitable current technology (commercial or pre-commercial) for each component. Then, we further contribute by developing a complete conceptual nanodevice layout taking into consideration its ultra-small size (similar to a blood cell) and its very restricted capabilities (e.g., processing, memory storage, telecommunication, and energy management). The required resources as well as the power consumption are realistically estimated.

A comprehensive WSN-based approach to efficiently manage a Smart Grid

The Smart Grid (SG) is conceived as the evolution of the current electrical grid representing a big leap in terms of efficiency, reliability and flexibility compared to today's electrical network. To achieve this goal, the Wireless Sensor Networks (WSNs) are considered by the scientific/engineering community to be one of the most suitable technologies to apply SG technology to due to their low-cost, collaborative and long-standing nature. However, the SG has posed significant challenges to utility operators—mainly very harsh radio propagation conditions and the lack of appropriate systems to empower WSN devices—making most of the commercial widespread solutions inadequate. In this context, and as a main contribution, we have designed a comprehensive ad-hoc WSN-based solution for the Smart Grid (SENSED-SG) that focuses on specific implementations of the MAC, the network and the application layers to attain maximum performance and to successfully deal with any arising hurdles. Our approach has been exhaustively evaluated by computer simulations and mathematical analysis, as well as validation within real test-beds deployed in controlled environments. In particular, these test-beds cover two of the main scenarios found in a SG; on one hand, an indoor electrical substation environment, implemented in a High Voltage AC/DC laboratory, and, on the other hand, an outdoor case, deployed in the Transmission and Distribution segment of a power grid. The results obtained show that SENSED-SG performs better and is more suitable for the Smart Grid than the popular ZigBee WSN approach.

Current trends in wireless mesh sensor networks: a review of competing approaches

Finding a complete mesh-based solution for low-rate wireless personal area networks (LR-WPANs) is still an open issue. To cope with this concern, different competing approaches have emerged in the Wireless Mesh Sensor Networks (WMSNs) field in the last few years. They are usually supported by the IEEE 802.15.4 standard, the most commonly adopted LR-WPAN recommendation for point-to-point topologies. In this work, we review the most relevant and up-to-date WMSN solutions that extend the IEEE 802.15.4 standard to multi-hop mesh networks. To conduct this review, we start by identifying the most significant WMSN requirements (i.e., interoperability, robustness, scalability, mobility or energy-efficiency) that reveal the benefits and shortcomings of each proposal. Then, we re-examine thoroughly the group of proposals following different design guidelines which are usually considered by end-users and developers. Among all of the approaches reviewed, we highlight the IEEE 802.15.5 standard, a recent recommendation that, in its LR-WPAN version, fully satisfies the greatest number of WMSN requirements. As a result, IEEE 802.15.5 can be an appropriate solution for a wide-range of applications, unlike the majority of the remaining solutions reviewed, which are usually designed to solve particular problems, for instance in the home, building and industrial sectors. In this sense, a description of IEEE 802.15.5 is also included, paying special attention to its efficient energy-saving mechanisms. Finally, possible improvements of this recommendation are pointed out in order to offer hints for future research.

A Comprehensive approach to WSN-based ITS applications: a survey

In order to perform sensing tasks, most current Intelligent Transportation Systems (ITS) rely on expensive sensors, which offer only limited functionality. A more recent trend consists of using Wireless Sensor Networks (WSN) for such purpose, which reduces the required investment and enables the development of new collaborative and intelligent applications that further contribute to improve both driving safety and traffic efficiency. This paper surveys the application of WSNs to such ITS scenarios, tackling the main issues that may arise when developing these systems. The paper is divided into sections which address different matters including vehicle detection and classification as well as the selection of appropriate communication protocols, network architecture, topology and some important design parameters. In addition, in line with the multiplicity of different technologies that take part in ITS, it does not consider WSNs just as stand-alone systems, but also as key components of heterogeneous systems cooperating along with other technologies employed in vehicular scenarios.

Wireless Sensor Network deployment for monitoring wildlife passages

Wireless Sensor Networks (WSNs) are being deployed in very diverse application scenarios, including rural and forest environments. In these particular contexts, specimen protection and conservation is a challenge, especially in natural reserves, dangerous locations or hot spots of these reserves (i.e., roads, railways, and other civil infrastructures). This paper proposes and studies a WSN based system for generic target (animal) tracking in the surrounding area of wildlife passages built to establish safe ways for animals to cross transportation infrastructures. In addition, it allows target identification through the use of video sensors connected to strategically deployed nodes. This deployment is designed on the basis of the IEEE 802.15.4 standard, but it increases the lifetime of the nodes through an appropriate scheduling. The system has been evaluated for the particular scenario of wildlife monitoring in passages across roads. For this purpose, different schemes have been simulated in order to find the most appropriate network operational parameters. Moreover, a novel prototype, provided with motion detector sensors, has also been developed and its design feasibility demonstrated. Original software modules providing new functionalities have been implemented and included in this prototype. Finally, main performance evaluation results of the whole system are presented and discussed in depth.