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Naseem S, Anwar M, Faheem M, Fayyaz M, Malik MSA. Bayesian-Edge system for classification and segmentation of skin lesions in Internet of Medical Things. Skin Res Technol 2024; 30:e13878. [PMID: 39081158 PMCID: PMC11289430 DOI: 10.1111/srt.13878] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2023] [Accepted: 07/05/2024] [Indexed: 08/03/2024]
Abstract
BACKGROUND Skin diseases are severe diseases. Identification of these severe diseases depends upon the abstraction of atypical skin regions. The segmentation of these skin diseases is essential to rheumatologists in risk impost and for valuable and vital decision-making. Skin lesion segmentation from images is a crucial step toward achieving this goal-timely exposure of malignancy in psoriasis expressively intensifies the persistence ratio. Defies occur when people presume skin diseases they have without accurately and precisely incepted. However, analyzing malignancy at runtime is a big challenge due to the truncated distinction of the visual similarity between malignance and non-malignance lesions. However, images' different shapes, contrast, and vibrations make skin lesion segmentation challenging. Recently, various researchers have explored the applicability of deep learning models to skin lesion segmentation. MATERIALS AND METHODS This paper introduces a skin lesions segmentation model that integrates two intelligent methodologies: Bayesian inference and edge intelligence. In the segmentation model, we deal with edge intelligence to utilize the texture features for the segmentation of skin lesions. In contrast, Bayesian inference enhances skin lesion segmentation's accuracy and efficiency. RESULTS We analyze our work along several dimensions, including input data (datasets, preprocessing, and synthetic data generation), model design (architecture, modules), and evaluation aspects (data annotation requirements and segmentation performance). We discuss these dimensions from seminal works and a systematic viewpoint and examine how these dimensions have influenced current trends. CONCLUSION We summarize our work with previously used techniques in a comprehensive table to facilitate comparisons. Our experimental results show that Bayesian-Edge networks can boost the diagnostic performance of skin lesions by up to 87.80% without incurring additional parameters of heavy computation.
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Affiliation(s)
- Shahid Naseem
- Department of Information SciencesDivision of Science and TechnologyUniversity of EducationLahorePakistan
| | - Muhammad Anwar
- Department of Information SciencesDivision of Science and TechnologyUniversity of EducationLahorePakistan
| | - Muhammad Faheem
- School of Technology and InnovationsUniversity of VaasaVaasaFinland
| | - Muhammad Fayyaz
- Department of Computer ScienceFAST National University of Computer & Emerging SciencesChiniot‐Faisalabad CampusIslamabadPakistan
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Qureshi KN, Khan A, Jamil SUU, Sharma B, Jeon G. Internet of Things enables smart solid waste bin management system for a sustainable environment. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:125188-125196. [PMID: 37453012 DOI: 10.1007/s11356-023-28611-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Accepted: 07/01/2023] [Indexed: 07/18/2023]
Abstract
Solid waste management (SWM) is a pressing concern and significant research topic that requires attention from citizens and government stakeholders. Most of the responsibility of waste management is on the municipal sector for its collection, reallocation, and reuse of other resources. The daily solid waste production is more than 54,850 tonnes in urban areas and is difficult to manage due to limited resources and different administrative and service issues. New technologies are playing their role in this area but how to integrate the technologies is still a question, especially for developing countries. This paper is divided into two main phases including a detailed investigation and a technological solution. In the first phase, the data is collected by using the qualitative method to investigate and identify the issues related to waste management. After a detailed investigation and results, the gap is identified by using statistical analysis and proposed a technological solution in the second phase. The technology-based solution is used to control and manage waste with a low-cost, fast, and manageable solution. The new sensor-based technologies, cellular networks, and social media are utilized to monitor the trash in the areas. The trash management department receives notification via cellular services to locate the dustbin when the dustbin reaches a maximum level so the department may send a waste collector vehicle to the relevant spot to collect waste. The smart and fast solution will connect all stakeholders in the community and reduce the cost and time and make the collection process faster. The experiment results indicated the issues and effectiveness of the proposed solution.
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Affiliation(s)
- Kashif Naseer Qureshi
- Department of Electronic & Computer Engineering, University of Limerick, Limerick, V94 T9PX, Ireland
| | - Ayesha Khan
- Department of Earth and Environmental Sciences, Bahria University, Islamabad, Pakistan
| | | | - Bhisham Sharma
- Chitkara University Institute of Engineering and Technology, Chitkara University, Rajpura, Punjab, 140 401, India
| | - Gwanggil Jeon
- Department of Embedded Systems Engineering, Incheon National University, Incheon, Korea.
- Energy Excellence & Smart City Lab, Incheon National University, Incheon, Korea.
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3
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Ali G, Anwar M, Nauman M, Faheem M, Rashid J. Lyme rashes disease classification using deep feature fusion technique. Skin Res Technol 2023; 29:e13519. [PMID: 38009027 PMCID: PMC10628356 DOI: 10.1111/srt.13519] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2023] [Accepted: 10/24/2023] [Indexed: 11/28/2023]
Abstract
Automatic classification of Lyme disease rashes on the skin helps clinicians and dermatologists' probe and investigate Lyme skin rashes effectively. This paper proposes a new in-depth features fusion system to classify Lyme disease rashes. The proposed method consists of two main steps. First, three different deep learning models, Densenet201, InceptionV3, and Exception, were trained independently to extract the deep features from the erythema migrans (EM) images. Second, a deep feature fusion mechanism (meta classifier) is developed to integrate the deep features before the final classification output layer. The meta classifier is a basic deep convolutional neural network trained on original images and features extracted from base level three deep learning models. In the feature fusion mechanism, the last three layers of base models are dropped out and connected to the meta classifier. The proposed deep feature fusion method significantly improved the classification process, where the classification accuracy was 98.97%, which is particularly impressive than the other state-of-the-art models.
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Affiliation(s)
- Ghulam Ali
- Department of Computer ScienceUniversity of OkaraOkaraPakistan
| | - Muhammad Anwar
- Department of Information SciencesDivision of Science and TechnologyUniversity of EducationLahorePakistan
| | - Muhammad Nauman
- Department of Computer ScienceUniversity of OkaraOkaraPakistan
| | - Muhammad Faheem
- School of Technology and InnovationsUniversity of VaasaVaasaFinland
| | - Javed Rashid
- Department of IT ServicesUniversity of OkaraOkaraPakistan
- MLC LabOkaraPakistan
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4
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Javaid Iqbal M, Waseem Iqbal M, Anwar M, Murad Khan M, Jabar Nazimi A, Nazir Ahmad M. Brain Tumor Segmentation in Multimodal MRI Using U-Net Layered Structure. COMPUTERS, MATERIALS & CONTINUA 2023; 74:5267-5281. [DOI: 10.32604/cmc.2023.033024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/05/2022] [Accepted: 09/22/2022] [Indexed: 09/02/2023]
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Abstract
Information and communication technology (ICT) and World Wide Web (WWW) are increasingly being used in daily life and becoming important in community, business, personal performance, and improvement of livelihood. people with disabilities (PWDs) can easily perform many tasks using WWW which might be difficult or impossible for them. However, many websites applications such as e-learning, e-commerce, and e-government are not specifically designed keeping in view PWD users. Through the web accessibility guidelines, web developers can build a web program accessible to PWDs. In this paper, we have investigated the issues related to website design that make it unavailable for PWDs. Keeping in view these issues, we have built a framework to make the web easier for PWDs. In addition, these issues are assessed using the GTmetrix, Netcraft, and WAVE accessibility tools and the results are generated using Google Analytics. Based on these results, we have proposed a simplified web version to improve website access for people with disabilities. The proposed prototype is also implemented on a website called Easywebcare by incorporating our recommendations for resolving the investigated issues. Analytics shows that the proposed type surpasses all existing activities in improving website accessibility for people with disabilities.
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6
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Sadiq A, Anwar M, Butt RA, Masud F, Shahzad MK, Naseem S, Younas M. A review of phishing attacks and countermeasures for internet of things‐based smart business applications in industry 4.0. HUMAN BEHAVIOR AND EMERGING TECHNOLOGIES 2021. [DOI: 10.1002/hbe2.301] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Affiliation(s)
- Ashina Sadiq
- Department of Computer Science Lahore Leads University Lahore Pakistan
| | - Muhammad Anwar
- Department of Computer Science NFC Institute of Engineering and Fertilizer Research Faisalabad Pakistan
| | - Rizwan A. Butt
- Department of Electronics Engineering NED University of Engineering and Technology Karachi Pakistan
| | - Farhan Masud
- Department of Statistics & Computer Science, Faculty of Life Sciences Business Management University of Veterinary and Animal Sciences Lahore Pakistan
| | - Muhammad K. Shahzad
- Department of Computing National University of Sciences and Technology Islamabad Pakistan
| | - Shahid Naseem
- Department of Information Science University of Education Lahore Pakistan
| | - Muhammad Younas
- Department of Computer Science GC University Faisalabad Pakistan
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7
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Batista E, Moncusi MA, López-Aguilar P, Martínez-Ballesté A, Solanas A. Sensors for Context-Aware Smart Healthcare: A Security Perspective. SENSORS (BASEL, SWITZERLAND) 2021; 21:6886. [PMID: 34696099 PMCID: PMC8537585 DOI: 10.3390/s21206886] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/27/2021] [Revised: 10/12/2021] [Accepted: 10/14/2021] [Indexed: 12/24/2022]
Abstract
The advances in the miniaturisation of electronic devices and the deployment of cheaper and faster data networks have propelled environments augmented with contextual and real-time information, such as smart homes and smart cities. These context-aware environments have opened the door to numerous opportunities for providing added-value, accurate and personalised services to citizens. In particular, smart healthcare, regarded as the natural evolution of electronic health and mobile health, contributes to enhance medical services and people's welfare, while shortening waiting times and decreasing healthcare expenditure. However, the large number, variety and complexity of devices and systems involved in smart health systems involve a number of challenging considerations to be considered, particularly from security and privacy perspectives. To this aim, this article provides a thorough technical review on the deployment of secure smart health services, ranging from the very collection of sensors data (either related to the medical conditions of individuals or to their immediate context), the transmission of these data through wireless communication networks, to the final storage and analysis of such information in the appropriate health information systems. As a result, we provide practitioners with a comprehensive overview of the existing vulnerabilities and solutions in the technical side of smart healthcare.
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Affiliation(s)
- Edgar Batista
- Department of Computer Engineering and Mathematics, Universitat Rovira i Virgili, Av. Països Catalans 26, 43007 Tarragona, Spain; (E.B.); (M.A.M.); (A.M.-B.)
- SIMPPLE S.L., C. Joan Maragall 1A, 43003 Tarragona, Spain
| | - M. Angels Moncusi
- Department of Computer Engineering and Mathematics, Universitat Rovira i Virgili, Av. Països Catalans 26, 43007 Tarragona, Spain; (E.B.); (M.A.M.); (A.M.-B.)
| | - Pablo López-Aguilar
- Anti-Phishing Working Group EU, Av. Diagonal 621–629, 08028 Barcelona, Spain;
| | - Antoni Martínez-Ballesté
- Department of Computer Engineering and Mathematics, Universitat Rovira i Virgili, Av. Països Catalans 26, 43007 Tarragona, Spain; (E.B.); (M.A.M.); (A.M.-B.)
| | - Agusti Solanas
- Department of Computer Engineering and Mathematics, Universitat Rovira i Virgili, Av. Països Catalans 26, 43007 Tarragona, Spain; (E.B.); (M.A.M.); (A.M.-B.)
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EERP-DPM: Energy Efficient Routing Protocol Using Dual Prediction Model for Healthcare Using IoT. JOURNAL OF HEALTHCARE ENGINEERING 2021; 2021:9988038. [PMID: 34040708 PMCID: PMC8121590 DOI: 10.1155/2021/9988038] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/26/2021] [Accepted: 04/29/2021] [Indexed: 11/17/2022]
Abstract
Healthcare is one of the most promising domains for the application of Internet of Things- (IoT-) based technologies, where patients can use wearable or implanted medical sensors to measure medical parameters anywhere and anytime. The information collected by IoT devices can then be sent to the health care professionals, and physicians allow having a real-time access to patients' data. However, besides limited batteries lifetime and computational power, there is spatio-temporal correlation, where unnecessary transmission of these redundant data has a significant impact on reducing energy consumption and reducing battery lifetime. Thus, this paper aims to propose a routing protocol to enhance energy-efficiency, which in turn prolongs the sensor lifetime. The proposed work is based on Energy Efficient Routing Protocol using Dual Prediction Model (EERP-DPM) for Healthcare using IoT, where Dual-Prediction Mechanism is used to reduce data transmission between sensor nodes and medical server if predictions match the readings or if the data are considered critical if it goes beyond the upper/lower limits of defined thresholds. The proposed system was developed and tested using MATLAB software and a hardware platform called "MySignals HW V2." Both simulation and experimental results confirm that the proposed EERP-DPM protocol has been observed to be extremely successful compared to other existing routing protocols not only in terms of energy consumption and network lifetime but also in terms of guaranteeing reliability, throughput, and end-to-end delay.
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Multiconstraint-Aware Routing Mechanism for Wireless Body Sensor Networks. JOURNAL OF HEALTHCARE ENGINEERING 2021; 2021:5560809. [PMID: 33868621 PMCID: PMC8032516 DOI: 10.1155/2021/5560809] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/08/2021] [Revised: 03/01/2021] [Accepted: 03/21/2021] [Indexed: 11/18/2022]
Abstract
The merger of wireless sensor technologies, pervasive computing, and biomedical engineering has resulted in the emergence of wireless body sensor network (WBSN). WBSNs assist human beings in various monitoring applications such as health-care, entertainment, rehabilitation systems, and sports. Life-critical health-care applications of WBSNs consider both reliability and delay as major Quality of Service (QoS) parameters. In addition to the common limitations and challenges of wireless sensor networks (WSNs), WBSNs pose distinct constraints due to the behavior and chemistry of the human body. The biomedical sensor nodes (BMSNs) adopt multihop communication while reporting the heterogeneous natured physiological parameters to the nearby base station also called local coordinator. Routing in WBSNs becomes a challenging job due to the necessary QoS considerations, overheated in-body BMSNs, and high and dynamic path loss. To the best of our knowledge, none of the existing routing protocols integrate the aforementioned issues in their designs. In this research work, a multiconstraint-aware routing mechanism (modular-based) is proposed which considers the QoS parameters, dynamic and high path loss, and the overheated nodes issue. Two types of network frameworks, with and without relay/forwarder nodes, are being used. The data packets containing physiological parameters of the human body are categorized into delay-constrained, reliability-constrained, critical (both delay- and reliability-constrained), and nonconstrained data packets. NS-2 is being used to carry out the simulations of the proposed mechanism. The simulation results reveal that the proposed mechanism has improved the QoS-aware routing for WBSNs by adopting the proposed multiconstraint-aware strategy.
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10
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Deep learning-based ambient assisted living for self-management of cardiovascular conditions. Neural Comput Appl 2021. [DOI: 10.1007/s00521-020-05678-w] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
AbstractAccording to the World Health Organization, cardiovascular diseases contribute to 17.7 million deaths per year and are rising with a growing ageing population. In order to handle these challenges, the evolved countries are now evolving workable solutions based on new communication technologies such as ambient assisted living. In these solutions, the most well-known solutions are wearable devices for patient monitoring, telemedicine and mHealth systems. This systematic literature review presents the detailed literature on ambient assisted living solutions and helps to understand how ambient assisted living helps and motivates patients with cardiovascular diseases for self-management to reduce associated morbidity and mortalities. Preferred reporting items for systematic reviews and meta-analyses technique are used to answer the research questions. The paper is divided into four main themes, including self-monitoring wearable systems, ambient assisted living in aged populations, clinician management systems and deep learning-based systems for cardiovascular diagnosis. For each theme, a detailed investigation shows (1) how these new technologies are nowadays integrated into diagnostic systems and (2) how new technologies like IoT sensors, cloud models, machine and deep learning strategies can be used to improve the medical services. This study helps to identify the strengths and weaknesses of novel ambient assisted living environments for medical applications. Besides, this review assists in reducing the dependence on caregivers and the healthcare systems.
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11
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An accurate and dynamic predictive model for a smart M-Health system using machine learning. Inf Sci (N Y) 2020. [DOI: 10.1016/j.ins.2020.06.025] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
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12
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Secure and energy-efficient framework using Internet of Medical Things for e-healthcare. J Infect Public Health 2020; 13:1567-1575. [PMID: 32682657 PMCID: PMC7362861 DOI: 10.1016/j.jiph.2020.06.027] [Citation(s) in RCA: 33] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2020] [Revised: 06/20/2020] [Accepted: 06/25/2020] [Indexed: 11/20/2022] Open
Abstract
In various fields, the internet of things (IoT) gains a lot of popularity due to its autonomous sensors operations with the least cost. In medical and healthcare applications, the IoT devices develop an ecosystem to sense the medical conditions of the patients' such as blood pressure, oxygen level, heartbeat, temperature, etc. and take appropriate actions on an emergency basis. Using it, the healthcare-related data of patients is transmitted towards the remote users and medical centers for post-analysis. Different solutions have been proposed using Wireless Body Area Network (WBAN) to monitor the medical status of the patients based on low powered biosensor nodes, however, preventing increased energy consumption and communication costs are demanding and interesting problems. The issue of unbalanced energy consumption between biosensor nodes degrades the timely delivery of the patient's information to remote centers and gives a negative impact on the medical system. Moreover, the sensitive data of the patient is transmitting over the insecure Internet and prone to vulnerable security threats. Therefore, data privacy and integrity from malicious traffic are another challenging research issue for medical applications. This research article aims to a proposed secure and energy-efficient framework using Internet of Medical Things (IoMT) for e-healthcare (SEF-IoMT), which primary objective is to decrease the communication overhead and energy consumption between biosensors while transmitting the healthcare data on a convenient manner, and the other hand, it also secures the medical data of the patients against unauthentic and malicious nodes to improve the network privacy and integrity. The simulated results exhibit that the proposed framework improves the performance of medical systems for network throughput by 18%, packets loss rate by 44%, end-to-end delay by 26%, energy consumption by 29%, and link breaches by 48% than other states of the art solutions.
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An Energy Efficient Enhanced Dual-Fuzzy Logic Routing Protocol for Monitoring Activities of the Elderly Using Body Sensor Networks. ELECTRONICS 2020. [DOI: 10.3390/electronics9050723] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Abstract
Wireless body area networks (WBANs) are an important application in wireless sensor networks (WSNs). Specifically, in healthcare monitoring systems, it is important to screen the patient’s biometric signals. For example, the elderlies’ vital signs, such as ECG (Electrocardiogram), blood pressure, heart rate, and blood glucose, can be used as measures of their well-being and are all critically important for remote elderly care in tracking their physical and cognitive capabilities. Therefore, WBANs require higher energy efficiency and data transmission. This paper proposes a cluster-based routing protocol which is suitable for WBANs while analyzing energy efficiency issue in data transmission. Considering the importance of sensor nodes in a specific environment for improving the network’s lifetime, the protocol based on the LEACH (low energy adaptive clustering hierarchy) algorithm is proposed. Due to its avoidance of long-distance transmission, the clustering technique is an efficient algorithm for prolonging the lifetimes of sensor networks. Therefore, this paper suggests an enhanced LEACH-dual fuzzy logic (ELEACH-DFL) protocol based-on clustering for CH (cluster head) selection and cluster configuration in wireless sensor networks. The simulation and analysis results address that the enhanced algorithm reduces the energy consumption effectively and extends the lifespan of the entire network. For wired sensors, attaching sensors to the user may cause problems and inconvenience of mobility. This leads to the use of wireless sensors to proceed with body sensors, which should consider the problem of battery efficiency, which concerns the configuration of wireless sensors. The LEACH protocol is energy efficient until the first node dead is generated. However, there is a sharp drop in energy efficiency after that. The ELEACH-DFL protocol has the advantage of maintaining energy efficiency even after the first node dead is generated, with the utmost consideration being given to stability in consideration of cluster selection and cluster head selection. In a field of 50 × 50, the FND efficiency improvement rate of ELEACH-DFL versus LEACH protocol is approximately 32%. In addition, in a field of 50 × 150, the FND efficiency improvement rate of ELEACH-DFL versus LEACH protocol is approximately 159%.
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Faheem M, Butt RA, Raza B, Alquhayz H, Abbas MZ, Ngadi MA, Gungor VC. A Multiobjective, Lion Mating Optimization Inspired Routing Protocol for Wireless Body Area Sensor Network Based Healthcare Applications. SENSORS 2019; 19:s19235072. [PMID: 31757104 PMCID: PMC6928723 DOI: 10.3390/s19235072] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/28/2019] [Revised: 11/13/2019] [Accepted: 11/15/2019] [Indexed: 01/10/2023]
Abstract
The importance of body area sensor networks (BASNs) is increasing day by day because of their increasing use in Internet of things (IoT)-enabled healthcare application services. They help humans in improving their quality of life by continuously monitoring various vital signs through biosensors strategically placed on the human body. However, BASNs face serious challenges, in terms of the short life span of their batteries and unreliable data transmission, because of the highly unstable and unpredictable channel conditions of tiny biosensors located on the human body. These factors may result in poor data gathering quality in BASNs. Therefore, a more reliable data transmission mechanism is greatly needed in order to gather quality data in BASN-based healthcare applications. Therefore, this study proposes a novel, multiobjective, lion mating optimization inspired routing protocol, called self-organizing multiobjective routing protocol (SARP), for BASN-based IoT healthcare applications. The proposed routing scheme significantly reduces local search problems and finds the best dynamic cluster-based routing solutions between the source and destination in BASNs. Thus, it significantly improves the overall packet delivery rate, residual energy, and throughput with reduced latency and packet error rates in BASNs. Extensive simulation results validate the performance of our proposed SARP scheme against the existing routing protocols in terms of the packet delivery ratio, latency, packet error rate, throughput, and energy efficiency for BASN-based health monitoring applications.
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Affiliation(s)
- Muhammad Faheem
- Department of Computer Science, Universiti Teknologi Malaysia, Johor Bahru 81310, Malaysia
- Department of Computer Engineering, Abdullah Gul University, Kayseri 38080, Turkey;
- Correspondence: (M.F.); (M.A.N.)
| | - Rizwan Aslam Butt
- Department of Electronics Engineering, NED University of Engineering, Karachi 75270, Pakistan;
| | - Basit Raza
- Department of Computer Science, COMSATS University Islamabad (CUI), Islamabad 45550, Pakistan;
| | - Hani Alquhayz
- Department of Computer Science and Information, College of Science in Zulfi, Majmaah University, Al-Majmaah 11952, Saudi Arabia;
| | - Muhammad Zahid Abbas
- Department of Computer Science, COMSATS University, Vehari Campus 61100, Pakistan;
| | - Md Asri Ngadi
- Department of Computer Science, Universiti Teknologi Malaysia, Johor Bahru 81310, Malaysia
- Correspondence: (M.F.); (M.A.N.)
| | - Vehbi Cagri Gungor
- Department of Computer Engineering, Abdullah Gul University, Kayseri 38080, Turkey;
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An Energy-Efficient Routing Protocol for Reliable Data Transmission in Wireless Body Area Networks. SENSORS 2019; 19:s19194238. [PMID: 31569568 PMCID: PMC6806081 DOI: 10.3390/s19194238] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/30/2019] [Revised: 09/24/2019] [Accepted: 09/25/2019] [Indexed: 01/10/2023]
Abstract
Wireless body area networks will inevitably bring tremendous convenience to human society in future development, and also enable people to benefit from ubiquitous technological services. However, one of the reasons hindering development is the limited energy of the network nodes. Therefore, the energy consumption in the selection of the next hop must be minimized in multi-hop routing. To solve this problem, this paper proposes an energy efficient routing protocol for reliable data transmission in a wireless body area network. The protocol takes multiple parameters of the network node into account, such as residual energy, transmission efficiency, available bandwidth, and the number of hops to the sink. We construct the maximum benefit function to select the next hop node by normalizing the node parameters, and dynamically select the node with the largest function value as the next hop node. Based on the above work, the proposed method can achieve efficient multi-hop routing transmission of data and improve the reliability of network data transmission. Compared with the priority-based energy-efficient routing algorithm (PERA) and modified new-attempt routing protocol (NEW-ATTEMPT), the simulation results show that the proposed routing protocol uses the maximum benefit function to select the next hop node dynamically, which not only improves the reliability of data transmission, but also significantly improves the energy utilization efficiency of the node and prolongs the network lifetime.
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Batista D, Oliveira LB, Paulino N, Carvalho C, Oliveira JP, Farinhas J, Charas A, Dos Santos PM. Combined Organic Photovoltaic Cells and Ultra Low Power CMOS Circuit for Indoor Light Energy Harvesting. SENSORS 2019; 19:s19081803. [PMID: 30991740 PMCID: PMC6515093 DOI: 10.3390/s19081803] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/07/2019] [Revised: 03/29/2019] [Accepted: 04/03/2019] [Indexed: 11/16/2022]
Abstract
This paper describes an energy harvesting system composed of an organic photovoltaic cell (OPV) connected to a DC–DC converter, designed in a 130 nm Complementary Metal-Oxide-Semiconductor (CMOS) technology, with a quasi- maximum power point tracking (MPPT) algorithm to maximize the system efficiency, for indoor applications. OPVs are an emerging technology with potential for low cost indoor light energy harvesting. The OPV current-voltage curves (I-V) under an irradiance of solar simulator Oriel Sol 3A, at room temperature, are obtained and an accurate electrical model is derived. The energy harvesting system is subjected to four different indoor light sources: 35 W halogen, 3.5 W LED, 5 W LED, and 7 W LED, positioned at three different heights (0.45 m, 0.26 m, and 0.11 m), to evaluate the potential of the system for indoor applications. The measurements showed maximum efficiencies of 60% for 35 W halogen and 45% for 7 W LED at the highest distance (0.45 m) and between 60% (5 W LED) and 70% (35 W halogen), at the shorter distance (0.11 m). Under irradiation, the integrated CMOS circuit presented a maximum efficiency of 75.76%, which is, to the best of the authors’ knowledge, the best reported power management unit (PMU) energy system using organic photovoltaic cells.
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Affiliation(s)
- Duarte Batista
- CTS-UNINOVA, Instituto de Desenvolvimento de Novas Tecnologias, 2829-517 Caparica, Portugal.
- Department of Electrical Engineering, Faculty of Sciences and Technology (FCT), University Nova de Lisboa (UNL), Lisbon, Portugal.
- Instituto de Telecomunicações, Av. Rovisco Pais 1, 1049-001 Lisbon, Portugal.
| | - Luis Bica Oliveira
- CTS-UNINOVA, Instituto de Desenvolvimento de Novas Tecnologias, 2829-517 Caparica, Portugal.
- Department of Electrical Engineering, Faculty of Sciences and Technology (FCT), University Nova de Lisboa (UNL), Lisbon, Portugal.
| | - Nuno Paulino
- CTS-UNINOVA, Instituto de Desenvolvimento de Novas Tecnologias, 2829-517 Caparica, Portugal.
- Department of Electrical Engineering, Faculty of Sciences and Technology (FCT), University Nova de Lisboa (UNL), Lisbon, Portugal.
| | - Carlos Carvalho
- CTS-UNINOVA, Instituto de Desenvolvimento de Novas Tecnologias, 2829-517 Caparica, Portugal.
- ADEETC, Instituto Superior de Engenharia de Lisboa (IPL-ISEL), CEDET, 1959-007 Lisbon, Portugal.
| | - João P Oliveira
- CTS-UNINOVA, Instituto de Desenvolvimento de Novas Tecnologias, 2829-517 Caparica, Portugal.
- Department of Electrical Engineering, Faculty of Sciences and Technology (FCT), University Nova de Lisboa (UNL), Lisbon, Portugal.
| | - Joana Farinhas
- Instituto de Telecomunicações, Av. Rovisco Pais 1, 1049-001 Lisbon, Portugal.
| | - Ana Charas
- Instituto de Telecomunicações, Av. Rovisco Pais 1, 1049-001 Lisbon, Portugal.
| | - Pedro Mendonça Dos Santos
- Instituto de Telecomunicações, Av. Rovisco Pais 1, 1049-001 Lisbon, Portugal.
- Academia Militar (AM), Instituto Universitário Militar (IUM), DCEE, Campus da Amadora, 2720-113 Amadora, Portugal.
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17
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A Survey of Routing Protocols in WBAN for Healthcare Applications. SENSORS 2019; 19:s19071638. [PMID: 30959817 PMCID: PMC6479667 DOI: 10.3390/s19071638] [Citation(s) in RCA: 49] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/29/2019] [Revised: 03/22/2019] [Accepted: 04/03/2019] [Indexed: 11/17/2022]
Abstract
The emergence of wireless body area network (WBAN) technology has brought hope and dawn to solve the problems of population aging, various chronic diseases, and medical facility shortage. The increasing demand for real-time applications in such networks, stimulates many research activities. Designing such a scheme of critical events while preserving the energy efficiency is a challenging task, due to the dynamic of the network topology, severe constraints on the power supply, and the limited computation power. The design of routing protocols becomes an essential part of WBANs and plays an important role in the communication stacks and has a significant impact on the network performance. In this paper, we briefly introduce WBAN and focus on the analysis of the routing protocol, classify, and compare the advantages and disadvantages of various routing protocols. Lastly, we put forward some problems and suggestions, which provides ideas for the follow-up routing design.
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18
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Outage Performance Analysis and SWIPT Optimization in Energy-Harvesting Wireless Sensor Network Deploying NOMA. SENSORS 2019; 19:s19030613. [PMID: 30717155 PMCID: PMC6387152 DOI: 10.3390/s19030613] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/17/2018] [Revised: 01/16/2019] [Accepted: 01/28/2019] [Indexed: 11/23/2022]
Abstract
Thanks to the benefits of non-orthogonal multiple access (NOMA) in wireless communications, we evaluate a wireless sensor network deploying NOMA (WSN-NOMA), where the destination can receive two data symbols in a whole transmission process with two time slots. In this work, two relaying protocols, so-called time-switching-based relaying WSN-NOMA (TSR WSN-NOMA) and power-splitting-based relaying WSN-NOMA (PSR WSN-NOMA) are deployed to study energy-harvesting (EH). Regarding the system performance analysis, we obtain the closed-form expressions for the exact and approximate outage probability (OP) in both protocols, and the delay-limited throughput is also evaluated. We then compare the two protocols theoretically, and two optimization problems are formulated to reduce the impact of OP and optimize the data rate. Our numerical and simulation results are provided to prove the theoretical and analytical analysis. Thanks to these results, a great performance gain can be achieved for both TSR WSN-NOMA and PSR WSN-NOMA if optimal values of TS and PS ratios are found. In addition, the optimized TSR WSN-NOMA outperforms that of PSR WSN-NOMA in terms of OP.
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19
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Masud F, Abdullah AH, Altameem A, Abdul-Salaam G, Muchtar F. Traffic Class Prioritization-Based Slotted-CSMA/CA for IEEE 802.15.4 MAC in Intra-WBANs. SENSORS (BASEL, SWITZERLAND) 2019; 19:E466. [PMID: 30678121 PMCID: PMC6386877 DOI: 10.3390/s19030466] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/27/2018] [Revised: 01/17/2019] [Accepted: 01/18/2019] [Indexed: 11/16/2022]
Abstract
This paper proposes an improved Traffic Class Prioritization based Carrier Sense Multiple Access/Collision Avoidance (TCP-CSMA/CA) scheme for prioritized channel access to heterogenous-natured Bio-Medical Sensor Nodes (BMSNs) for IEEE 802.15.4 Medium Access Control (MAC) in intra-Wireless Body Area Networks (WBANs). The main advantage of the scheme is to provide prioritized channel access to heterogeneous-natured BMSNs of different traffic classes with reduced packet delivery delay, packet loss, and energy consumption, and improved throughput and packet delivery ratio (PDR). The prioritized channel access is achieved by assigning a distinct, minimized and prioritized backoff period range to each traffic class in every backoff during contention. In TCP-CSMA/CA, the BMSNs are distributed among four traffic classes based on the existing patient's data classification. The Backoff Exponent (BE) starts from 1 to remove the repetition of the backoff period range in the third, fourth, and fifth backoffs. Five moderately designed backoff period ranges are proposed to assign a distinct, minimized, and prioritized backoff period range to each traffic class in every backoff during contention. A comprehensive verification using NS-2 was carried out to determine the performance of the TCP-CSMA/CA in terms of packet delivery delay, throughput, PDR, packet loss ratio (PLR) and energy consumption. The results prove that the proposed TCP-CSMA/CA scheme performs better than the IEEE 802.15.4 based PLA-MAC, eMC-MAC, and PG-MAC as it achieves a 47% decrease in the packet delivery delay and a 63% increase in the PDR.
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Affiliation(s)
- Farhan Masud
- School of Computing, Faculty of Engineering, Universiti Teknologi Malaysia (UTM), Johor Bahru 81310, Malaysia.
- Department of Statistics & Computer Science, Faculty of Life Sciences Business Management, University of Veterinary and Animal Sciences, Lahore 54000, Pakistan.
| | - Abdul Hanan Abdullah
- School of Computing, Faculty of Engineering, Universiti Teknologi Malaysia (UTM), Johor Bahru 81310, Malaysia.
| | - Ayman Altameem
- College of Applied Studies and Community Services, King Saud University, Riyadh 11564, Saudi Arabia.
| | - Gaddafi Abdul-Salaam
- Department of Computer Science, Faculty of Physical and Computational Sciences, Kwame Nkrumah University of Science & Technology, Private Mail Bag, University Post Office, KNUST-Kumasi 00233, Ghana.
| | - Farkhana Muchtar
- School of Computing, Faculty of Engineering, Universiti Teknologi Malaysia (UTM), Johor Bahru 81310, Malaysia.
- School of Computer Sciences, Universiti Sains Malaysia, Gelugor, Pulau Pinang 11800, Malaysia.
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20
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Selem E, Fatehy M, Abd El-Kader SM, Nassar H. THE (Temperature Heterogeneity Energy) Aware Routing Protocol for IoT Health Application. IEEE ACCESS 2019; 7:108957-108968. [DOI: 10.1109/access.2019.2931868] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/01/2023]
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21
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Towards The Internet-of-Smart-Clothing: A Review on IoT Wearables and Garments for Creating Intelligent Connected E-Textiles. ELECTRONICS 2018. [DOI: 10.3390/electronics7120405] [Citation(s) in RCA: 124] [Impact Index Per Article: 20.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
Technology has become ubiquitous, it is all around us and is becoming part of us. Together with the rise of the Internet-of-Things (IoT) paradigm and enabling technologies (e.g., Augmented Reality (AR), Cyber-Physical Systems, Artificial Intelligence (AI), blockchain or edge computing), smart wearables and IoT-based garments can potentially have a lot of influence by harmonizing functionality and the delight created by fashion. Thus, smart clothes look for a balance among fashion, engineering, interaction, user experience, cybersecurity, design and science to reinvent technologies that can anticipate needs and desires. Nowadays, the rapid convergence of textile and electronics is enabling the seamless and massive integration of sensors into textiles and the development of conductive yarn. The potential of smart fabrics, which can communicate with smartphones to process biometric information such as heart rate, temperature, breathing, stress, movement, acceleration, or even hormone levels, promises a new era for retail. This article reviews the main requirements for developing smart IoT-enabled garments and shows smart clothing potential impact on business models in the medium-term. Specifically, a global IoT architecture is proposed, the main types and components of smart IoT wearables and garments are presented, their main requirements are analyzed and some of the most recent smart clothing applications are studied. In this way, this article reviews the past and present of smart garments in order to provide guidelines for the future developers of a network where garments will be connected like other IoT objects: the Internet-of-Smart-Clothing.
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