Wireless sensor network for telemonitoring and home support for elderly people with chronic diseases

Weitz, Darío; Lianza, Franco; Maria, Denis; Schmidt, Nicole; Nant, Juan Pablo

doi:10.15208/ati.2017.01

Cited by 2 publications

(1 citation statement)

References 6 publications

(6 reference statements)

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“…In health monitoring and healthcare system, different applications need a careful designing and deploying of WSNs to improve and expand the quality of care [ 54 ]. Deploying WSNs for telemonitoring [ 55 ] in smart cities is one of these applications. In telemonitoring, WSNs should be deployed to connect the hospitals, medical centers, and care institutions by considering city coverage, connectivity, and reducing energy consumption so that the health medical services are immediately available throughout the city.…”

Section: Literature Reviewmentioning

confidence: 99%

Performance Analysis of IoT-Based Health and Environment WSN Deployment

Shakeri

Sadeghi‐Niaraki

Choi

et al. 2020

Sensors

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With the development of Internet of Things (IoT) applications, applying the potential and benefits of IoT technology in the health and environment services is increasing to improve the service quality using sensors and devices. This paper aims to apply GIS-based optimization algorithms for optimizing IoT-based network deployment through the use of wireless sensor networks (WSNs) and smart connected sensors for environmental and health applications. First, the WSN deployment research studies in health and environment applications are reviewed including fire monitoring, precise agriculture, telemonitoring, smart home, and hospital. Second, the WSN deployment process is modeled to optimize two conflict objectives, coverage and lifetime, by applying Minimum Spanning Tree (MST) routing protocol with minimum total network lengths. Third, the performance of the Bees Algorithm (BA) and Particle Swarm Optimization (PSO) algorithms are compared for the evaluation of GIS-based WSN deployment in health and environment applications. The algorithms were compared using convergence rate, constancy repeatability, and modeling complexity criteria. The results showed that the PSO algorithm converged to higher values of objective functions gradually while BA found better fitness values and was faster in the first iterations. The levels of stability and repeatability were high with 0.0150 of standard deviation for PSO and 0.0375 for BA. The PSO also had lower complexity than BA. Therefore, the PSO algorithm obtained better performance for IoT-based sensor network deployment.

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Section: Literature Reviewmentioning

confidence: 99%

Performance Analysis of IoT-Based Health and Environment WSN Deployment

Shakeri

Sadeghi‐Niaraki

Choi

et al. 2020

Sensors

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Sigma Routing Metric for RPL Protocol

Sanmartin

Rojas

Fernández

et al. 2018

Sensors

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This paper presents the adaptation of a specific metric for the RPL protocol in the objective function MRHOF. Among the functions standardized by IETF, we find OF0, which is based on the minimum hop count, as well as MRHOF, which is based on the Expected Transmission Count (ETX). However, when the network becomes denser or the number of nodes increases, both OF0 and MRHOF introduce long hops, which can generate a bottleneck that restricts the network. The adaptation is proposed to optimize both OFs through a new routing metric. To solve the above problem, the metrics of the minimum number of hops and the ETX are combined by designing a new routing metric called SIGMA-ETX, in which the best route is calculated using the standard deviation of ETX values between each node, as opposed to working with the ETX average along the route. This method ensures a better routing performance in dense sensor networks. The simulations are done through the Cooja simulator, based on the Contiki operating system. The simulations showed that the proposed optimization outperforms at a high margin in both OF0 and MRHOF, in terms of network latency, packet delivery ratio, lifetime, and power consumption.

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Wireless sensor network for telemonitoring and home support for elderly people with chronic diseases

Cited by 2 publications

References 6 publications

Performance Analysis of IoT-Based Health and Environment WSN Deployment

Performance Analysis of IoT-Based Health and Environment WSN Deployment

Sigma Routing Metric for RPL Protocol

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