An Energy-Efficient Modified Metaheuristic Inspired Algorithm for Disaster Management System Using WSNs

Singh, Samayveer; Nandan, Aridaman Singh; Malik, Arun; Kumar, Neeraj; Barnawi, Ahmed

doi:10.1109/jsen.2021.3074497

Cited by 30 publications

(17 citation statements)

References 21 publications

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“…Papers [ 27 – 32 ] discuss the various methods of the CH election process like CHs that are selected based on the amount of residual energy present, distance, and node density. Once a set of CHs has been selected, a message is broadcast by the CHs to the sensor devices in order to initiate cluster formation.…”

Section: Literature Reviewmentioning

confidence: 99%

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An Optimized Artificial Intelligence System Using IoT Biosensors Networking for Healthcare Problems

Khan¹,

Singh

Singh³

et al. 2022

Computational Intelligence and Neuroscience

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In today’s environment, electronics technology is growing rapidly because of the availability of the numerous and latest devices which can be deployed for monitoring and controlling the various healthcare systems. Due to the limitations of such devices, there is a dire need to optimize the utilization of the devices. In healthcare systems, Internet of things (IoT) based biosensors networking has minimal energy during transmission and collecting data. This paper proposes an optimized artificial intelligence system using IoT biosensors networking for healthcare problems for efficient data collection from the deployed sensor nodes. Here, an optimized tunicate swarm algorithm is used for optimizing the route for data collection and transmission among the patient and doctor. The fitness function of the optimized tunicate swarm algorithm used the distance, proximity, residual, and average energy of nodes parameters. The proposed method is attributed to the optimal CH chosen under TSA operation having a lower energy consumption. The performance of the proposed method is compared to the existing methods in terms of various metrics like stability period, lifetime, throughput, and clusters per round.

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Section: Literature Reviewmentioning

confidence: 99%

“…Here, one and three levels of heterogeneity are considered for homogeneous and heterogeneous networks, respectively. One level of heterogeneity considers the only single type of node in terms of their battery power, i.e., n 1 nodes [ 27 , 41 ]. This network contains n nodes with E o initial energy nodes.…”

Section: System Modelmentioning

confidence: 99%

An Optimized Artificial Intelligence System Using IoT Biosensors Networking for Healthcare Problems

Khan¹,

Singh

Singh³

et al. 2022

Computational Intelligence and Neuroscience

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“…Having a few more nodes with extra power is helpful in such applications to extend the network's lifespan. Similarly, various clustering-oriented approaches for enhancing network efficiency, lifetime, and stability have been proposed by several academics [4] , [5] , [6] , [7] , [8] , [9] , [10] , [11] , [12] , [13] , [14] , [15] , [16] , [17] , [18] , [19] , [20] , [21] , [22] , [23] , [24] , [25] . The most important objective in these types of protocols is to choose the cluster head (CH) with precision.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Other researchers have also discussed various data collection techniques using IoT-based WSNs [23] , [24] , [25] . Singh et al.…”

Section: Literature Reviewmentioning

confidence: 99%

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A secure energy-efficient routing protocol for disease data transmission using IoMT

Singh

Nandan²,

Sikka³

et al. 2022

Computers and Electrical Engineering

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An IIoT based secure and sustainable smart supply chain system using sensor networks

Singh

Kumar

Verma

et al. 2022

Trans Emerging Tel Tech

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Industrial Internet of Things (IIoT) is a very effective and efficient way to track products during their production, packaging, storage, and shipments. It can also help in monitoring their real‐time conditions such as location, speed of moments, and temperature. Presently most of the supply chain management systems are not effective due to their inefficient tracking of real‐time shipments, long delays in shipments and lost identification on a real‐time basis, and uneconomical storage of goods. To solve these problems, an IoT‐based secure and sustainable smart supply chain system using sensor networks is proposed that provides real‐time shipment tracking, storage, delay, and lost identification. Threshold‐based weighted probability formula is devised by considering the average distance and node spacing of sensor nodes, total network energy, residual, and maximum energy parameters to alleviate the hot spot problem. Additionally, the communication signals are transmitted in compression form with end‐to‐end encryption that reduces the use of bandwidth by decreasing the signal size. The percentage increment in the stability and the network lifespan of the proposed method is 35.19% and 7.23% & 119.33% and 71.72% as compared to the T. Senthil et al method and S. Singh's method, respectively.

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An Energy-Efficient Modified Metaheuristic Inspired Algorithm for Disaster Management System Using WSNs

Cited by 30 publications

References 21 publications

An Optimized Artificial Intelligence System Using IoT Biosensors Networking for Healthcare Problems

An Optimized Artificial Intelligence System Using IoT Biosensors Networking for Healthcare Problems

A secure energy-efficient routing protocol for disease data transmission using IoMT

An IIoT based secure and sustainable smart supply chain system using sensor networks

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