A study on disaster detection and management using WSN in Himalayan region of Uttarakhand

Pant, Diwaker; Verma, Sandeep; Dhuliya, Piyush

doi:10.1109/icaccaf.2017.8344703

Cited by 42 publications

(13 citation statements)

References 12 publications

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“…Wireless sensor networks (WSNs) has been a revolutionary sensing technology that pacts with monitoring the target area for different attributes depending upon application 1 . WSN consists of various wireless sensor nodes, when deployed collects data, and finally, data are sent to sink for further operation 2 . The prominent concern while operating the sensor nodes is the limited battery resources, replacement of which is quixotic 3 .…”

Section: Introductionmentioning

confidence: 99%

A novel framework for energy‐efficient compressive data gathering in heterogeneous wireless sensor network

Manchanda

Sharma

2020

Int J Communication

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Summary Wireless sensor network (WSN) suffers from the energy‐limited sensor nodes which consume energy heavily depending upon the magnitude of data which is transmitted or received by the nodes in the network. In this paper, our primary aim is to reduce the quantity of data transmitted to the data‐collecting sink, which helps in the energy preservation and eventually leads to network longevity. To address this concern, in this paper, we propose a novel framework for energy‐efficient compressive data gathering (NFECG) for heterogeneous WSN. NFECG works in four following phases; in the first phase, the cluster head (CH) selection is performed by considering remaining energy, “distance within the nodes and the sink,” and node density; in second phase, sleep scheduling is done among the cluster member nodes; further, in third phase, the compression of the aggregated data is performed at the CH level, and equivalent compressed sparse signals are generated which are transmitted to sink. In the last phase, at the sink, decompression is applied to retrieve the original signals. The simulation of NFECG is performed using MATLAB under two cases of different network area and number of nodes. We examine its performance for various performance metrics and also inspect for its scalable characteristics. The results show that for one of the two cases, it improves stability period and network lifetime by 52.59% and 46.09%, respectively, as compared to energy‐adjusted high‐level data total tree (EHDT) protocol, and also for the other case of network configuration, it acquires supreme performance.

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Section: Introductionmentioning

confidence: 99%

A novel framework for energy‐efficient compressive data gathering in heterogeneous wireless sensor network

Manchanda

Sharma

2020

Int J Communication

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“…The hardware composition of SNs is integrated with the limited battery, computing unit (microcontroller along with memory), transceiver, and the sensing unit (sensors and transducer) 3 . The predominant role of WSN is in hostile applications where the energy resources are not replaceable and the survival period of SNs is highly constrained; consequently, it becomes the vital concern which needs to be extenuated 4 …”

Section: Introductionmentioning

confidence: 99%

A novel approach for particle swarm optimization‐based clustering with dual sink mobility in wireless sensor network

Kaur

Grewal

2020

Int J Communication

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SummaryThe proliferation in the sensing technology in wireless sensor network has left an everlasting impact to revolutionize every sector of human's lives. The limited battery of sensor nodes (SNs) has generated a tremendous challenge for the researchers to ameliorate the network's life span. To pacify this concern, in this paper, we have proposed a particle swarm optimization (PSO)‐based dual sink mobility (PSODSM) technique to reduce the energy expenditure of the SNs. PSODSM has the paramount focus on the cluster head (CH) selection based on integration of crucial factors: “ratio of remaining energy to the initial energy,” node degree, node centrality, separation factor between the SN and the sink, CH number, and energy consumption rate. As soon as the CHs are selected, two sinks placed opposite to each other are made to move towards the selected CHs for data collection. The most prominent fact is the movement of sinks which is done outside the periphery of the network to collect data rather than the reported conventional research works that employ sink mobility inside the network. Extensive simulations are performed to examine the empirical evaluation of PSODSM based on the benchmark of different performance metrics. The performance validation of PSODSM is done against the other meta‐heuristic algorithms, and findings show that the PSODSM outperforms the competitive algorithms and is also found to be scalable pertaining to real time implementation.

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“…In all, the steps involved are target detection and tracking, tracking information forwarding, and target location prediction. The resulting system providing an accurate location of the target (indoor and outdoor) opens up new applications for crisis and commercial services, for example, rescue operation, 16 forest fire monitoring, 17 location known vehicle, 18 shipment tracking, 19 navigation, 20,21 health monitoring, 22 home automation, 23,24 and so on. In the end, making daily life easier in terms of safety and efficiency.…”

Section: Introductionmentioning

confidence: 99%

Exploiting cooperative sensing for accurate target tracking in industrial Internet of things

Khan

Rahman

et al. 2019

International Journal of Distributed Sensor Networks

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Wireless sensor networks are a cornerstone of the Internet of things with many applications. An important aspect of such applications is target tracking using self-positioned known sensor nodes. Over the years, many schemes have been proposed to locate and track the target path. However, accuracy and reliable tracking remain an open area of research. In this article, we propose a dynamic cooperative multilateral sensing scheme for indoor industrial environments to improve target localization and tracking accuracy. The scheme is designed to select reliable nodes based on the distance between nodes within-cluster and to the target for reduced positioning error. Furthermore, a cluster node is dynamically selected based on distance from the base station. We simulate the proposed technique in scenarios with tracking at regular intervals and with the complete path. Furthermore, the performance of the scheme is also tested under different sensor coverage areas. The results show that the proposed scheme provides better target tracking with up to 19% higher accuracy in comparison to the traditional trilateration scheme.

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A study on disaster detection and management using WSN in Himalayan region of Uttarakhand

Cited by 42 publications

References 12 publications

A novel framework for energy‐efficient compressive data gathering in heterogeneous wireless sensor network

A novel framework for energy‐efficient compressive data gathering in heterogeneous wireless sensor network

A novel approach for particle swarm optimization‐based clustering with dual sink mobility in wireless sensor network

Exploiting cooperative sensing for accurate target tracking in industrial Internet of things

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