An overview of Wireless Sensor Network and applications

Rajaravivarma, V.; Yang, Yi; Yang, Teng

doi:10.1109/ssst.2003.1194607

Cited by 92 publications

(35 citation statements)

References 4 publications

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“…On intensive study, it is found that, the WSN is significantly used for precision agriculture [7], wherein, the parameters of spatio-temporal variations should be essentially monitored. The WSN also proved its suitability for monitoring transportation, environmental monitoring, forecasting, pollution monitoring, security, disaster management etc [8]. Moreover, it is most suitable for monitoring of industrial parameters.…”

Section: Introductionmentioning

confidence: 99%

ARM Microcontroller Based Wireless Sensor Network to Monitor Environmental Parameters of Textile Industry

Chavan¹,

Tilekar²,

Deshmukh³

et al. 2017

IJARCSSE

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Section: Introductionmentioning

confidence: 99%

ARM Microcontroller Based Wireless Sensor Network to Monitor Environmental Parameters of Textile Industry

Chavan¹,

Tilekar²,

Deshmukh³

et al. 2017

IJARCSSE

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“…They are composed of limited-power sensors that have limited transmission range, processing and storage capabilities, called sensor nodes [7,8]. They typically depend on batteries for power and need to stay alive for the longest time possible to sense the environment and report data, especially if they are deployed in rough places where human intervention is risky.…”

Section: Introductionmentioning

confidence: 99%

MUCH: Multi-Criteria Cluster Head Delegation Based on Fuzzy Logic

Ghosn¹,

Ghaddar²

2017

International Journal of Advanced Research in Computer and Comm

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WSNs are composed of limited-power sensors. Replacing or recharging sensors, especially when deployed in places where human intervention is risky, is an important challenge. Therefore, and since communication is the major energy consuming operation [1], ensuring an energy efficient usage is a major concern. Clustering is one of the techniques used for this purpose [2]. It decreases the number of sensors which take part in transmission thereby assist in power consumption [3]. The sensors are organized into clusters. Each Cluster has a Cluster Head (CH) to which only other cluster members send data. CHs gather information and send it to a base station for processing. We propose an method for CH selection based on multiple criteria (distance to base station, distance to cluster members, energy cost and number of rounds) using fuzzy logic. Simulation results show that MUCH decreases the energy consumption comparing to LEACH thus increases the network lifetime.

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“…The coverage can be considered as a measure of the monitoring quality produced by a sensor network [4]. WSNs are usually dense and redundant (more than 20 nodes/m 3 [5]). So, the coverage of AI can be done, but it is not optimal if all nodes contribute for observing this AI.…”

Section: Introductionmentioning

confidence: 99%

Distributed Algorithm for Coverage and Connectivity in Wireless Sensor Networks

Khelil

Beghdad

2015

IFIP Advances in Information and Communication Technology

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ABSTRACT. Even if several algorithms were proposed in the literature to solve the coverage problem in Wireless Sensor Networks (WSNs), they still suffer from some weaknesses. This is the reason why we suggest in this paper, a distributed protocol, called Single Phase Multiple Initiator (SPMI). Its aim is to find Connect Cover Set (CCS) for assuring the coverage and connectivity in WSN. Our idea is based on determining a Connected Dominating Set (CDS) which has a minimum number of necessary and sufficient nodes to guarantee coverage of the area of interested (AI), when WSN model is considered as a graph. The suggested protocol only requires a single phase to construct a CDS in distributed manner without using sensors' location information. Simulation results show that SPMI assures better coverage and connectivity of AI by using fewer active nodes and by inducing very low message overhead, and low energy consumption, when compared with some existing protocols.

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An overview of Wireless Sensor Network and applications

Cited by 92 publications

References 4 publications

ARM Microcontroller Based Wireless Sensor Network to Monitor Environmental Parameters of Textile Industry

ARM Microcontroller Based Wireless Sensor Network to Monitor Environmental Parameters of Textile Industry

MUCH: Multi-Criteria Cluster Head Delegation Based on Fuzzy Logic

Distributed Algorithm for Coverage and Connectivity in Wireless Sensor Networks

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