A military surveillance system based on wireless sensor networks with extended coverage life

Mahamuni, Chaitanya Vijaykumar

doi:10.1109/icgtspicc.2016.7955331

Cited by 42 publications

(13 citation statements)

References 5 publications

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“…A wireless sensor network (WSN) is composed of a large number of sensor nodes that cover an even larger set of application areas [ 28 ], such as, military and surveillance [ 29 , 30 , 31 ], environment [ 3 , 32 , 33 ], health [ 34 , 35 , 36 ], home and building monitoring [ 37 , 38 , 39 ]. On the network, sensor nodes send information at regular time intervals from inside enclosures to be monitored, and ensure that the nodes in the network operate faultlessly.…”

Section: Development Of the Temperature Estimation And Sensor Failmentioning

confidence: 99%

An Intelligent Failure Detection on a Wireless Sensor Network for Indoor Climate Conditions

Gutiérrez

Ponce

2019

Sensors

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Wireless sensor networks (WSN) involve large number of sensor nodes distributed at diverse locations. The collected data are prone to be inaccurate and faulty due to internal or external influences, such as, environmental interference or sensor aging. Intelligent failure detection is necessary for the effective functioning of the sensor network. In this paper, we propose a supervised learning method that is named artificial hydrocarbon networks (AHN), to predict temperature in a remote location and detect failures in sensors. It allows predicting the temperature and detecting failure in sensor node of remote locations using information from a web service comparing it with field temperature sensors. For experimentation, we implemented a small WSN to test our sensor in order to measure failure detection, identification and accommodation proposal. In our experiments, 94.18% of the testing data were recovered and accommodated allowing of validation our proposed approach that is based on AHN, which detects, identify and accommodate sensor failures accurately.

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Section: Development Of the Temperature Estimation And Sensor Failmentioning

confidence: 99%

An Intelligent Failure Detection on a Wireless Sensor Network for Indoor Climate Conditions

Gutiérrez

Ponce

2019

Sensors

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“…However, wireless sensor nodes often use a limited energy source like a battery (rechargeable and non-rechargeable) and thus leading to the need to save energy and prolong the life of the wireless sensor network. Therefore, one of the challenging sensor network performance issues is related to energy-saving operating mechanisms [1][2][3][4].…”

Section: Introduction *mentioning

confidence: 99%

Untitled

2021

JST: SSAD

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Wireless sensor networks (WSN) play an important role in IoT (Internet of Things) as an interconnecting infrastructure. Working with a limited energy source, the vital challenge for WSN is to prolong the network lifetime as an important performance metric. Furthermore, the limitations of regular transmission technologies create localized network areas of a multi-hop fashion form that adds more constraints to enhance the network performance. Hence, the clustering strategies initially have solved these problems and received the attention of many studies, an approach using unequal clustering strategy has yielded some positive results since consumed energy gaps are avoided in regions near base stations. However, the routing strategy among cluster heads in multi-hop wireless networks is still a big challenge because of its inefficiency in energy consumption aspects. Therefore, in this paper, we propose a novel method that combining an unequal clustering problem and a simple multi-hop routing to prolong network life. The numerical results show that the proposed solution is more effective than other models in recent studies

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“…In recent decades, the research on wireless sensor networks (WSNs) has been a hotspot for numerous applications, such as, environment monitoring [ 1 ], smart cities [ 2 , 3 ], military monitoring [ 4 ], maritime resource gathering [ 5 ] and health-care surveillance [ 6 ].…”

Section: Introductionmentioning

confidence: 99%

Two-Tier PSO Based Data Routing Employing Bayesian Compressive Sensing in Underwater Sensor Networks

Chen

Xiong

Chu

2020

Sensors

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Underwater acoustic sensor networks play an important role in assisting humans to explore information under the sea. In this work, we consider the combination of sensor selection and data routing in three dimensional underwater wireless sensor networks based on Bayesian compressive sensing and particle swarm optimization. The algorithm we proposed is a two-tier PSO approach. In the first tier, a PSO-based clustering protocol is proposed to synthetically consider the energy consumption and uniformity of cluster head distribution. Then in the second tier, a PSO-based routing protocol is proposed to implement inner-cluster one-hop routing and outer-cluster multi-hop routing. The nodes selected to constitute i-th effective routing path decide which positions in the i-th row of the measurement matrix are nonzero. As a result, in this tier the protocol comprehensively considers energy efficiency, network balance and data recovery quality. The Bayesian Cramér-Rao Bound (BCRB) in such a case is analyzed and added in the fitness function to monitor the mean square error of the reconstructed signal. The experimental results validate that our algorithm maintains a longer life time and postpones the appearance of the first dead node while keeps the reconstruction error lower compared with the cutting-edge algorithms which are also based on distributed multi-hop compressive sensing approaches.

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A military surveillance system based on wireless sensor networks with extended coverage life

Cited by 42 publications

References 5 publications

An Intelligent Failure Detection on a Wireless Sensor Network for Indoor Climate Conditions

An Intelligent Failure Detection on a Wireless Sensor Network for Indoor Climate Conditions

Untitled

Two-Tier PSO Based Data Routing Employing Bayesian Compressive Sensing in Underwater Sensor Networks

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