PAFF: predictive analytics on forest fire using compressed sensing based localized Ad Hoc wireless sensor networks

Vikram, Raj; Sinha, Ditipriya; De, Debashis; Das, Ayan

doi:10.1007/s12652-020-02238-x

Cited by 10 publications

(1 citation statement)

References 43 publications

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“…The sensor nodes monitor the relevant information along the railway line and transmit it to the data monitoring center and the onboard aggregation node in the form of a wireless relay through the aggregation node located at the cluster head. After receiving the data information along the railway line, the safety monitoring center uses data mining algorithms to analyze and process and evaluate the safety level along the railway line and display the position of trains before and after and provide corresponding disaster warnings and other information [15]. Wireless sensor networks have become an important part of the next generation of the Internet.…”

Section: Passive Wireless Sensor Network Detection Networkmentioning

confidence: 99%

Passive Wireless Sensor Network‐Based In‐Transit Health Status Monitoring for Railway Transportation

Wei¹,

Song

2021

Journal of Sensors

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In this paper, passive wireless sensor network technology is used to conduct in-depth research and analysis on the monitoring of the in-transit health status of railway transportation. Safety detection sensors, train communication networks, and other onboard devices organically constitute a train sensor network with comprehensive state sensing, information aggregation, and business collaboration. First, this paper analyzes the three-layer architecture of the sensing layer, network layer, and application layer of the train operation status safety detection sensor network. Based on analyzing the feasibility of Ethernet application in an onboard communication network, ring, multiring, and ladder-type sensor network structure schemes are designed. Next, the real-time performance and reliability of various sensor network structures are analyzed. First, the characteristics of bandwidth demand, priority, and importance of information transmission of each monitoring object are analyzed; then, the system utility function is established according to the bandwidth usage efficiency and communication demand of information transmission of each monitoring object; finally, the bandwidth allocation optimization model is solved by using a particle swarm optimization algorithm, and the remaining bandwidth resources are dynamically rationed on demand while ensuring the complete transmission of basic information of each monitoring object. Rail transit technology has profoundly affected and changed the travel and lifestyle of residents in the new era and will provide strong infrastructure support for the smooth advancement of new urbanization construction and development strategies. The remaining bandwidth resources are dynamically allocated on the premise of ensuring the complete transmission of basic information of each monitoring object. In summary, this paper presents a complete study on the optimal allocation of resources for wireless sensor networks dedicated to rail transit condition monitoring, starting from the perspectives of routing protocol optimization, data fusion rate optimization, and bandwidth dynamic allocation optimization to achieve the efficient use of limited resources. The achieved research results enrich the research content in the field of wireless monitoring of rail transit system conditions at home and abroad in a certain sense and will also provide theoretical and empirical support for practical practitioners, managers, and scholars of service condition monitoring of rail transit systems.

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Section: Passive Wireless Sensor Network Detection Networkmentioning

confidence: 99%