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Time-Aware Distributed Sequential Detection of Gas Dispersion via Wireless Sensor Networks

Abstract

This work addresses the problem of detecting gas dispersions through concentration sensors with wireless transmission capabilities organized as a distributed Wireless Sensor Network (WSN). The concentration sensors in the WSN perform local sequential detection (SD) and transmit their individual decisions to the Fusion Center (FC) according to a transmission rule designed to meet the low-energy requirements of a wireless setup. The FC receives the transmissions sent by the sensors and makes a more reliable global decision by employing a SD algorithm. Two variants of the SD algorithm named Continuous Sampling Algorithm (CSA) and Decision-Triggered Sampling Algorithm (DTSA), each with its own transmission rule, are presented and compared against a fully-batch algorithm named Batch Sampling Algorithm (BSA). The CSA operates as a time-aware detector by incorporating the time of each transmission in the detection rule. The proposed framework encompasses the gas dispersion model into the FC’s decision rule and leverages real-time weather measurements. The case study involves an accidental dispersion of carbon dioxide (CO2). System performances are evaluated in terms of the receiver operating characteristic (ROC) curve as well as average decision delay and communication cost.
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Category

Academic article

Language

English

Author(s)

Affiliation

  • Norwegian University of Science and Technology
  • University of Naples 'Federico II'
  • University of South Florida
  • Columbia University in the City of New York
  • SINTEF Energy Research / Gassteknologi

Year

2023

Published in

IEEE Transactions on Signal and Information Processing over Networks

ISSN

2373-7778

Publisher

IEEE (Institute of Electrical and Electronics Engineers)

Volume

9

Page(s)

721 - 735

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