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 (CO ₂ ). System performances are evaluated in terms of the receiver operating characteristic (ROC) curve as well as average decision delay and communication cost.