Deep Neural Network for Localizing Gas Source Based on Gas Distribution Map
Journal
Lecture Notes in Electrical Engineering
ISSN
18761100
Date Issued
2022-01-01
Author(s)
Zaffry Hadi Mohd Juffry
Mao X.
Abdulnasser Nabil Abdullah
DOI
10.1007/978-981-16-8690-0_96
Handle (URI)
Abstract
The dynamic characteristic of gas dispersal in uncontrolled environment always leads to inaccurate gas source localization prediction from gas distribution map. Gas distribution map is a representation of the gas distribution over an environment which helps human to observe the concentration of harmful gases at a contaminated area. This paper proposes the utilization of Deep Neural Network (DNN) to predict the gas source location in a gas distribution map. DNN learns from the previous gas distribution map data and patterns to generate a model that is able predict location of gas source. The results indicate that DNN is able to accurately predict the location within the range of 0.8 to 2 m from the actual gas source. This finding shows that DNN has a high potential for utilization in gas source localization application.
Funding(s)
Kementerian Pendidikan Malaysia
Subjects
File(s)