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Evaluation of Knowledge Gaps in Mathematical Applications of Thermal Image Processing Techniques for Fire Prevention

Authors:

Sonali Agarwal,

G. N. PandeyAuthors Info & Claims

ACM Computing Surveys (CSUR), Volume 50, Issue 1

Article No.: 4, Pages 1 - 43

https://doi.org/10.1145/3009967

Published: 06 March 2017 Publication History

Abstract

In this article, we present literature reviews on fire prevention methods, especially in mining industries, using thermal image processing techniques. Fire protection systems are crucial because of the increased loss of human lives due to coal fires and fatal explosions in coal mines across the world in the past few decades. And with the growth in the demand for energy and the mining of coal expected up to the year 2050, determining conditions leading up to a breakout of fire is paramount. To detect uncertain fire breakout conditions, thermal imaging is considered the most significant among several early warning methods to recognize spontaneous combustion of coal piles (e.g., temperature recordings by sensors, compaction testing of ore seam, gas tests). The evolution of thermographic imaging applied in various industrial sectors (e.g., coal furnaces, oil tankers, building inspections, security) with numerous applications of mathematical models will be presented in the light of safety dimensions in the mining industry. The missing links or unattended areas of mathematics in the application of thermal image processing in mining, especially in the coal industry, will be evolved as the gap in knowledge suggested in our concluding statements.

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Cited By

Abu Dabous SShikhli AShareef SMushtaha EObaideen KAlsyouf I(2024)Fire prevention and mitigation technologies in high-rise buildings: A bibliometric analysis from 2010 to 2023Ain Shams Engineering Journal10.1016/j.asej.2024.10301015:11(103010)Online publication date: Nov-2024
https://doi.org/10.1016/j.asej.2024.103010
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https://doi.org/10.1007/s11042-022-13248-6
Zhou WLiu HLou JChen X(2022)Locality sensitive hashing with bit selectionApplied Intelligence10.1007/s10489-022-03546-952:13(14724-14738)Online publication date: 31-May-2022
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Index Terms

Evaluation of Knowledge Gaps in Mathematical Applications of Thermal Image Processing Techniques for Fire Prevention
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision problems
        Image segmentation

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Published In

cover image ACM Computing Surveys

ACM Computing Surveys Volume 50, Issue 1

January 2018

588 pages

ISSN:0360-0300

EISSN:1557-7341

DOI:10.1145/3058791

Editor:
Sartaj Sahni
Department of Computer and Information Science and Engineering / University of Florida / Gainesville, FL 32611

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Copyright © 2017 ACM.

Publication rights licensed to ACM. ACM acknowledges that this contribution was authored or co-authored by an employee, contractor or affiliate of a national government. As such, the Government retains a nonexclusive, royalty-free right to publish or reproduce this article, or to allow others to do so, for Government purposes only.

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New York, NY, United States

Publication History

Published: 06 March 2017

Accepted: 01 October 2016

Revised: 01 June 2016

Received: 01 January 2016

Published in CSUR Volume 50, Issue 1

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Cited By

Abu Dabous SShikhli AShareef SMushtaha EObaideen KAlsyouf I(2024)Fire prevention and mitigation technologies in high-rise buildings: A bibliometric analysis from 2010 to 2023Ain Shams Engineering Journal10.1016/j.asej.2024.10301015:11(103010)Online publication date: Nov-2024
https://doi.org/10.1016/j.asej.2024.103010
Rusia MSingh D(2022)A comprehensive survey on techniques to handle face identity threats: challenges and opportunitiesMultimedia Tools and Applications10.1007/s11042-022-13248-6Online publication date: 10-Jun-2022
https://doi.org/10.1007/s11042-022-13248-6
Zhou WLiu HLou JChen X(2022)Locality sensitive hashing with bit selectionApplied Intelligence10.1007/s10489-022-03546-952:13(14724-14738)Online publication date: 31-May-2022
https://doi.org/10.1007/s10489-022-03546-9
Haase JThim CBender B(2022)Expanding Modeling Notations: Requirements for Creative Process ModelingBusiness Process Management Workshops10.1007/978-3-030-94343-1_15(197-208)Online publication date: 23-Jan-2022
https://doi.org/10.1007/978-3-030-94343-1_15
Ibsen MRathgeb CFischer DDrozdowski PBusch C(2022)Digital Face Manipulation in Biometric SystemsHandbook of Digital Face Manipulation and Detection10.1007/978-3-030-87664-7_2(27-43)Online publication date: 31-Jan-2022
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Singh JRamachandra RBusch C(2021)Hierarchical Interpolation of Imagenet Features for Cross-Dataset Presentation Attack DetectionIntelligent Technologies and Applications10.1007/978-3-030-71711-7_17(203-214)Online publication date: 15-Mar-2021
https://doi.org/10.1007/978-3-030-71711-7_17

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