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Chemical Sensor Systems and Associated Algorithms for Fire Detection: A Review.

Jordi Fonollosa1,2,3, Ana Solórzano4,5, Santiago Marco6,7

  • 1Department of Electronic and Biomedical Engineering, Universitat de Barcelona, 08028 Barcelona, Spain. jordi.fonollosa.m@upc.edu.

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Gas chemical sensing offers faster indoor fire detection by identifying toxic volatiles before smoke appears. Advanced data processing is crucial for reliable gas-based fire detection systems, enhancing safety.

Keywords:
carbon monoxidefire detectiongas sensorhydrogen cyanidemachine learningpattern recognitionsensor fusionsmokestandard test firestoxicantstransducers

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Area of Science:

  • Fire Safety Engineering
  • Chemical Sensing Technology
  • Toxicology

Background:

  • Indoor fire detection traditionally relies on smoke sensors, but chemical volatiles often precede smoke.
  • Gas-based detection, particularly using carbon monoxide sensors, offers potential for earlier fire alarms and reduced casualties from toxic emissions.
  • Existing gas sensors can react to non-combustion volatiles, necessitating sophisticated processing for accuracy.

Purpose of the Study:

  • To survey toxic emissions from fires and established fire detection standards.
  • To review the current state of chemical sensor systems and signal processing for fire detection.
  • To examine validation protocols and their impact on reported performance metrics.

Main Methods:

  • Literature review of toxic fire emissions and detection standards.
  • Survey of chemical sensor technologies and signal/data processing algorithms for fire detection.
  • Analysis of experimental protocols for validating gas-based fire detection systems.

Main Results:

  • Chemical sensing can detect fire volatiles before smoke, enabling faster alarms and improved safety.
  • Multivariate data processing techniques are essential to distinguish fires from nuisance sources and prevent false alarms.
  • The complexity of testing significantly influences the reported sensitivity and specificity of gas-based detectors.

Conclusions:

  • Gas-based fire detection shows promise for enhanced safety and faster response times.
  • Further research and extensive testing across diverse fire and nuisance scenarios are needed for market adoption.
  • Exploiting dynamic sensor features and multivariate models that leverage sensor correlations is imperative for effective gas-based fire detection.