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

Fonollosa, Jordi; Solórzano, Ana; Marco, S.

doi:10.3390/s18020553

Cited by 117 publications

(68 citation statements)

References 62 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Moreover, indoor fire detection using gas chemical sensing provides faster fire alarm responses than conventional smoke-based fire detectors. Gas-based fire detection could provide an additional level of safety to building occupants in the event of fire [27]. But, these detectors rely heavily on one or two of the three fire signatures, which are inadequate for effective fire detection and firefighting.…”

Section: Literature Reviewmentioning

confidence: 99%

Hardware Module Design and Software Implementation of Multisensor Fire Detection and Notification System Using Fuzzy Logic and Convolutional Neural Networks (CNNs)

Sowah

Apeadu

Gatsi

et al. 2020

Journal of Engineering

View full text Add to dashboard Cite

This paper presents the design and development of a fuzzy logic-based multisensor fire detection and a web-based notification system with trained convolutional neural networks for both proximity and wide-area fire detection. Until recently, most consumer-grade fire detection systems relied solely on smoke detectors. These offer limited protection due to the type of fire present and the detection technology at use. To solve this problem, we present a multisensor data fusion with convolutional neural network (CNN) fire detection and notification technology. Convolutional Neural Networks are mainstream methods of deep learning due to their ability to perform feature extraction and classification in the same architecture. The system is designed to enable early detection of fire in residential, commercial, and industrial environments by using multiple fire signatures such as flames, smoke, and heat. The incorporation of the convolutional neural networks enables broader coverage of the area of interest, using visuals from surveillance cameras. With access granted to the web-based system, the fire and rescue crew gets notified in real-time with location information. The efficiency of the fire detection and notification system employed by standard fire detectors and the multisensor remote-based notification approach adopted in this paper showed significant improvements with timely fire detection, alerting, and response time for firefighting. The final experimental and performance evaluation results showed that the accuracy rate of CNN was 94% and that of the fuzzy logic unit is 90%.

show abstract

Section: Literature Reviewmentioning

confidence: 99%

Hardware Module Design and Software Implementation of Multisensor Fire Detection and Notification System Using Fuzzy Logic and Convolutional Neural Networks (CNNs)

Sowah

Apeadu

Gatsi

et al. 2020

Journal of Engineering

View full text Add to dashboard Cite

show abstract

“…A key to successful fire prevention and controlling is the accurate detection of fire characteristics as early as possible. The fire characteristics can vary greatly for various types and at different stages of fires (Fonollosa et al, 2018). So far numerous fire detectors based on the detection of gas, smoke, temperature, flame, etc., have been developed (Han and Lee, 2009;Verstockt et al, 2010).…”

Section: Introductionmentioning

confidence: 99%

“…So far numerous fire detectors based on the detection of gas, smoke, temperature, flame, etc., have been developed (Han and Lee, 2009;Verstockt et al, 2010). Gases or chemical vapors due to pyrolysis or smoldering of the combustible materials are usually emitted before the other fire characteristics become evident, such as smoke and temperature change, and could thus be used as a signature of fire (Fonollosa et al, 2018;Vincent et al, 2019). For many conventional fires, CO has been recognized as the signature gas, which has led to successful application of CO gas sensors in commercial fire detectors.…”

Section: Introductionmentioning

confidence: 99%

Detection of Semi-volatile Plasticizers as a Signature of Early Electrical Fire

Jia

Chen

et al. 2019

Front. Mater.

View full text Add to dashboard Cite

Detection of characteristic species released from overheated PVC cables may enable early warning of electrical fire. This work identified the major volatile species for overheated PVC cables, and verified their potential as fire signatures with metal oxide gas sensors. Semi-volatile Dioctyl phthalate (DOP) and 2-Ethylhexanol (2-EH) were found to be ubiquitously present in the cable vapors as major species. Detection of these species and the vapors of overheated cables was accomplished with a metal oxide gas sensor. The response of the gas sensor to the cable vapors resulted mainly from DOP and 2-EH, demonstrating them as effective signature gases for overheated PVC cables. A gas sensor based on SnO 2 nanofibers was prepared with greatly enhanced response to the signature gases. Large-scale simulation tests showed that the nanofiber gas sensor could effectively detect the cable overheating at an early stage.

show abstract

“…During the ignition and development phases of a fire, besides examining the production of smoke and toxic gases, we must analyze the increasing temperature over time (to check if the structures are able to resist the thermal stresses) [1,2]. Most victims die of asphyxiation and intoxication due to a high concentration of products of the combustion (CO, CO 2 , HCN, Sox, NOx) [3]. Those gases, at high temperatures, can cause: burns, eye irritation and breathing problems, provoking death even if the subject was not exposed directly to the flames [4,5].…”

Section: Introductionmentioning

confidence: 99%

Fire Temperature Based on the Time and Resistance of Buildings—Predicting the Adoption of Fire Safety Measures

Santarpia

Bologna

Ciancio

et al. 2019

Fire

View full text Add to dashboard Cite

During a fire in enclosed spaces, having structures with a good level of resistance is very important. The post flashover fire time interval, during which rescue squads operate, is important to verify if the structure can still resist fire for an acceptable time interval. This can be determined through the REI value. Hence, the way the fire develops must be examined together with the trend of the temperature that might guarantee that the structure will resist the heat flux released during the combustion. This article examines and compares, through a case study, the most important methods for analysis of the fire risk: the prescriptive approach and the simplified performance-based approach. The performance-based method (more suitable for the actual planning demand with respect to the more cautious prescriptive approach) is affected by the parameters influencing its development. The goal of this article is to provide a graph (based on parameters like the type of building, opening factor “O” and fire load “q”) that might be used by designers and architects to carry out the planning phase and adopt fire prevention systems before dealing with the assessments required by the engineering field for the fire risk analysis.

show abstract

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

Cited by 117 publications

References 62 publications

Hardware Module Design and Software Implementation of Multisensor Fire Detection and Notification System Using Fuzzy Logic and Convolutional Neural Networks (CNNs)

Hardware Module Design and Software Implementation of Multisensor Fire Detection and Notification System Using Fuzzy Logic and Convolutional Neural Networks (CNNs)

Detection of Semi-volatile Plasticizers as a Signature of Early Electrical Fire

Fire Temperature Based on the Time and Resistance of Buildings—Predicting the Adoption of Fire Safety Measures

Contact Info

Product

Resources

About