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Sensors for Fire and Smoke Monitoring
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Sensors for Fire and Smoke Monitoring

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Physical Sensors".

Deadline for manuscript submissions: closed (15 April 2021) | Viewed by 91524

Printed Edition Available!
A printed edition of this Special Issue is available here.

Special Issue Editors

Prof. Dr. Robert S. Allison

E-Mail Website
Guest Editor
Electrical Engineering & Computer Science, York University, Toronto, ON M3J 1P3, Canada
Interests: applications of sensors and displays in aviation; human perception and performance; immersive virtual reality (VR) and augmented reality (AR) systems; stereoscopic displays and applications; cue conflict in synthetic displays
Dr. Joshua Johnston

E-Mail Website
Guest Editor
Canadian Forest Service, Sault Ste Marie, ON P6A 2E5, Canada
Interests: wildfire remote sensing; tactical mapping systems; computer vision and machine learning-based automation; thermal detector design and applications; combustion physics; fire behavior
Prof. Dr. Martin Wooster

E-Mail Website
Guest Editor
Earth Observation Science, ​​NERC National Center for Earth Observation & Department of Geography, King's College London, Strand, London WC2R 2LS, UK
Interests: local to global biomass burning quantification and impacts; active fire remote sensing; fire radiative power metrics; smoke emissions measurements; fire and air quality; in situ and UAV measurements
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

We wish to invite you to contribute to a Special Issue of Sensors on fire and smoke detection and monitoring. This issue will curate and collect the latest research on sensors and systems to detect and quantify wildland, structural, and industrial combustion and gaseous emissions for diverse applications. For example, the devastation from the recent wildfires in California, Australia, and elsewhere has captured the attention of the public and highlighted the need to detect and monitor wildfires to protect and preserve life and property. Similar public interest surrounds detecting and monitoring fire and smoke behavior for fire protection and suppression in residential and industrial settings or for the design and test of safer materials and structures. Recently advances in low resource detector technology and the rise in small satellite applications has seen a surge in innovative detector technologies and applications. We seek the latest and most innovative research in the field of sensing and measurement of flame, smoke, and combustion gases. Original research papers, theoretical papers, and critical reviews in all aspects of combustion and emissions sensing, pre- and post-fire assessment, and other aspects of fire monitoring are sought. Topics may include but are not limited to:

  • Sensing of heat and flame;
  • Measuring carbon and biomass combustion;
  • Assessing impacts of burning on climate change;
  • Optical and chemical sensors for smoke and gas detection;
  • Remote sensing of high temperature events;
  • Visible, hyperspectral and thermal imaging;
  • Satellite fire detection and monitoring platforms, detectors and systems;
  • Automated fire detection and autonomous sensors;
  • Artificial intelligence and machine learning for fire monitoring;
  • Sensors for analysis of smoke and combustion gases and byproducts;
  • Fuel and environmental sensing, fire prediction, and burn and severity assessment;
  • Hardened sensors for fire environments;
  • Wearable sensors for firefighters;
  • Sensors for structural fire engineering;
  • Sensors for firefighting robotics and uninhabited aerial vehicles.

Prof. Dr. Robert S. Allison
Dr. Joshua Johnston
Prof. Dr. Martin Wooster
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • wildfire
  • fire detection
  • fire monitoring
  • airborne sensors
  • combustion
  • smoke detection
  • heat detection
  • flame detection
  • satellite sensors

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Published Papers (11 papers)

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Editorial

Jump to: Research, Review

3 pages, 156 KiB  
Editorial
Sensors for Fire and Smoke Monitoring
by Robert S. Allison, Joshua M. Johnston and Martin J. Wooster
Sensors 2021, 21(16), 5402; https://doi.org/10.3390/s21165402 - 10 Aug 2021
Cited by 5 | Viewed by 3362
Abstract
Mastery of fire is intimately linked to advances in human civilization, culture and technology [...] Full article
(This article belongs to the Special Issue Sensors for Fire and Smoke Monitoring)

Research

Jump to: Editorial, Review

13 pages, 29030 KiB  
Article
A Bi-Spectral Microbolometer Sensor for Wildfire Measurement
by Denis Dufour, Loïc Le Noc, Bruno Tremblay, Mathieu N. Tremblay, Francis Généreux, Marc Terroux, Carl Vachon, Melanie J. Wheatley, Joshua M. Johnston, Mike Wotton and Patrice Topart
Sensors 2021, 21(11), 3690; https://doi.org/10.3390/s21113690 - 26 May 2021
Cited by 11 | Viewed by 4448
Abstract
This study describes the development of a prototype bi-spectral microbolometer sensor system designed explicitly for radiometric measurement and characterization of wildfire mid- and long-wave infrared radiances. The system is tested experimentally over moderate-scale experimental burns coincident with FLIR reference imagery. Statistical comparison of [...] Read more.
This study describes the development of a prototype bi-spectral microbolometer sensor system designed explicitly for radiometric measurement and characterization of wildfire mid- and long-wave infrared radiances. The system is tested experimentally over moderate-scale experimental burns coincident with FLIR reference imagery. Statistical comparison of the fire radiative power (FRP; W) retrievals suggest that this novel system is highly reliable for use in collecting radiometric measurements of biomass burning. As such, this study provides clear experimental evidence that mid-wave infrared microbolometers are capable of collecting FRP measurements. Furthermore, given the low resource nature of this detector type, it presents a suitable option for monitoring wildfire behaviour from low resource platforms such as unmanned aerial vehicles (UAVs) or nanosats. Full article
(This article belongs to the Special Issue Sensors for Fire and Smoke Monitoring)
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24 pages, 17105 KiB  
Article
Geocorrection of Airborne Mid-Wave Infrared Imagery for Mapping Wildfires without GPS or IMU
by Gabriela Ifimov, Tomas Naprstek, Joshua M. Johnston, Juan Pablo Arroyo-Mora, George Leblanc and Madeline D. Lee
Sensors 2021, 21(9), 3047; https://doi.org/10.3390/s21093047 - 27 Apr 2021
Cited by 3 | Viewed by 3105
Abstract
The increase in annual wildfires in many areas of the world has triggered international efforts to deploy sensors on airborne and space platforms to map these events and understand their behaviour. During the summer of 2017, an airborne flight campaign acquired mid-wave infrared [...] Read more.
The increase in annual wildfires in many areas of the world has triggered international efforts to deploy sensors on airborne and space platforms to map these events and understand their behaviour. During the summer of 2017, an airborne flight campaign acquired mid-wave infrared imagery over active wildfires in Northern Ontario, Canada. However, it suffered multiple position-based equipment issues, thus requiring a non-standard geocorrection methodology. This study presents the approach, which utilizes a two-step semi-automatic geocorrection process that outputs image mosaics from airborne infrared video input. The first step extracts individual video frames that are combined into orthoimages using an automatic image registration method. The second step involves the georeferencing of the imagery using pseudo-ground control points to a fixed coordinate systems. The output geocorrected datasets in units of radiance can then be used to derive fire products such as fire radiative power density (FRPD). Prior to the georeferencing process, the Root Mean Square Error (RMSE) associated with the imagery was greater than 200 m. After the georeferencing process was applied, an RMSE below 30 m was reported, and the computed FRPD estimations are within expected values across the literature. As such, this alternative geocorrection methodology successfully salvages an otherwise unusable dataset and can be adapted by other researchers that do not have access to accurate positional information for airborne infrared flight campaigns over wildfires. Full article
(This article belongs to the Special Issue Sensors for Fire and Smoke Monitoring)
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18 pages, 2556 KiB  
Article
The Wildland Fire Heat Budget—Using Bi-Directional Probes to Measure Sensible Heat Flux and Energy in Surface Fires
by Matthew B. Dickinson, Cyle E. Wold, Bret W. Butler, Robert L. Kremens, Daniel Jimenez, Paul Sopko and Joseph J. O’Brien
Sensors 2021, 21(6), 2135; https://doi.org/10.3390/s21062135 - 18 Mar 2021
Cited by 9 | Viewed by 3300
Abstract
Sensible energy is the primary mode of heat dissipation from combustion in wildland surface fires. However, despite its importance to fire dynamics, smoke transport, and in determining ecological effects, it is not routinely measured. McCaffrey and Heskestad (A robust bidirectional low-velocity probe for [...] Read more.
Sensible energy is the primary mode of heat dissipation from combustion in wildland surface fires. However, despite its importance to fire dynamics, smoke transport, and in determining ecological effects, it is not routinely measured. McCaffrey and Heskestad (A robust bidirectional low-velocity probe for flame and fire application. Combustion and Flame 26:125–127, 1976) describe measurements of flame velocity from a bi-directional probe which, when combined with gas temperature measurements, can be used to estimate sensible heat fluxes. In this first field application of bi-directional probes, we describe vertical and horizontal sensible heat fluxes during the RxCADRE experimental surface fires in longleaf pine savanna and open ranges at Eglin Air Force Base, Florida. Flame-front sensible energy is the time-integral of heat flux over a residence time, here defined by the rise in gas temperatures above ambient. Horizontal flow velocities and energies were larger than vertical velocities and energies. Sensible heat flux and energy measurements were coordinated with overhead radiometer measurements from which we estimated fire energy (total energy generated by combustion) under the assumption that 17% of fire energy is radiated. In approximation, horizontal, vertical, and resultant sensible energies averaged 75%, 54%, and 64%, respectively, of fire energy. While promising, measurement challenges remain, including obtaining accurate gas and velocity measurements and capturing three-dimensional flow in the field. Full article
(This article belongs to the Special Issue Sensors for Fire and Smoke Monitoring)
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25 pages, 7074 KiB  
Article
Top-Down Estimation of Particulate Matter Emissions from Extreme Tropical Peatland Fires Using Geostationary Satellite Fire Radiative Power Observations
by Daniel Fisher, Martin J. Wooster, Weidong Xu, Gareth Thomas and Puji Lestari
Sensors 2020, 20(24), 7075; https://doi.org/10.3390/s20247075 - 10 Dec 2020
Cited by 9 | Viewed by 5189
Abstract
Extreme fires in the peatlands of South East (SE) Asia are arguably the world’s greatest biomass burning events, resulting in some of the worst ambient air pollution ever recorded (PM10 > 3000 µg·m−3). The worst of these fires coincide with [...] Read more.
Extreme fires in the peatlands of South East (SE) Asia are arguably the world’s greatest biomass burning events, resulting in some of the worst ambient air pollution ever recorded (PM10 > 3000 µg·m−3). The worst of these fires coincide with El Niño related droughts, and include huge areas of smouldering combustion that can persist for months. However, areas of flaming surface vegetation combustion atop peat are also seen, and we show that the largest of these latter fires appear to be the most radiant and intensely smoke-emitting areas of combustion present in such extreme fire episodes. Fire emissions inventories and early warning of the air quality impacts of landscape fire are increasingly based on the fire radiative power (FRP) approach to fire emissions estimation, including for these SE Asia peatland fires. “Top-down” methods estimate total particulate matter emissions directly from FRP observations using so-called “smoke emission coefficients” [Ce; g·MJ−1], but currently no discrimination is made between fire types during such calculations. We show that for a subset of some of the most thermally radiant peatland fires seen during the 2015 El Niño, the most appropriate Ce is around a factor of three lower than currently assumed (~16.8 ± 1.6 g·MJ−1 vs. 52.4 g·MJ−1). Analysis indicates that this difference stems from these highly radiant fires containing areas of substantial flaming combustion, which changes the amount of particulate matter emitted per unit of observable fire radiative heat release in comparison to more smouldering dominated events. We also show that even a single one of these most radiant fires is responsible for almost 10% of the overall particulate matter released during the 2015 fire event, highlighting the importance of this fire type to overall emission totals. Discriminating these different fires types in ways demonstrated herein should thus ultimately improve the accuracy of SE Asian fire emissions estimates derived using the FRP approach, and the air quality modelling which they support. Full article
(This article belongs to the Special Issue Sensors for Fire and Smoke Monitoring)
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29 pages, 18575 KiB  
Article
Thermal Infrared Sensing for Near Real-Time Data-Driven Fire Detection and Monitoring Systems
by Maria João Sousa, Alexandra Moutinho and Miguel Almeida
Sensors 2020, 20(23), 6803; https://doi.org/10.3390/s20236803 - 28 Nov 2020
Cited by 40 | Viewed by 9997
Abstract
With the increasing interest in leveraging mobile robotics for fire detection and monitoring arises the need to design recognition technology systems for these extreme environments. This work focuses on evaluating the sensing capabilities and image processing pipeline of thermal imaging sensors for fire [...] Read more.
With the increasing interest in leveraging mobile robotics for fire detection and monitoring arises the need to design recognition technology systems for these extreme environments. This work focuses on evaluating the sensing capabilities and image processing pipeline of thermal imaging sensors for fire detection applications, paving the way for the development of autonomous systems for early warning and monitoring of fire events. The contributions of this work are threefold. First, we overview image processing algorithms used in thermal imaging regarding data compression and image enhancement. Second, we present a method for data-driven thermal imaging analysis designed for fire situation awareness in robotic perception. A study is undertaken to test the behavior of the thermal cameras in controlled fire scenarios, followed by an in-depth analysis of the experimental data, which reveals the inner workings of these sensors. Third, we discuss key takeaways for the integration of thermal cameras in robotic perception pipelines for autonomous unmanned aerial vehicle (UAV)-based fire surveillance. Full article
(This article belongs to the Special Issue Sensors for Fire and Smoke Monitoring)
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27 pages, 15885 KiB  
Article
A Fast Segmentation Method for Fire Forest Images Based on Multiscale Transform and PCA
by Lotfi Tlig, Moez Bouchouicha, Mohamed Tlig, Mounir Sayadi and Eric Moreau
Sensors 2020, 20(22), 6429; https://doi.org/10.3390/s20226429 - 10 Nov 2020
Cited by 10 | Viewed by 3657
Abstract
Forests provide various important things to human life. Fire is one of the main disasters in the world. Nowadays, the forest fire incidences endanger the ecosystem and destroy the native flora and fauna. This affects individual life, community and wildlife. Thus, it is [...] Read more.
Forests provide various important things to human life. Fire is one of the main disasters in the world. Nowadays, the forest fire incidences endanger the ecosystem and destroy the native flora and fauna. This affects individual life, community and wildlife. Thus, it is essential to monitor and protect the forests and their assets. Nowadays, image processing outputs a lot of required information and measures for the implementation of advanced forest fire-fighting strategies. This work addresses a new color image segmentation method based on principal component analysis (PCA) and Gabor filter responses. Our method introduces a new superpixels extraction strategy that takes full account of two objectives: regional consistency and robustness to added noises. The novel approach is tested on various color images. Extensive experiments show that our method obviously outperforms existing segmentation variants on real and synthetic images of fire forest scenes, and also achieves outstanding performance on other popular benchmarked images (e.g., BSDS, MRSC). The merits of our proposed approach are that it is not sensitive to added noises and that the segmentation performance is higher with images of nonhomogeneous regions. Full article
(This article belongs to the Special Issue Sensors for Fire and Smoke Monitoring)
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14 pages, 4929 KiB  
Article
Obscuration Threshold Database Construction of Smoke Detectors for Various Combustibles
by Hyo-Yeon Jang and Cheol-Hong Hwang
Sensors 2020, 20(21), 6272; https://doi.org/10.3390/s20216272 - 4 Nov 2020
Cited by 11 | Viewed by 6906
Abstract
The obscuration thresholds for various smoke detectors and combustibles, required as an input parameter in fire simulation, were measured to predict the accurate activation time of detectors. One ionization detector and nine photoelectric detectors were selected. A fire detector evaluator, which can uniformly [...] Read more.
The obscuration thresholds for various smoke detectors and combustibles, required as an input parameter in fire simulation, were measured to predict the accurate activation time of detectors. One ionization detector and nine photoelectric detectors were selected. A fire detector evaluator, which can uniformly control the velocity and smoke concentration, was utilized. Filter paper, liquid fuels, and polymer pellets were employed as smoke-generation combustibles. The nominal obscuration thresholds of the considered detectors were 15 %/m, but the ionization detectors activated at approximately 40 %/m and 16 %/m, respectively, on applying filter paper and kerosene. In contrast, the reverse obscuration thresholds were found quantitatively according to the combustibles in the photoelectric detector. This phenomenon was caused by differences in the color of the smoke particles according to the combustibles, which is explained by single-scattering albedo (ratio of light scattering to light extinction). The obscuration thresholds for liquid fuels (kerosene, heptane and toluene) as well as fire types of polymer plastic pellets were also measured for several photoelectric detectors. A database of obscuration thresholds was thereby established according to the detector and combustible types, and it is expected to provide useful information for predicting more accurate detector activation time and required safe egress time (REST). Full article
(This article belongs to the Special Issue Sensors for Fire and Smoke Monitoring)
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23 pages, 1610 KiB  
Article
Development of the User Requirements for the Canadian WildFireSat Satellite Mission
by Joshua M. Johnston, Natasha Jackson, Colin McFayden, Linh Ngo Phong, Brian Lawrence, Didier Davignon, Martin J. Wooster, Helena van Mierlo, Dan K. Thompson, Alan S. Cantin, Daniel Johnston, Lynn M. Johnston, Meghan Sloane, Rebecca Ramos and Tim J. Lynham
Sensors 2020, 20(18), 5081; https://doi.org/10.3390/s20185081 - 7 Sep 2020
Cited by 22 | Viewed by 7436
Abstract
In 2019 the Canadian Space Agency initiated development of a dedicated wildfire monitoring satellite (WildFireSat) mission. The intent of this mission is to support operational wildfire management, smoke and air quality forecasting, and wildfire carbon emissions reporting. In order to deliver the mission [...] Read more.
In 2019 the Canadian Space Agency initiated development of a dedicated wildfire monitoring satellite (WildFireSat) mission. The intent of this mission is to support operational wildfire management, smoke and air quality forecasting, and wildfire carbon emissions reporting. In order to deliver the mission objectives, it was necessary to identify the technical and operational challenges which have prevented broad exploitation of Earth Observation (EO) in Canadian wildfire management and to address these challenges in the mission design. In this study we emphasize the first objective by documenting the results of wildfire management end-user engagement activities which were used to identify the key Fire Management Functionalities (FMFs) required for an Earth Observation wildfire monitoring system. These FMFs are then used to define the User Requirements for the Canadian Wildland Fire Monitoring System (CWFMS) which are refined here for the WildFireSat mission. The User Requirements are divided into Observational, Measurement, and Precision requirements and form the foundation for the design of the WildFireSat mission (currently in Phase-A, summer 2020). Full article
(This article belongs to the Special Issue Sensors for Fire and Smoke Monitoring)
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19 pages, 19361 KiB  
Article
Computationally Efficient Wildfire Detection Method Using a Deep Convolutional Network Pruned via Fourier Analysis
by Hongyi Pan, Diaa Badawi and Ahmet Enis Cetin
Sensors 2020, 20(10), 2891; https://doi.org/10.3390/s20102891 - 20 May 2020
Cited by 64 | Viewed by 4990
Abstract
In this paper, we propose a deep convolutional neural network for camera based wildfire detection. We train the neural network via transfer learning and use window based analysis strategy to increase the fire detection rate. To achieve computational efficiency, we calculate frequency response [...] Read more.
In this paper, we propose a deep convolutional neural network for camera based wildfire detection. We train the neural network via transfer learning and use window based analysis strategy to increase the fire detection rate. To achieve computational efficiency, we calculate frequency response of the kernels in convolutional and dense layers and eliminate those filters with low energy impulse response. Moreover, to reduce the storage for edge devices, we compare the convolutional kernels in Fourier domain and discard similar filters using the cosine similarity measure in the frequency domain. We test the performance of the neural network with a variety of wildfire video clips and the pruned system performs as good as the regular network in daytime wild fire detection, and it also works well on some night wild fire video clips. Full article
(This article belongs to the Special Issue Sensors for Fire and Smoke Monitoring)
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Review

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26 pages, 2546 KiB  
Review
A Review on Early Forest Fire Detection Systems Using Optical Remote Sensing
by Panagiotis Barmpoutis, Periklis Papaioannou, Kosmas Dimitropoulos and Nikos Grammalidis
Sensors 2020, 20(22), 6442; https://doi.org/10.3390/s20226442 - 11 Nov 2020
Cited by 331 | Viewed by 37168
Abstract
The environmental challenges the world faces nowadays have never been greater or more complex. Global areas covered by forests and urban woodlands are threatened by natural disasters that have increased dramatically during the last decades, in terms of both frequency and magnitude. Large-scale [...] Read more.
The environmental challenges the world faces nowadays have never been greater or more complex. Global areas covered by forests and urban woodlands are threatened by natural disasters that have increased dramatically during the last decades, in terms of both frequency and magnitude. Large-scale forest fires are one of the most harmful natural hazards affecting climate change and life around the world. Thus, to minimize their impacts on people and nature, the adoption of well-planned and closely coordinated effective prevention, early warning, and response approaches are necessary. This paper presents an overview of the optical remote sensing technologies used in early fire warning systems and provides an extensive survey on both flame and smoke detection algorithms employed by each technology. Three types of systems are identified, namely terrestrial, airborne, and spaceborne-based systems, while various models aiming to detect fire occurrences with high accuracy in challenging environments are studied. Finally, the strengths and weaknesses of fire detection systems based on optical remote sensing are discussed aiming to contribute to future research projects for the development of early warning fire systems. Full article
(This article belongs to the Special Issue Sensors for Fire and Smoke Monitoring)
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