Intelligent and vision-based fire detection systems: A survey

Bu, Fengju; Gharajeh, Mohammad Samadi

doi:10.1016/j.imavis.2019.08.007

Cited by 109 publications

(36 citation statements)

References 42 publications

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“…Recent advances in computer vision, machine learning, and remote sensing technologies offer new tools for detecting and monitoring forest fires, while the development of new materials and microelectronics have allowed sensors to be more efficient in identifying active forest fires. Unlike other fire detection review papers that have focused on various sensing technologies [ 5 ], on video flame or/and smoke methodologies in visible or/and InfraRed (IR) range [ 6 , 7 , 8 , 9 ], on various environments [ 10 ], and airborne systems [ 11 , 12 ], in this paper, we provide a comprehensive study of the most representative forest fire detection systems, focusing on those that use optical remote sensing, as well as digital image processing [ 13 ] and classification techniques [ 14 ]. Depending on the acquisition level, three broad categories of widely used systems that can detect or monitor active fire or smoke incidents in real/near-real-time are identified and discussed, namely terrestrial, aerial, and satellite.…”

Section: Introductionmentioning

confidence: 99%

A Review on Early Forest Fire Detection Systems Using Optical Remote Sensing

Barmpoutis

Papaioannou

Dimitropoulos

et al. 2020

Sensors

285

106

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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.

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Section: Introductionmentioning

confidence: 99%

A Review on Early Forest Fire Detection Systems Using Optical Remote Sensing

Barmpoutis

Papaioannou

Dimitropoulos

et al. 2020

Sensors

285

106

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“…For the developed proof-of-concept, an algorithm was created to detect the complex event of "Fire", demonstrating how instance and complex events may be simultaneously detected by an EDU. In fact, there are plenty of solutions for such processing, which has evolved considerably [39,40]. For this particular implementation, we employed the OpenCV framework [41], which is an open-source multi-platform library that supports a great number of functions to process visual data.…”

Section: Implementation Detailsmentioning

confidence: 99%

On the Use of Cameras for the Detection of Critical Events in Sensors-Based Emergency Alerting Systems

Costa

Vasques

Portugal

et al. 2020

JSAN

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The adoption of emergency alerting systems can bring countless benefits when managing urban areas, industrial plants, farms, roads and virtually any area that is subject to the occurrence of critical events, supporting in rescue operations and reducing their negative impacts. For such systems, a promising approach is to exploit scalar sensors to detect events of interest, allowing for the distributed monitoring of different variables. However, the use of cameras as visual sensors can enhance the detection of critical events, which can be employed along with scalar sensors for a more comprehensive perception of the environment. Although the particularities of visual sensing may be challenging in some scenarios, the combination of scalar and visual sensors for the early detection of emergency situations can be valuable for many scenarios, such as smart cities and industry 4.0, bringing promising results. Therefore, in this article, we extend a sensors-based emergency detection and alerting system to also exploit visual monitoring when identifying critical events. Implementation and experimental details are provided to reinforce the use of cameras as a relevant sensor unit, bringing promising results for emergencies management.

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“…Recent research emphasize on the suitability of deep learning techniques adoption for assisting SAR missions supported by UAVs [21] [22]. Such approaches involve autonomous navigation of aerial vehicles [23], exploration of various unknown cluttered environments [24] or rescue missions conduction in indoor environments for human presence recognition [25].…”

Section: Notable Research Has Been Conducted Towards Vision-based Vicmentioning

confidence: 99%

Vision and Geolocation Data Combination for Precise Human Detection and Tracking in Search and Rescue Operations

Lygouras¹

2020

IJIS

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In this paper, a study and evaluation of the combination of GPS/GNSS techniques and advanced image processing algorithms for distressed human detection, positioning and tracking, from a fully autonomous Unmanned Aerial Vehicle (UAV)-based rescue support system, are presented. In particular, the issue of human detection both on terrestrial and marine environment under several illumination and background conditions, as the human silhouette in water differs significantly from a terrestrial one, is addressed. A robust approach, including an adaptive distressed human detection algorithm running every N input image frames combined with a much faster tracking algorithm, is proposed. Real time or near-real-time distressed human detection rates achieved, using a single, low cost day/night NIR camera mounted onboard a fully autonomous UAV for Search and Rescue (SAR) operations. Moreover, the generation of our own dataset, for the image processing algorithms training is also presented. Details about both hardware and software configuration as well as the assessment of the proposed approach performance are fully discussed. Last, a comparison of the proposed approach to other human detection methods used in the literature is presented.

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Intelligent and vision-based fire detection systems: A survey

Cited by 109 publications

References 42 publications

A Review on Early Forest Fire Detection Systems Using Optical Remote Sensing

A Review on Early Forest Fire Detection Systems Using Optical Remote Sensing

On the Use of Cameras for the Detection of Critical Events in Sensors-Based Emergency Alerting Systems

Vision and Geolocation Data Combination for Precise Human Detection and Tracking in Search and Rescue Operations

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