Forest Fire Monitoring System Based on UAV Team, Remote Sensing, and Image Processing

Sherstjuk, Volodymyr; Zharikova, Maryna; Сокол, Ігор

doi:10.1109/dsmp.2018.8478590

Cited by 27 publications

(10 citation statements)

References 9 publications

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“…The results have shown the accuracy of 91%, based on a data set of 544 images (with disaster images, such as collapsed buildings, earthquakes, floods, fires, tsunamis, and nondisaster scenes), which indicates that deep learning, together with UAVs with camera sensors, can anticipate a disaster with high accuracy. Sherstjuk et al (2018) presented the tactical forest fire‐fighting detection and monitoring system based on remote sensing, UAV, and image processing. It defined a system with its general parameters and options, and also the system's functions, activities, and architecture are taken into account.…”

Section: Data Collection Through Uavs For Various Dm Scenariosmentioning

confidence: 99%

Emerging UAV technology for disaster detection, mitigation, response, and preparedness

Khan

Gupta

2022

Journal of Field Robotics

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In recent years, Unmanned Aerial Vehicles (UAVs) have gained significant interest in research groups due to the wide range of applications, such as disaster surveillance and monitoring, rescue operations, military, civil, and so forth. UAVs are most often used to fulfill both user's services and requirements such as wireless communication facilities to end-users, as a relay node to extend the coverage of the core network, and so forth. UAVs are versatile in design and can cover larger areas, contrary to the Tethered Balloon and Loon Balloon systems. Generally in any natural or humanmade disaster, there is a high potential risk of damage to buildings, transport systems, communication systems, and basic services. During heavy disasters like landslides, forest fires, floods, earthquakes, and so forth, the conventional terrestrial communication system gets destroyed, and people face many problems. In this case, UAVs prove to offer a better solution to provide fast, cost-effective, easy to deploy, and secure wireless communication to the victims. But there are some issues like interference between UAVs and other base stations, coordination between UAVs, Quality of Service requirements, Size, Weight, and Power limitation, delay, coverage, positioning of UAVs, and so forth. This study article mainly highlighted these issues and try to present the recent developments of the state-of-the-art to overcome these issues. In UAV communications, with an increasing emphasis on how UAVs can be integrated with different technologies, such as the Internet of Things, Wireless Sensor Network, Heterogeneous Network, and Cloud computing. The primary aim of this article is to examine how UAVs can assist survivors in floods, earthquakes, tsunamis, or in any natural or human-made disaster situations, either in the present or soon. Also, it focused on various applications of UAVs in disaster management (DM). It underlines the significance of UAVs in DM and their advantages. It also focuses on the various issues and challenges faced by the UAV-based infrastructure and security issues and gives future directions.

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Section: Data Collection Through Uavs For Various Dm Scenariosmentioning

confidence: 99%

Emerging UAV technology for disaster detection, mitigation, response, and preparedness

Khan

Gupta

2022

Journal of Field Robotics

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“…• the moderate resolution imaging spectroradiometer (MODIS) [24], launched in 1999, and the Visible Infrared Imaging Radiometer Suite (VIIRS) [25] that was launched in 2011 gave the capability for the use of a new generation of operational moderate resolution-imaging following the legacy of the AVHRR on NOAA and MODIS on Terra and Aqua satellites.…”

Section: Satellite-based Systemsmentioning

confidence: 99%

“…Generally, UAVs are used across the world for various civil applications in search and rescue, surveillance, journalism, and agriculture among others. According to Sherstjuk et al [24], UAVs should fulfill some requirements for their autonomous operation in forest areas for early detection of wildfires:…”

Section: Unmanned Aerial Vehicles (Uav) Based Systemsmentioning

confidence: 99%

From Pillars to AI Technology-Based Forest Fire Protection Systems

Aspragathos¹,

Dogkas²,

Konstantinidis³

et al. 2020

Intelligent System and Computing

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The importance of forest environment in the perspective of the biodiversity as well as from the economic resources which forests enclose, is more than evident. Any threat posed to this critical component of the environment should be identified and attacked through the use of the most efficient available technological means. Early warning and immediate response to a fire event are critical in avoiding great environmental damages. Fire risk assessment, reliable detection and localization of fire as well as motion planning, constitute the most vital ingredients of a fire protection system. In this chapter, we review the evolution of the forest fire protection systems and emphasize on open issues and the improvements that can be achieved using artificial intelligence technology. We start our tour from the pillars which were for a long time period, the only possible method to oversee the forest fires. Then, we will proceed to the exploration of early AI systems and will end-up with nowadays systems that might receive multimodal data from satellites, optical and thermal sensors, smart phones and UAVs and use techniques that cover the spectrum from early signal processing algorithms to latest deep learning-based ones to achieving the ultimate goal.

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“…Watchtowers have limited sight that can barely cover the whole area of interest. Although satellite remote sensing is capable of detecting large-scale forest fires, the cost of start-up and maintenance is pretty high, and the monitoring effect is often affected by weather, cloud thickness, orbital period etc., let alone sizes of early forest fires [1]. As flight control technology improves by leaps and bounds, unmanned aerial vehicles (UAVs) have been widely used in the field of forest fire detection due to flexibility and low cost.…”

Section: Introductionmentioning

confidence: 99%

Pyramid Attention Based Early Forest Fire Detection Using UAV Imagery

Zhang

Chen²,

Wang³

et al. 2022

J. Phys.: Conf. Ser.

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Early forest fire detection using unmanned aerial vehicle (UAV) imagery is widely implemented in recent years. However, as the size of moving object in UAV imagery changes dramatically, the issues of focusing more informative areas of an image, large-scale variation as well as temporal consistency preservation have yet to be resolved due to the wide field of vision of UAVs in flight. To address these issues, in this work, we concerned the visual characteristics of early stage forest fire in UAV imagery and employ pyramid attention mechanism. We engineered a novel convolutional neural network (CNN) based on the state-of-the-art backbone by stacking our proposed PyrAtten blocks. We built a large dataset of early stage forest fire, including real world aerial photographs shot using our UAV prototype. Extensive evaluation of PyrAtten demonstrates its efficiency and effectiveness in detecting multi-scale objects of fire and smoke in UAV imagery, even if the object takes up a very small proportion of the whole image. Compared with existing similarly-sized networks, average detecting accuracy of PyrAtten-ResNet-50 reaches 97.5%, with negligible increase in computational overhead.

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Forest Fire Monitoring System Based on UAV Team, Remote Sensing, and Image Processing

Cited by 27 publications

References 9 publications

Emerging UAV technology for disaster detection, mitigation, response, and preparedness

Emerging UAV technology for disaster detection, mitigation, response, and preparedness

From Pillars to AI Technology-Based Forest Fire Protection Systems

Pyramid Attention Based Early Forest Fire Detection Using UAV Imagery

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