Real-time autonomous wildfire monitoring and georeferencing using rapidly deployable mobile units

Perez-Mato, Javier; Arana, V.; Cabrera-Almeida, Francisco

doi:10.1109/taes.2016.150057

Cited by 2 publications

(5 citation statements)

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“…The goal was to develop a model for early-warning fire monitoring systems. [68] proposed a framework for prototyping rapidly deployable mobile units for autonomous, real-time wildfire monitoring and georeferencing. [69] described the development process of a thermal infrared camera with the uncooled microbolometer array for a 50-kg class satellite to be used for small wildfire detection.…”

Section: Early Detection Of Wildfiresmentioning

confidence: 99%

Three Lines of Defense for Wildfire Risk Management in Electric Power Grids: A Review

et al. 2021

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Wildfires pose a significant challenge to the natural and the built environments, as well as the safety and economic wellbeing of the communities residing in wildfire-prone areas. The electric power grid is specifically among the built environments most affected by, and contributing to, wildfires. In this paper, we propose a three lines of defense (3LD) framework for wildfire risk management in electric power infrastructure and review the literature from this lens. An overview of the physics and phenomenology of the wildfires as it relates to power grids is presented, and the logic for the proposed 3LD framework is discussed. The reviewed literature based on the 3LD theme includes the most relevant and emerging research work on wildfire prevention as the first line of defense, wildfire mitigation and proactive response as the second line of defense, and wildfire recovery preparedness as the third line of defense. This study reveals that while the state of the art, to a large extent, stands comprehensive in various aspects of power system resilience and wildfire risk management, there is a gap in the literature in addressing this emerging risk in a holistic, interdisciplinary approach.

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Section: Early Detection Of Wildfiresmentioning

confidence: 99%

Three Lines of Defense for Wildfire Risk Management in Electric Power Grids: A Review

et al. 2021

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“…The precise determination of the location (latitude, longitude, and altitude) and the accurate calculation of the attitude by the thermographic camera are the key requirements to achieving successful georeferencing. As described in [ 13 ], the generation of the synthetic image relies solely on these two sets of inputs, so a high degree of precision for their determination benefits the whole system. Also, it must account for possible errors in calibration, especially regarding radiometric effects and the possible attenuation of thermal radiation by the atmosphere, which could cause both false negatives and false positives during the fire identification process.…”

Section: Sources Of Error and Limitations Of An Automated Wildfirementioning

confidence: 99%

“…Figure 1 describes how the synthetic image is created in the RDMU using the ray-tracing techniques described in [ 13 ]. This process uses as inputs the thermographic camera’s location, attitude, and optical characteristics.…”

Section: Sources Of Error and Limitations Of An Automated Wildfirementioning

confidence: 99%

“…Some proposals have been made to implement either mobile or fixed sensor networks to detect the occurrence of wildfires [ 10 , 11 , 12 ], but they usually lack a certain degree of dynamic reconfigurability and ease of use. Furthermore, an emphasis was made in [ 13 ] to use low-cost components in order to make the solution more cost-effective and, therefore, more replicable.…”

Section: Introductionmentioning

confidence: 99%

“…A system capable of solving these limitations was implemented in [ 13 ]. It relies on an innovative use of synthetic vision technology, combined with a fully automated and rapidly deployable thermographic camera to detect and track the evolution of a wildfire in a completely autonomous manner (RDMU: Rapidly Deployable Mobile Unit).…”

Section: Introductionmentioning

confidence: 99%

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Challenges of an Autonomous Wildfire Geolocation System Based on Synthetic Vision Technology

Arana

Cabrera-Almeida

Perez-Mato

et al. 2018

Sensors

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Thermographic imaging has been the preferred technology for the detection and tracking of wildfires for many years. Thermographic cameras provide some very important advantages, such as the ability to remotely detect hotspots which could potentially turn into wildfires if the appropriate conditions are met. Also, they can serve as a key preventive method, especially when the 30-30-30 rule is met, which describes a situation where the ambient temperature is higher than 30 ∘C, the relative humidity is lower than 30%, and the wind speed is higher than 30 km/h. Under these circumstances, the likelihood of a wildfire outburst is quite high, and its effects can be catastrophic due to the high-speed winds and dry conditions. If this sort of scenario actually occurs, every possible technological advantage shall be used by firefighting teams to enable the rapid and efficient coordination of their response teams and to control the wildfire following a safe and well-planned strategy. However, most of the early detection methods for wildfires, such as the aforementioned thermographic cameras, lack a sufficient level of automation and usually rely on human interaction, imposing high degrees of subjectivity and latency. This is especially critical when a high volume of data is required in real time to correctly support decision-making scenarios during the wildfire suppression tasks. The present paper addresses this situation by analyzing the challenges faced by a fully autonomous wildfire detection and a tracking system containing a fully automated wildfire georeferencing system based on synthetic vision technology. Such a tool would provide firefighting teams with a solution capable of continuously surveilling a particular area and completely autonomously identifying and providing georeferenced information on current or potential wildfires in real time.

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Real-time autonomous wildfire monitoring and georeferencing using rapidly deployable mobile units

Cited by 2 publications

References 6 publications

Three Lines of Defense for Wildfire Risk Management in Electric Power Grids: A Review

Three Lines of Defense for Wildfire Risk Management in Electric Power Grids: A Review

Challenges of an Autonomous Wildfire Geolocation System Based on Synthetic Vision Technology

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