Aerial wildfire identification soars high
A groundbreaking study, published in the IEEE Internet of Things Journal, has shown that networks of ground-based sensors paired with airborne drones could significantly improve wildfire detection and control. The research, led by a team from the King Abdullah University of Science and Technology (KAUST), simulated the performance of a wildfire detection Internet of Things (IoT)/Unmanned Aerial Vehicle (UAV) network under various UAV and IoT device densities.
The study found that, given optimal UAV and IoT device densities, a wildfire can be detected much faster compared to satellite imaging. This is particularly beneficial as current wildfire detection methods, such as satellite imaging and remote cameras, can be impeded by cloudy weather, and fires can grow to a considerable size before they are spotted.
UAVs, or drones, can be utilised to fly over the forest, wirelessly gathering data from each sensor. They then return to base to report a fire or to recharge their depleted batteries. Deploying a massive number of low-cost IoT sensors through the forest allows for early wildfire detection at the sensor level.
However, beyond a certain sensor density, the extra time UAVs spend gathering data in each location compromises their capability to monitor the whole forest. As a result, UAV-IoT networks can cover relatively small areas of forest compared to satellite imaging. Nevertheless, they would be particularly suitable for wildfire detection in high-risk regions, such as near human settlements and national parks.
The study also highlighted that inexpensive sensors do not have the battery or computational power to communicate a fire detection event across a massive IoT network to the fire control center. To overcome this, the researchers proposed a system where the UAVs would act as relay nodes, transmitting the fire detection data from the sensors to the fire control center.
With the rapid advancement of UAV-IoT networks, their ubiquitous application is becoming increasingly feasible at declining deployment costs. The study concludes by emphasising the potential of UAV-IoT networks in providing a critical edge for wildfire detection and control.
The DOI for the study is 10.1109/JIOT.2021.3077593. The research team simulated how a wildfire detection IoT/UAV network might perform and demonstrated that the more UAVs that are deployed, the faster a fire can be detected. This promising development could revolutionise wildfire detection and management, potentially saving lives and protecting valuable forest resources.
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