Drones and Sensors Could Spot Fires Before They Go Wild

To detect wildfires earlier on, some researchers are proposing a novel solution that harnesses a network of Internet of Things (IoT) sensors and a fleet of drones, or unmanned aerial vehicles (UAVs). IEEE Spectrum reports: The researchers tested their approach through simulations, described in a study published May 5 in IEEE Internet of Things Journal, finding that it can detect fires that are just 2.5 km2 (just under one square mile) in size with near perfect accuracy. 'In the last few years, the number, frequency, and severity of wildfires have increased dramatically worldwide, significantly impacting countries' economies, ecosystems, and communities. Wildfire management presents a significant challenge in which early fire detection is key,' emphasizes Osama Bushnaq, a senior researcher at the Autonomous Robotics Research Center of the Technology Innovation Institute in Abu Dhabi, who was involved in the study.

The approach that Bushnaq and his colleagues are proposing involves a network of IoT sensors scattered throughout regions of concern, such as a national park or forests situated near communities. If a fire ignites, IoT devices deployed in the area will detect it and wait until a patrolling UAV is within transmission range to report their measurements. If a UAV receives multiple positive detections by the IoT devices, it will notify the nearby firefighting department that a wildfire has been verified.

The researchers evaluated a number of different UAVs and IoT sensors based on cost and features to determine the optimal combinations. Next, they tested their UAV-IoT approach through simulations, whereby 420 IoT sensors were deployed and 18 UAVs patrolled per square kilometer of simulated forest. The system could detect fires covering 2.5 km2 with greater than 99 percent accuracy. For smaller fires covering 0.5 km2 the approach yielded 69 percent accuracy. These results suggest that, if an optimal number of UAVs and IoT devices are present, wildfires can be detected in much shorter time than with the satellite imaging.

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