Unmanned Aerial Systems for Wildland and Forest Fires

Wildfires represent an important natural risk causing economic losses, human death and important environmental damage. In recent years, we witness an increase in fire intensity and frequency. Research has been conducted towards the development of dedicated solutions for wildland and forest fire assistance and fighting. Systems were proposed for the remote detection and tracking of fires. These systems have shown improvements in the area of efficient data collection and fire characterization within small scale environments. However, wildfires cover large areas making some of the proposed ground-based systems unsuitable for optimal coverage. To tackle this limitation, Unmanned Aerial Systems (UAS) were proposed. UAS have proven to be useful due to their maneuverability, allowing for the implementation of remote sensing, allocation strategies and task planning. They can provide a low-cost alternative for the prevention, detection and real-time support of firefighting. In this paper we review previous work related to the use of UAS in wildfires. Onboard sensor instruments, fire perception algorithms and coordination strategies are considered. In addition, we present some of the recent frameworks proposing the use of both aerial vehicles and Unmanned Ground Vehicles (UV) for a more efficient wildland firefighting strategy at a larger scale.Comment: A recent published version of this paper is available at: https://doi.org/10.3390/drones501001

Performance Analysis of a Cooperative Search Algorithm for Multiple Unmanned Aerial Vehicles under Limited Communication Conditions

This research investigates the impacts of realistic wireless communications upon a group of unmanned aerial vehicles (UAVs) utilizing a distributed search algorithm. The UAVs are used to survey an area for mobile targets and they require communication to cooperatively locate the targets. The mobile targets do not continually radiate energy, which exacerbates the search effort; a UAV could fly directly over a target and not detect it. A simulation of cooperative UAVs is implemented using the OPNET Modeler network simulation tool. The search performance of a group of UAVs is observed when communication range, data rate, and the number of UAVs are varied. The performance is evaluated based on the total time it takes for the UAVs to completely detect all the targets in a given search area, the number of times internal areas are scanned, the amount of communication throughput achieved, the network traffic generated, network latency, and number of network collisions. The results indicate that the number of UAVs was found to have the greatest impact on the group\u27s ability to search an area, implying that the data shared between the UAVs provides little benefit to the search algorithm. In addition, it was found that a network with a 100 Kbps or faster data rate should allow for minimal congestion and a large degree of scalability. The findings demonstrate that the proposed four-stage search algorithm should operate reasonably well under realistic conditions

Multi-UAV Integrated Internet of Things System for Generating Safe Map in Post-Disaster

芝浦工業大学2019年