TSAR: Trustworthy Search And Rescue uncrewed aerial vehicle
Lead Research Organisation:
Edge Hill University
Department Name: Computer Science
Abstract
Recent disasters around the globe, natural and manmade, claimed over a million lives and cost trillions of dollars in economic losses. Although disasters may not be prevented, rescue operations can considerably reduce the loss of life. Search And Rescue (SAR) is the foremost mission to be swiftly carried out in the aftermath of a disaster. First responders' search efforts in disaster situations, especially in contested areas (obstacles and foggy conditions) and war zones, are slow as they thoroughly examine the surroundings to avoid unnecessary debris shifts while protecting themselves. The existing state-of-the-art SAR Uncrewed Aerial Vehicles (UAVs) can only identify people in open areas using Artificial Intelligence (AI) algorithms. The proposed project, TSAR (Trustworthy SAR UAV), intends to develop an intelligent, trustworthy, reliable, and cost-effective SAR UAV that locates victims in contested areas and assesses their health. Such a UAV can expedite the search process and prioritize rescue missions for multiple casualties, enhancing successful rescue and saving lives.
TSAR's research objectives: 1) Design a novel UAV for SAR operations considering vertical take-off and landing capability, high endurance and range, maneuverability, fault tolerance, and reliability factors; 2) Develop innovative computer vision algorithms to separate the contested areas from open areas, and adapt Voronoi tessellations to generate low-altitude search trajectories in the open areas to get a closer look at the contested areas; 3) Develop multimodal AI algorithms to fuse and process the data from the auditory and visual sensors to geo-locate victims; 4) Non-disruptive health check maneuvers providing maximum visual coverage of victims and their health status via a novel algorithm by analyzing heat signatures; and 5) TSAR's trustworthiness will be achieved by considering legal, ethical, system and human elements embedded through design, development and testing phases.
TSAR's research objectives: 1) Design a novel UAV for SAR operations considering vertical take-off and landing capability, high endurance and range, maneuverability, fault tolerance, and reliability factors; 2) Develop innovative computer vision algorithms to separate the contested areas from open areas, and adapt Voronoi tessellations to generate low-altitude search trajectories in the open areas to get a closer look at the contested areas; 3) Develop multimodal AI algorithms to fuse and process the data from the auditory and visual sensors to geo-locate victims; 4) Non-disruptive health check maneuvers providing maximum visual coverage of victims and their health status via a novel algorithm by analyzing heat signatures; and 5) TSAR's trustworthiness will be achieved by considering legal, ethical, system and human elements embedded through design, development and testing phases.
