Streamlining Military Equipment Inspection with AI-powered Detection

The research is a computerized technique that uses the YOLO-NAS (You Only Look Once with Neural Architecture Search) algorithm to identify troops' protective gear. This system is especially designed for military operations, where quick and accurate identification is essential in difficult surroundings, such as low light and obstructed conditions, in contrast to earlier work using YOLO-based algorithms utilized in industrial settings. By correctly identifying necessary protective gear, such gloves, helmets, and vests, the system shortens inspection times and lowers the dangers of inadequate protection. This approach improves mission effectiveness and soldier welfare by guaranteeing that soldiers are properly prepared before venturing into hazardous areas. Furthermore, by lowering the danger of injuries and fatalities during military operations, it advances Sustainable Development Goal (SDG) 3: Good Health and Well-Being. As of right now, the system has undergone laboratory testing (Technology Readiness Level 4), and it is moving closer to TRL 6 for field testing and military process integration.