A Review on Ai-Integrated Helmet-Mounted Thermal Imaging Systems for Victim Detection in Disaster Response Scenarios

Abstract

This review examines the integration of artificial intelligence (AI) with helmet-mounted thermal imaging systems to enhance victim detection during disaster response operations. The fusion of AI algorithms with thermal imaging technology has led to significant advancements in identifying and locating victims in environments with limited visibility, such as those affected by smoke, darkness, or structural obstructions. Recent developments include the deployment of smart helmets equipped with infrared cameras, real-time object recognition capabilities, and augmented reality displays, all designed to improve situational awareness for first responders. Field trials have demonstrated the efficacy of these systems in accelerating victim detection and improving navigation in complex disaster scenarios. The review also discusses the challenges associated with implementing these technologies, including issues related to power autonomy, equipment compatibility, and data processing requirements. Future research directions are proposed to address these challenges and to further integrate AI-driven thermal imaging solutions into standard emergency response protocols.