Use of Artificial Intelligence and Digital Technologies in Disaster Victim Identification (DVI): Current Developments, Challenges, and Future Perspectives

Disaster victim identification (DVI) represents a critical component of forensic investigation during mass fatality incidents caused by natural disasters, transportation accidents, terrorist attacks, and armed conflicts. Traditional identification techniques—namely fingerprint analysis, dental record comparison, and DNA profiling—remain the gold standard [1–5]; however, their effectiveness is often compromised in cases involving severe decomposition, fragmentation, or lack of antemortem records [4,5,16]. Recent advances in artificial intelligence (AI) and digital technologies have introduced innovative tools capable of improving the efficiency, accuracy, and scalability of DVI operations [6–9,14,22]. This review provides a comprehensive and critical analysis of contemporary applications of AI in forensic identification, including facial recognition, forensic odontology, postmortem imaging, DNA analysis, drone-assisted recovery, and integrated forensic data systems [10–15,17–19]. In addition, the study highlights key challenges such as ethical concerns, data privacy, algorithmic bias, and disparities in global technological infrastructure [19,36]. AI-driven forensic technologies demonstrate strong potential to enhance disaster response systems; however, their implementation requires rigorous validation, international standardization, and regulatory oversight [6,9,18,36].