@Article{cmes.2025.070944,
AUTHOR = {Hsiao-Chun Han, Der-Chen Huang, Chin-Ling Chen},
TITLE = {Applications of AI and Blockchain in Origin Traceability and Forensics: A Review of ICs, Pharmaceuticals, EVs, UAVs, and Robotics},
JOURNAL = {Computer Modeling in Engineering \& Sciences},
VOLUME = {145},
YEAR = {2025},
NUMBER = {1},
PAGES = {67--126},
URL = {http://www.techscience.com/CMES/v145n1/64349},
ISSN = {1526-1506},
ABSTRACT = {This study presents a systematic review of applications of artificial intelligence (abbreviated as AI) and blockchain in supply chain provenance traceability and legal forensics cover five sectors: integrated circuits (abbreviated as ICs), pharmaceuticals, electric vehicles (abbreviated as EVs), drones (abbreviated as UAVs), and robotics—in response to rising trade tensions and geopolitical conflicts, which have heightened concerns over product origin fraud and information security. While previous literature often focuses on single-industry contexts or isolated technologies, this review comprehensively surveys these sectors and categorizes 116 peer-reviewed studies by application domain, technical architecture, and functional objective. Special attention is given to traceability control mechanisms, data integrity, and the use of forensic technologies to detect origin fraud. The study further evaluates real-world implementations, including blockchain-enabled drug tracking systems, EV battery raw material traceability, and UAV authentication frameworks, demonstrating the practical value of these technologies. By identifying technological challenges and policy implications, this research provides a comprehensive foundation for future academic inquiry, industrial adoption, and regulatory development aimed at enhancing transparency, resilience, and trust in global supply chains.},
DOI = {10.32604/cmes.2025.070944}
}