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With the fast growth of IoT and AI techniques, AIoT’s potential in creating and capturing business value is being increasingly acknowledged. AIoT is the practice of combining AI with IoT-based hardware to proactively predict what might happen and what action needs to be taken. However, research on this issue has been limited and what the key mechanisms for designing AIoT-based context-aware services are in the real field is still underexplored. In this article, the authors bridge this gap by studying a case study of AIoT-based context-aware system in law enforcement in terms of information system artifacts to extend our understating of the AIoT-based system’s mechanisms for business applications. The case study reveals a conceptual model that can ensure AIoT-empowered context-aware services in a police field unit. The implications, limitations, and future applications of the development of AIoT-empowered context-aware services are discussed.

Towards Convergence of AI and IoT for Smart Policing: A Case of a Mobile Edge Computing-Based Context-Aware System