IJLTEMAS International Journal of Latest Technology in Engineering, Management & Applied Science (IJLTEMAS) IJLTEMAS 2278-2540 IJLTEMAS 120 10.51583/IJLTEMAS.2026.150700115 Artificial Intelligence Technologies in the Architecture of an AI-Driven Analytical Engine: Facilitating Real-time Police Surveillance Arup Barman Prof Professor, Dept of Business Administration, Assam University, Silchar (India) India Nath Saswati Superintendent of Training, North East Police Academy, Meghalaya (India) India 15 7 1517 1537 08 08 2026 13 08 2026 20 08 2026 Real-time Policing Data Fusion Technology Fusion Integrated intelligence Analytical Engine Technology Architecture Abstract

In the age of artificial intelligence, real-time policing relies on high-level and diverse technologies. Generating data, decisions, responses, and surveillance strategies depends on efficient system generation. AI is critically important for real-time surveillance and policing, from data collection and analysis to decision execution. To implement AI technologies, data fusion and computing fusion occur at multiple points between data collection and response operations. The paper synthesises the empirical evidence of AI and related technologies used for real-time policing and surveillance. As real-time surveillance technologies are multifarious, multi-staged technologies are used in an AI-driven analytical engine that ranges from data collection to operational response; a clear mapping of the technology architecture is needed. This paper attempts to identify technologies, synthesise the use, and design a robust technology mapping to complete the architecture of an AI-driven data analytical engine for enabling real-time surveillance intelligence. The paper synthesised and classified the technologies used in real-time AI-Driven Policing (RTAIDP), which could fill a strong gap in existing literature on real-time policing, even though AI policing literature is abundant.

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