AI-Enabled Policing through CCTNS Data Analysis: A Quantitative Study on smarter FIR Filing and Resource Optimization in India

The policing system in India has to deal with significant workload with limited human and institutional capacity. This paper tires to find how Artificial Intelligence when integrated into Crime and criminal tracking Network and systems can help in strengthening the speed and quality of FIR drafting, or FIR Automation with smoothen routine documentation and data centric decision implementation. The analysis of the study was done by using verified secondary sources that helped in understanding the patterns of investigation, reporting and digital adoption that undermines the debate of India’s transition in evidence based-policing technologies that also require Digital Policing Reforms. This paper draws a comparison between domestic developments with international models and tries to identify the gaps where AI can reduce the clerical burden and assist in disposing caseloads. Issues of transparency, privacy protection and responsible accountability that are transformed by the ethical and legal principles are also emphasized in this study. The findings suggest that AI should be introduced gradually and carefully with each AI adoption being evaluated using real data and measurable outcomes eventually transforming the Indian Criminal Justice system.

Artificial Intelligence in Policing, CCTNS Integration, FIR Automation, Digital Policing Reform, Predictive Analysis, Resource Allocation, Indian Criminal Justice System

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