AI Surveillance System for Detecting Criminal Intent in Voice and Chat Communication

With the rapid growth of digital communication 
platforms, voice calls and online chat systems have become 
common mediums for interaction, but they are also increasingly 
exploited for coordinating unlawful activities. Traditional surveil
lance approaches based on simple keyword detection often fail 
to understand context, emotions, and evolving language patterns, 
leading to high false positives and missed threats. This project 
proposes an AI-based surveillance system for detecting criminal 
intent in both voice and chat communication through a unified 
platform. The system converts voice inputs into text using speech
to-text technology and applies natural language processing (NLP) 
techniques to analyze messages for suspicious intent in real time. 
If any unwanted or potentially harmful message is detected, it is 
automatically reported to an admin dashboard for further action. 
Additionally, the system incorporates a continuous learning 
mechanism where newly identified keywords or sentence patterns 
are treated as new data, enabling the model to adapt and 
improve over time. The proposed system aims to deliver context
aware, real-time threat detection, reduce false alerts, and enhance 
proactive monitoring in modern communication environments.