SCOPIA: Self-navigating Crime-scene Officer for Processing, Investigation & Analysis

Crime Scene Investigation (CSI) requires accurate evidence identification, thorough documentation, and strict preservation of data integrity, often under hazardous and time-critical conditions. Traditional manual investigation methods expose investigators to physical risks, increase the likelihood of evidence contamination, and provide limited spatial documentation of complex scenes. This paper presents S.C.O.P.I.A. (Self-navigating Crime-scene Officer for Processing, Investigation and Analysis), an integrated robotic and software-based system designed to enhance forensic investigation through automation, secure data handling, and intelligent analysis.

The proposed system deploys an autonomous tracked rover equipped with multimodal sensors, visual SLAM, and deep learning–based object detection to safely navigate crime scenes and identify forensic evidence such as weapons, blood patterns, broken objects, and human presence. Captured images are used to generate accurate three-dimensional reconstructions of the scene using Structure from Motion and Multi-View Stereo techniques, enabling investigators to revisit and analyze scenes virtually. A secure forensic software platform encrypts all visual evidence using AES-256-CBC and verifies integrity through HMAC-SHA256 to ensure confidentiality and tamper detection.

Additionally, the system integrates an AI-assisted forensic analysis agent based on a contextual system prompt that compiles case information with the list of clues and suspects as well as the digital forensic graph in textual form. By combining autonomous robotics, computer vision, secure software engineering, and explainable AI, S.C.O.P.I.A. improves investigator safety, evidence reliability, and analytical efficiency, demonstrating a scalable and modern approach to crime scene investigation.

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