A Study on AI-based Bloodstains and Footprints Detection in Crime Scene Investigations

In criminal investigations, investigators must analyze crime scene evidence and conduct a forensic examination of physical evidence, including bloodstains and footprint impressions. Such examination allows investigators to reconstruct the crime scene, and in some cases, determine which crimes were committed by the criminal. When examining bloodstains and footprint impressions, the investigator's role is to identify, collect, preserve, and analyze any evidence systematically. The collection and analysis of bloodstains and any impressions of footprints is often time-consuming, flawed by human error, or, in some cases, compromises the evidence they are trying to preserve at a crime scene. The research study aims to explore existing research methods that can address these challenges by utilizing artificial intelligence for the automatic identification and classification of bloodstains and footprint impressions, while preserving the crime scene and accelerating the analysis process, thereby enhancing the quality of evidence analysis. Based on the research study, the proposed system has been designed to utilize artificial intelligence to identify and process crime scene evidence.