Augmented reality for crime scene analysis

Inspiration The traditional CSI process is time-consuming and is prone to errors. We wanted to use Augmented Reality (AR) and AI to help investigators see and study digital evidence at the crime scene in real-time. The purpose of the investigation was to modernize and make it more accurate.

How we built it This project has been created with python. We applied YOLOv8 for fast object detection, such as weapons and digital devices. Our model was integrated into the AR interface using the Flask framework.The Flask framework was used to link our model to the AR interface.

Challenges we faced The main problem was getting the object detection model, YOLOv8, to detect the objects accurately under various lighting conditions. Our system diagrams were another challenge, and we had to work hard to keep our team members' work (such as our backend, design, reporting, etc.) coordinated.

What we learned In this project, we had learnt many things about Computer Vision and AR. We also learned how to solve real world digital forensic issues and how to deal with a technical project from start to finish.