Mentor: Younes Benkarroum
Student: Yusuf Mohammed
Poster:
Poster-2Abstract:
The rise in crime rates in New York State is a pressing issue, with the New York Police Department reporting a 27% increase in reported crimes in May 2022 compared to the previous year. To address this issue, this study proposes using computer vision technology to detect harmful objects, specifically evaluating the effectiveness of the “Single Shot Detector” algorithm and training a machine learning model using Google TensorFlow. The objective is to develop a system that connects to public cameras and analyzes real-time footage to detect suspicious activities and notify law enforcement which will help to reduce crime rates and promote a safer environment. The results of this study will provide insights into the potential of computer vision technology as a tool for crime prevention and offer a framework for implementing such a system in other cities facing similar challenges.
