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Figure 1
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Figure 2
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Team 39

Team Members

Faculty Advisor

Mathew Kirschbaum
Zachary Zambuto

Seung-Hyun Hong

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Remote Firearm Detection

In recent years, the US has experienced many tragic shooting events. Businesses and public places need a security system design that can identify, deter, and eliminate threats with concealed firearms before tragedies occur. Our project uses modern AI and object detection to identify both concealed and openly visible firearms. The system has the flexibility to forward the detection results to a web-app interface or log the detections for future reference. We designed our project to find a good balance between size, speed, and cost – all aspects of the system are self-contained on a single small form factor computer – NVIDIA’s Jetson Nano – along with either a standard or infrared camera (for detecting concealed weapons). The end result is a model that can detect open carry rifles and pistols at ~84 % MaP and concealed at ~70% MaP.