Firing Range Scoring System

Overview

The Naval Education and Training Command (NETC) has identified the need for an automated live-fire scoring system to improve marksmanship training by replacing manual, paper-based evaluations. This project proposes a compact, portable prototype that uses computer vision and AI to detect and score bullet impacts on paper targets in real time. It integrates a high-resolution camera, Raspberry Pi 5 with AI acceleration, and a Python-based user interface. Using a YOLOv8 model for target detection and bullet scoring logic, the system provides immediate feedback and stores performance data for long-term tracking. Designed for indoor and outdoor use, the prototype follows a structured development process and sets the stage for future enhancements like automated calibration and cloud integration.

 

Community Benefit

The Naval Education and Training Command (NETC) seeks to enhance marksmanship training by addressing the limitations of manual scoring methods, which are prone to human error, slow feedback, and lack of long-term performance tracking. While electronic scoring systems exist, they are often costly, fragile, and unsuitable for outdoor use without major infrastructure changes. To overcome these challenges, this project proposes a cost-effective, portable, and durable scoring system using computer vision and AI. Featuring a high-resolution camera and real-time processing, the system offers accurate, reliable feedback with minimal setup, aligning with NETC’s mission to modernize and improve training efficiency.

 

Team Members

• Brandon Denardo 
• Ilia Fedorenko 
• Edgar Lopez 
• Christian Nering 
• Guillermo Tchelebi Cruz 

 

Sponsored By

Naval Education and Training Command (NETC)