Developing A CCTV-AI System with The Capability to Accurately Detect and Recognize Individuals Who Are Wearing Helmets, Specifically Targeting Riders and Passengers.
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Currently, Thailand is experiencing a high mortality rate due to motorcycle accidents, coupled with a low rate of helmet usage. Previous research has indicated that law enforcement measures can effectively increase helmet compliance. To address this issue, a study was conducted to create a system using artificial intelligence and CCTV technology to identify riders and passengers who are not wearing helmets. The study involved four key stages: data collection, software development utilizing Yolo V.4 library, neural network training, and accuracy assessment. Results demonstrate that the program can successfully identify non-helmet-wearing riders with a 95% accuracy rate, which is deemed suitable for implementation by law enforcement agencies.
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