Smoking Violation Detection System Using YOLO in Non-Smoking Areas in Medan City
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Abstract
The city of Medan has recorded a significant increase in the percentage of smokers in recent years. This is in line with the increase in the prevalence of smokers nationally. There are a lot of deaths caused by smoking habits in Indonesia every year. To reduce the negative impact of cigarettes and protect public health, the Medan City government has issued a Regional Regulation on Smoke-Free Areas (KTR). Even though there are regulations regulating non-smoking areas in the city of Medan, it turns out that the level of compliance of the people of Medan is still very low. This research aims to create a system that can detect smoking violations in the smoke-free area of Medan city. This study uses the YOLOv5l model to detect cigarettes. The researcher collects and analyzes the necessary datasets. The dataset is divided into data training, validation, and testing. The model evaluated using test data got a fairly good mAP score. The model is also dieva.
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