<![CDATA[Security is important for housing. In general, housing now uses rfid to enter through the gate. In addition to the use of rfid, there are human workers who help secure access to housing. However, access to housing using rfid and human labor has the disadvantage that rfid can be lost and human labor can feel tired. With the existing problems, a system is needed that can help cover these weaknesses. A vehicle license plate detection system was created for residential residents using the YOLOv5 and jetson nano-based pytesseract methods. YOLOv5 (You Only Look Once) is a fast and accurate new object detection algorithm that is suitable for real-time applications. This system will recognize the vehicle number plates of residential occupants starting from training data and license plate detection using YOLOv5 and then, when the vehicle number plate has been detected, the contents of the number plate will be read using the pytesseract ocr (optical character recognition) method so that it can open the housing access door latch. . This recognition system uses training data of 502 images of vehicle license plates. The result of this test is the movement of the servo motor for housing access when the number plate is detected in the data file. The accuracy obtained in this study was 100% for the number plate detection system and 100% for the identification of vehicle occupants' vehicle license plates.]]>
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