Abstract
Person detection is an interesting machine learning application that can be implemented in embedded devices. One such need is to automate an alarm system to detect whether a person that works in a Point of Sale is indeed working at his/her working time. This presence monitoring system can be automated by using an esp-eye development board by Espressif. In this paper, the key important aspect of modelling the person detection behavior is discussed and implemented in ESP32 technologies. The rate of accuracy in detecting a person’s presence is up to 65% based on a four (4) minute window-time, and therefore it is reliable to be used as a person’s monitoring automated system, based on the current requirement from the food industry. The inference time is circa 0,7 MS, that is the time between each sample in a situation where a person is in front of the camera.
Keywords
ESP32, ESP-EYE, person detection, inference and Convolutional Neural Network