Sistema de control de acceso por medio de reconocimiento facial con uso de mascarilla y monitoreo de temperatura

Abstract

The world is going through a health crisis that has affected many people, the number of infections has been gradually increasing due to non-compliance with biosafety regulations by citizens. The present degree work describes the development of a control system through facial recognition with the use of a mask and temperature monitoring, where there is control of the acquired data, which are stored for later analysis. The control system is made up of three stages, these being: data acquisition through the temperature sensor and a webcam to later be sent to the Raspberry Pi development card so that it receives the information and performs the process of recognition of use. of masks through convolutional neural networks, which detect whether or not a person is wearing the mask, the information is sent through the MQTT network protocol that transports messages between devices, a mobile app is used to view the data which is linked to ThingSpeak, which is an Internet of things platform, in case the temperature exceeds its nominal value, an alert signal will be sent to the Telegram messaging application. This project is aimed at controlling the entry of people, whether in public or private places, avoiding direct contact with control personnel, and monitoring the correct temperature for the respective entry.