Smart airport Check-In and Guidance system with Access Control and, Health Surveillance using IoT and AI for Oman Airports.
Keywords:OpenCV, Face Recognition, KNN, Raspberry Pi, SRS, GS, ACS, HSSS, MCD, MCU, FaceNet, MTCNN
"Airports Intelligent Inspection and Guidance System with Access Control and Health Monitoring Using IoT and Artificial Intelligence for Oman Airports" is an IoT project with AI touch that aims to provide an easier and smart way to manage traditional travel operations. The traditional way of checking in is that travelers must queue at immigration offices for an extended period which on many occasions results in delays or missed flights. This project uses Internet of Things technology combined with computer vision to provide an easier and smarter way to interact with each other. The main technology that will be implemented in this project is the use
of OpenCV for face detection and recognition using the KNN algorithm. Starting with selfregistration desks, a Raspberry Pi camera will capture the photo, associate it with relevant information, and record that information into a central database. Guidance and access control systems will detect a person using a motion sensor which in turn operates the system to identify the person and provides the required information through an LCD screen. The health and safety monitoring system using the Pi camera will identify people who are not wearing face masks and thus trigger an alert to those concerned. Along the way, it will also turn on/off the stepper motor system to open/close doors or gates, or display information messages.”