Design and Implementation of a Real-Time Geolocation Tracking System Using AI

The geolocation tracking system would be a Wi-Fi based system that proposes to find professors within a university campus in real-time. The system employs the Wi-Fi triangulation and signal strength estimation used to estimate the positions indoors with the use of existing Wi-Fi access points. The system uses the values of the Received Signal Strength Indicator (RSSI) to compute precise location values in buildings with more than one storey. Machine learning algorithms are used to enhance the precision of positioning and forecast the movement patterns using the past data. The solution proposed does not require GPS or Bluetooth and, therefore, is inexpensive and can be installed easily with the existing campus systems. The system monitors attendance automation and improves security of the campuses with realtime tracking systems. A server-client design is adopted to process, store and visualize the location data effectively. Encryption, anonymization, and controlled access are the means to ensure data privacy. The techniques used in performance optimization are used to manage performance variations and interference. In general, the system offers a scalable, secure, and efficient smart campus tracking system with Wi-Fi.Keywords— Wi-Fi Triangulation, Indoor Positioning System (IPS), Geolocation Tracking, Machine Learning, RSSI (Received Signal Strength Indicator),Smart Campus, Attendance Automation, Movement Prediction, Data Privacy and Security.