A company wants to develop an indoor localization system that can track the location of people and assets within a building using Wi-Fi signals. They have installed Wi-Fi access points throughout the building and have collected a dataset of Wi-Fi signal strength measurements at various locations within the building.
The challenge is to build a machine learning model that can accurately predict the location of a person or asset based on the Wi-Fi signal strength measurements.
This project uses the power of numerous access points to precisely locate WiFi-enabled devices within indoor spaces. It employs advanced algorithms to analyse the signals emitted by WiFi devices and triangulate their location using data gathered from multiple access points. The system can identify the location of devices in real-time by combining signal strength and time-of-flight calculations. It provides a dependable and cost-effective option for asset tracking, Localize navigation, or security, and is a valuable asset for companies, organizations, and individuals.
