This project explores Indoor Localization with Sensor Fusion of PDR (Pedestrian Dead Reckoning) and a Single RTT (Round Trip Time) Wi-Fi with known initial position, the implementation of which deals with IMU measurements, Complementary Filters and Kalman Filters.
It is a project on Indoor Localization without using trilaterization and using as less dependencies as possible ( Range information from 1 AP and 1 IMU ). Since a single range equation would give many solutions the location of the starting point is assumed as known. This can be a valid assumption in many cases.
The aim is also to make a prototype app running on Android which could be used for helping Visually Challenged people navigate their surroundings in a public place.
The problem is to track the Carts in supermarkets so that we can gather information about what consumers are doing the data obtained can then be used in Data Analysis and Machine Learning Models to gather useful information.
Here the problem is to track the location of Visually Impaired person, so that directions can be given to them using a speech assistant when they find themselves in a new location.
For more details on each of these, checkout the main Report and README's in each of the folders.