Track&go A Location Prediction Web Application

Location prediction is currently gaining attention due to the increasing number of applications in travel, military etc. This work focusses on creating a web application that generates a predictive model that identifies user’s destination, given current location, date and time by the user. We are using K-Means clustering to group the same locations and stores the data. The data is fed into a Random Forest Classifier which predicts the destination. Track&Go app allows the user to plan their travel ahead by providing a route for the destination and facilities near the location and also routes to these locations with the help of Google Maps. The web application itself is created using Django, a python web framework.