The project aimed to develop an intuitively designed application named AutoMate which caters specifically to drivers navigating Manhattan.

By harnessing historical data and leveraging advanced machine learning models, the application anticipates congestion levels across distinct zones within Manhattan. This predictive insight is then amalgamated to provide users with an informed projection of the anticipated occupancy at various parking facilities through a user-friendly interface. The application is developed from the ground up using cutting-edge technology stack across all facets of its development.

The AutoMate application’s comprehensive technology stack is depicted in the following picture. The front-end is built upon the React framework, while the backend employs the Spring framework in Java. We’ve opted for the relational PostgreSQL database. Maven serves as our unified project management tool for both front-end and backend, culminating in deployment through Docker.