Oftentimes our friends and family spend numerous hours on roads due to traffic, hence this inspired us to create a solution that solves the traffic management problem in our country. With DCongest we solve it by decreasing waiting hours at intersections with the help of our smart IoT device and recommend the users' best route and time to encounter the least amount of traffic on their way.

What it does

Our solution has two parts:

1. The IoT device: The IoT solution is a dynamic traffic light device that allows for us to change the state of the traffic light according to the data collected by the web application by which we can understand the number of cars on each lane and give priority to the lane with the most cars while keeping in mind the final destination to make the flow of traffic smooth and reduce the wait times at each intersection.

2. The web application: Integration of public and private transport applications, Bus Routes Recommendation, Time recommendation, Route recommendation, Connectivity Index of the areas, and Traffic official support system.

How we built it

We have built the web application using the latest tech stack and technologies based on the MVN model. We have used HTML, CSS, EJS for the frontend, MongoDB as the database, Node.js, and express.js for the backend. Whereas the implementation of IoT device was done on an online platform Tinkercad with the help of the Arduino manual to figure out the cache storage of the microprocessors.

Challenges we ran into

Throughout this project, we’ve run into several issues such as collecting user data and acquiring data for public transportation, along with the complete integration of the system of the Web application and the Public Transport Authority Portal. There were also minor challenges faced during the building of the Arduino solution, writing the algorithm for the traffic light solution was the most challenging part of the IoT solution. In this part, I was faced with handling the overloading of the microprocessor by the code.

Accomplishments that we're proud of

One thing that we are extremely proud of is that we were able to solve a real-life problem with the help of the skillsets we've developed overtime.

What we learned

Anshum Shailey: Working on both the front end and backend helped me learn better how the overall integration works, and how to use the data accumulated in a way to benefit the users.

Parth Chadha: I was able to broaden my UX/UI design approach by conducting more user research and defining the users of this app. This also helped build additional stages to the iteration process that gave us the polished and open interface in our final designs.

Ronith Nair: Learnt the nuances of Arduino and handling the overloading of the microprocessor. Besides this was challenged with creating a situational-based algorithm that improved proficiency in writing C code.

What's next for DCongest

The DCongest team will continue pushing work by creating a better IoT device with the help of Machine Learning, use crowdsourced data for the unregistered parking spots in the city, leaderboard system so that more people use our application and collaboration with the government which would expand the reach of our web app and the IoT device.

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