Sustaining Our Planet for Future Generations
Online PUC Certificate
Summary
The project aims to build an application that will help in sustainable development. We will build an application using machine learning that will predict the Carbon monoxide and Hydrocarbon emission of the vehicle on providing specific details about the vehicle such as on which fuel it runs petrol or diesel, when was the last time the vehicle engine was greased and cleaned, engine model of the vehicle BS4 or BS6 or any other model. On the basis of this calculation, it will be determined that whether the pollution emitted by the vehicle is under the standards set by the Government of India or not. It will help in issuing the PUC certificates online.
How I Addressed This Challenge
We developed an application that determines on the basis of the input given that whether the pollution emitted by the vehicle is under the limit set the by the government or more and on this basis it provides the PUC certificate.
It is important because as per the present scenario the government wants to digitalize the entire procedure and they have taken a step forward by allowing E copy of the driving license and registration of the vehicle but still no option is available for PUC certificate. People have to stand in long queues to get their PUC certificate renewed. At the same time a considerable amount of fuel is used to just calculate the pollutant level emitted by the vehicle.
It uses random forest regression model in machine learning to calculate the level of pollutant emitted by the vehicle on the basis of the input provided by the user such as fuel type of the vehicle, year of manufacturing of the vehicle and others.
We hope to build an excellent model based on Indian vehicles and Indian usage so that it can provide an accurate data and so that the physical need of each time going to a pollution checking station is reduced.
How I Developed This Project
We were inspired to build this project after getting to know about government step towards digitalization of documents like driving license. We came to know that a considerable amount of fuel is used to just calculate the pollutant level emitted by the vehicle.
We tried to build a machine learning model that automatically calculates the CO2 emission of a vehicle based on the data provided to the model.
We used Python, Flask, HTML, CSS to build the frontend and backend of our application.
We were able to build a model with an accuracy rate of 99% with the Canadian data. The problem that we faced was that we could not build a model for India as we could not get Indian data to train our model.
How I Used Space Agency Data in This Project
It was used to make our machine learning model more accurate. We tried different regression models on it.