Our team has come up with an idea which we have named as Clibomate. We are using Internet of things, Machine Learning, AWS and a website. we are using various IoT gas sensors in a box controlled by ESP32. The device will be fitted to local goverment vehicles. Wherever the vehicles goes it will collect the ground data of green house gas emission and will send it to SDE's, WHO and environmental agencies using AWS to keep tract of the area that emitts more pollution. But our main motive is to put this device on Government vehicles which covers several places in a day around a particular region which help us to get the real-time data of greenhouse gases according to the locations in various time slots. 

Now, the question arises that what can we do with this data or how can we utilize it. So, we are going to provide this data to the NGOs, WHO and other welfare groups who are willingly seeking the opportunity to save our precious gift of nature for the future generation. This data from us will help them to customize their service according to the graph represented by our ML Algorithm, which highlights those areas crossing some particular threshold values and need to perform required actions.

Also, we are building a website which draws attention or aware people regarding the drawbacks they are going to face for ignoring our beautiful nature. Carbon Dioxide is the main reason for the greenhouse effect. That's why we include all the latest stats with graph and images, also have the carbon footprint calculator. This calculator helps one to calculate their carbon footprint which tells them about their emission of carbon per day, which enables you to take some initial steps to adapt to a changing world and creating a more resilient business. Besides, we are providing them with our policy, solution and measure, which they can follow to control the emission of carbon per day.

Statistics which we include in our website is in a predicted form. We have taken the dataset for the emission of carbon since the past 10 years. We had performed our ML model on that data to predict the rate of carbon emission for the future and made a graphical representation of that. That prediction in the form of graph helps our user to understand how disastrous this ignorance can lead to our future.

We have also proposed a policy to reduce Green House Gases.

check here: https://drive.google.com/file/d/1LfTp-7W1oIrvRi65dsFNx9WVSRPrbKov/view?usp=drive_web