The idea is to give awareness to the public in a convenient way, which educates them to reduce carbon footprint. The realization of each point counts is the key, and quantifying day to day data makes this easy by showing the impact. The platform agnostic way of implementation increases the reach of the application, which ultimately helps deliver better results.
Carbon footprint is very important but less understood concept. Our aim is to educate people on the importance of reducing carbon footprint to make the world a better place. We used Google's DialogFlow platform to build a conversational AI. We chose this technology because it support wide variety of platforms and it's advanced AI capabilities. We also made use of Google Cloud Functions for our backend system and utilized NodeJS for coding it. We chose this stack because of it's scalability and extendibility. We ran across various problems related to conversational flow building. We did extensive research to sort them out. Another challenge was to derive formulas to calculate carbon footprints. Resources from NASA also helped us materializing the idea.
The first resource we made use of is the video on "Virtual Bootcamp Video/Introduction: What Is Our Carbon Footprint?" (https://www.youtube.com/watch?v=uwTV8TQJadY) which served as the backbone of our ideation phase. Then we looked in data sources ODIAC Fossil Fuel Emissions and DARTE US Traffic Emissions, which served as the base for the formulas we used for carbon footprint calculation. https://climate.nasa.gov/causes/ gave us more information on causes, which also helped us creating our prototype.

Demo Video Link : https://youtu.be/IJjM5-nx7e8
Demo Project Link: https://bot.dialogflow.com/7ce0e96d-5ed2-4d91-8b26-15d98f69759b