Sustainable Scholars

Inspiration

Climate change is a rapidly growing problem especially with the growing scale of AI. As engineering and computer science students, we wanted to build a system that helps explain environmental issues clearly, but also model real world systems to explore smarter and data-driven solutions.

What it does

Our simulations showed traffic and provided information on CO2 emissions as well as provide information on civic engagement. Our webpage helps provide users with information on environmental policies and issues.

How we built it

We built this project using Python. We created a webapp using Gemini API. We also created traffic simulations connecting SUMO to Python with TraCI. Then, used streamlit to provide information about CO2 emissions. We used YOLO for computer vision to analyze objects for recycling.

Challenges we ran into

We ran into problems creating simulations using SUMO since it were our first time using it. We also struggled to understand but we persevered and continued to combine our technical experience with the power of AI to build something cool and understand how to make it again in the future by reusing the skills we picked up.

Accomplishments that we're proud of

We were accomplished that we managed to make working simulations despite using new software we haven't used before.

What we learned

We learned abt DQL reinforcement learning, how much CO2 comes from idle cars.

What's next for Sustainable Scholars

To improve our project for the future, we hope to specialize our AI more in order to summarize transcripts scrapped off the internet to keep users up to date on policies, integrate simulations into our websites.