ICESeeYou

Inspiration

Our project was inspired by the urgent need for real-time, reliable information on ICE enforcement activities impacting immigrant communities. Many existing reporting systems lack verification mechanisms, leading to misinformation and fear. We aimed to create a trustworthy, community-driven platform that not only collects ICE sighting reports but also leverages generative AI to assess their credibility.

What it does

The goal is to inform immigrants about recent ICE sightings using user-inputted information to formulate a heat map of past ICE sightings. Users report ICE sightings through the website form and generative AI filters the entries to ensure each addition to the heat map is credible and accurate. We use the data collected from past entries to predict future hotspots for ICE sightings to ensure immigrant protection and create a safer, more aware community.

How we built it

Frontend/backend: We used Next.js and React to develop an intuitive, responsive UI for submitting reports and viewing the heat map. Database: We implemented a Supabase database to store user reports and structured metadata. AI Integration: We utilized generative AI models to analyze and validate ICE sighting reports, flagging potential inconsistencies.

Work in Progress:

The validated data is displayed on an interactive heat map using Google Maps API for easy navigation.
Prediction of future ICE encounters using generative AI to analyze patterns in previous data.

Challenges we ran into

-Lack of known data: we started off with limited reports of ICE sightings so we generated supplemental data to improve accuracy when testing the validity of the data entries using the generative AI filter. -Learning how to use Supabase and working with it throughout the process.

Accomplishments that we're proud of

We created a useful and functional tool to help immigrants stay informed and generate greater awareness towards the scope of ICE sightings in Massachusetts.