Global Green Screen

Inspiration

Urban communities near roadways experience significantly higher exposure to PM2.5, minute particulate matter difficult to remove from the air, and linked to respiratory and cardiovascular disease. Cities increasingly install vegetative roadside barriers, but there is no standardized, accessible system to measure the real-world effectiveness of these “green screens.” We were inspired by a simple question: Are green infrastructure projects actually reducing pollution exposure where people breathe? Global Green Screen was built to transform student-led environmental curiosity into a structured, data-driven environmental intelligence platform.

What it does

Global Green Screen is a mobile-first urban air intelligence platform that allows users to: Record paired PM2.5 measurements (roadside vs barrier-side) Automatically calculate pollution reduction percentage Capture contextual data (plant species, barrier type, weather) Upload photo evidence Generate a live confidence score for research integrity Visualize submissions on a color-coded global map Aggregate insights across locations and barrier types The platform transforms distributed data collection into actionable insights about green infrastructure performance.

How we built it

Frontend: React-based, mobile-responsive interface Geospatial Layer: Interactive map with dynamic pin rendering Analytics Engine: Real-time pollution reduction calculation Confidence Scoring System: Algorithm based on measurement completeness and protocol consistency Insight Engine: Aggregates and summarizes trends across submissions Data Layer: Structured dataset supporting scalable expansion We focused on building a smooth end-to-end loop: Submit → Process → Visualize → Analyze.

Challenges we ran into

-Balancing Simplicity with Scientific Rigor We needed the app to be accessible to students while maintaining research credibility. -Designing a Meaningful Confidence Score Creating a scoring system that reflects data integrity without overwhelming users required careful UX decisions. -Preventing Overclaiming We ensured our analytics describe trends without implying causation beyond the collected data. -Keeping the Interface Clean While Managing Complex Data Presenting measurements, metadata, and insights in a mobile-friendly format required multiple design iterations.

Accomplishments that we're proud of

-Building a full measurement-to-visualization pipeline within hackathon constraints -Creating a live data confidence system to improve citizen-science reliability -Designing an insight engine that translates raw PM2.5 data into meaningful summaries -Developing a platform that feels scalable beyond a prototype

What we learned

Data without structure lacks credibility. UX design significantly impacts scientific usability. Even simple environmental measurements require thoughtful protocol design. We also learned that environmental technology must balance optimism with precision.

What's next for Global Green Screen

Next steps include: Expanding the dataset through partnerships with schools and nonprofits Integrating validated live public air quality APIs for contextual comparison Refining the confidence scoring model with expert input Developing advanced analytics and policy recommendations for urban planners and policymakers Exploring predictive modeling for barrier performance under varying conditions Our long-term vision is to build a distributed environmental intelligence network that supports healthier city design worldwide.

Built With

• geminiapi
• googleaistudio
• googlecloudrun
• javascript
• node.js
• react