Modern campuses generate massive ecological footprints but lack real-time, actionable data for students and administrators to intervene effectively. Inspired by Georgia Tech's commitment to sustainability, we engineered Campus GreenSpace AI to bridge the gap between abstract climate goals and daily campus life. What it does Campus GreenSpace AI is an intelligent ecosystem that unifies campus environmental metrics. It utilizes edge AI and computer vision to track real-time carbon footprints, monitor green infrastructure, and gamify sustainability, empowering students to become active stewards of their environment. How we built it Built on a scalable microservices architecture, leveraging computer vision models for environmental monitoring, integrated with campus IoT sensors via secure APIs, and deployed on cloud infrastructure for high availability and low latency analytics. Challenges we ran into Integrating disparate IoT sensors and processing high-volume visual data without latency. We overcame this by implementing edge-computing filtering algorithms and optimized data pipelines ensuring smooth real-time tracking. Accomplishments we're proud of Achieving seamless real-time carbon tracking and fostering a highly engaged student community dedicated to measurable campus sustainability improvements. What's next Expanding predictive modeling for campus energy consumption and integrating augmented reality for interactive ecological education across the grounds.
Built With
- ai
- analytics
- api
- automation
- cloud
- computer-vision
- data-science
- education
- environment
- gamification
- green-tech
- iot
- machine-learning
- mobile-app
- monitoring
- python
- react-native
- real-time
- smart-campus
- sustainability
- tensorflow
- typescript
- urban-planning
- user-engagement
