Eco-AI Energy Tracker

Empowering schools to monitor and reduce energy consumption with AI insights.

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Inspiration

Schools often struggle to monitor their energy usage, leading to wasted electricity and higher costs. We wanted to create a solution that empowers schools to make data-driven decisions to reduce energy waste, lower bills, and promote sustainability among students.

What it does

Monitors energy usage in real-time using IoT sensors. Uses AI to predict future energy consumption and detect spikes. Displays actionable insights and reports on a user-friendly dashboard. Sends alerts when energy usage exceeds expected levels. Allows schools to set sustainability goals and track progress.

How we built it

Frontend: React + Tailwind CSS for a responsive, modern UI. Backend: Node.js + Express.js to handle API requests and manage data. Database: Firebase (or MongoDB) for storing energy data and user settings. AI/ML: Python + TensorFlow to forecast energy usage and provide predictions. Deployment: Vite + Netlify/Vercel for live demo hosting. Optional Hardware: IoT sensors (e.g., smart plugs) to collect real-time energy data.

Challenges we ran into

Integrating real-time IoT sensor data with the backend. Designing AI models that provide accurate energy predictions with limited historical data. Creating a dashboard interface that is intuitive for school staff. Ensuring the app is scalable and works across multiple devices.

Accomplishments that we're proud of

Built a fully functional dashboard that visualises energy data. Implemented AI predictions to identify patterns and forecast usage. Created a scalable architecture that can handle multiple schools or buildings. Developed a mobile-friendly interface using Tailwind CSS. Made the project hackathon-ready with zero errors in React + TypeScript.

What we learned

How to integrate AI/ML models with a React frontend. Best practices for handling real-time data in web applications. How to design user-friendly dashboards that communicate complex data clearly. Collaboration techniques for combining hardware, software, and AI effectively.

What's next for Eco-AI Energy Tracker

Add mobile app support for remote monitoring. Expand AI models for advanced energy optimisation. Introduce gamification features to encourage students to adopt energy-saving habits. Add exportable reports and analytics for school boards. Explore integration with solar panels or renewable energy systems.

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