Be The Greener Version of your self
Give a chance for the better future 🚀🚀🚀
☀️ SolarSuitability Smart Rooftop Intelligence & Energy Analytics Empowering homeowners to transition from the Old Grid 🏛️ to New Energy 🌱 using satellite precision.
📍 Precision Pinpointing Using location-based APIs to zoom into your exact coordinates. Our application removes the guesswork by seeing exactly what the sun sees from above. 🛰️
📏 Automated Geometry Our algorithms calculate your roof size, pitch, and orientation automatically. By simply dropping a pin, the system extracts the geometry needed to determine how many panels your home can support. 📐
💰 Grid vs. Solar Stop paying for transmission losses and rising utility rates. We provide a side-by-side analysis comparing your current monthly utility bill against a 25-year solar savings plan. 📉 ➡️ 📈
🌍 Environmental Impact Track your carbon offset in real-time. Our tool translates complex energy data into tangible environmental results, showing you exactly how many trees your rooftop is equivalent to. 🌳🌳🌳
Built with ❤️ for a Greener Planet
The SolarSuitability web application is a high-performance tool designed to bridge the gap between residential consumers and renewable energy adoption. By leveraging advanced geospatial data and satellite imagery analysis, the platform provides users with an immediate, data-driven assessment of their home's solar potential.
The primary objective is to demonstrate that rooftop solar is no longer just an environmental choice but a superior financial and logistical alternative to traditional utility grid lines.
- Chart JS: Provides the interactive map interface for address lookup and location pinning.
- Open AI API The backbone of the application, used to extract solar flux data, rooftop segments, and shading patterns.
- Framework: React.js for a responsive, state-driven user interface.
- Data Visualization: Chart.js to render complex comparisons between grid spending and solar savings.
- Styling: Tailwind CSS for a modern look.
- Environment: Node.js.
- Firebase: Google Firebase used for the data storage for future machine learning preditions and data security purposes.
- Open AI API: Integration with the Open AI API for precise energy production estimates based on local climate data.
The application performs a three-tier analysis:
- Direct Energy Offset: Calculates the kilowatt-hours (kWh) produced by the solar array based on the identified roof size and local irradiance.
- Transmission Efficiency: Demonstrates the energy loss inherent in grid lines (typically 5-10%) vs. the 0% transmission loss of on-site solar.
- Levelized Cost of Energy (LCOE): Compares the locked-in price of solar power (cost of system / total lifetime energy) against the projected rising rates of utility providers.
Future iterations will include a machine learning model using Computer Vision to identify seasonal foliage growth. This will allow the app to predict how a neighbor's growing tree might affect solar efficiency 5 or 10 years into the future.
Integration with EV charging data to show how solar panels can essentially "fuel" a vehicle for free, further increasing the ROI compared to traditional energy and gasoline costs.
A live database connection to federal, state, and local solar rebates (ITC - Investment Tax Credit) to provide a "Net Effective Cost" in real-time.
To run this project locally:
- Clone the repository.
- Run
npm installto fetch dependencies. - Add your
API_KEYSto the.envfile. - Execute
npm run startto launch the development server.
By simplifying the complex math of solar ROI, SolarSuitability empowers homeowners to take control of their energy production, reducing global carbon footprints one rooftop at a time. """
A Geospatial Web Application for Residential Solar Optimization
The SolarSuitability project is a comprehensive web-based platform designed to demystify the transition from traditional grid electricity to rooftop solar energy. In an era of rising energy costs and environmental concerns, this application provides users with an interactive, data-driven interface to evaluate their specific home's solar potential. By integrating high-resolution satellite imagery and advanced geospatial APIs, the project automates the complex process of rooftop measurement, orientation analysis, and financial forecasting.
- Precision Mapping: Utilize geocoding to locate residential properties with high accuracy.
- Rooftop Extraction: Automatically identify usable roof area, accounting for pitch, orientation, and physical obstructions.
- Comparative Analytics: Deliver a side-by-side financial and environmental comparison between utility grid reliance and solar independence.
- Accessibility: Create an intuitive UX that translates technical energy metrics (kWh, Solar Flux, Irradiance) into actionable consumer insights.
The application is built using React.js to manage a highly dynamic state, ensuring that as users adjust their "pin" on the map, data calculations update in real-time. Tailwind CSS is utilized for a clean, professional aesthetic that maintains performance across mobile and desktop devices.
Future versions will incorporate Computer Vision (CV) to detect objects like chimneys, HVAC units, and vents automatically, refining the "Usable Area" calculation without user intervention. Additionally, we aim to integrate Machine Learning to predict energy storage needs based on the user's specific regional cloud-cover patterns.
We plan to add support for Virtual Power Plants (VPP), allowing users to see how much they could earn by selling stored battery energy back to the grid during peak demand hours, turning their home from a "Consumer" into a "Prosumer."