Solar Energy Potential Mapping: Integrating Real-Time Meteorological Data and the Segment Anything Model

Solar Energy Potential Mapping: Integrating Real-Time Meteorological Data and the Segment Anything Model

Dr.Ankita V. Karale 1, Nivedita R. Vibhandik 2, Soham A. Kulkarni 3, Khemchandra A. Chaudhari 4, Chetan R. Sonawane 5, Aman A. Mansuri 6

1Head of Department, Computer Department, Sandip Institute of technology and research centre, Nashik, India

2Assistant Professor, Computer Department, Sandip Institute of technology and research centre, Nashik, India

3 4 5 6 Student, Computer Department, Sandip Institute of technology and research centre, Nashik, India

Abstract: - This paper presents an innovative approach to Solar Energy Potential Mapping, utilizing the Segment Anything Model (SAM) for accurate rooftop segmentation from satellite images, combined with real-time meteorological data from the SolarAnywhere API. The project aims to estimate the potential for solar energy generation by identifying and mapping rooftops and other relevant surfaces. SAM's robust image segmentation capabilities enable precise identification of areas suitable for solar panel installations. In conjunction with real-time solar irradiance data, the tool provides a reliable assessment of solar energy potential. The proposed solution offers a user-friendly web application, which integrates machine learning models and real-time data to deliver charts visualizing the solar energy potential. This paper surveys existing methods for solar potential mapping and demonstrates the effectiveness of our approach in optimizing rooftop solar assessments for sustainable energy planning.

Key Words:  Solar Energy, Image Segmentation, Segment Anything Model, SAM, SolarAnywhere API, Rooftop Detection, Satellite Imagery, Solar Potential Mapping, Charts, Machine Learning