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Stream/Area:
-
Subject:
-
Paper ID:
10.55041/IJSREM38229
Volume:
8 |
10 |
Oct 2024
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
– 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.
KEYWORDS
Publication Date
10/26/2024
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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The authors declare no conflict of interest related to this research work.
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