OCR-based framework for calculating the ROI of residential solar energy installations

• DOI: https://doi.org/10.22533/at.ed.31742624011110

• Palavras-chave: ROI; Solar Energy; Residential Installation; OCR; ReturnOnInvestment

• Keywords: ROI; Solar Energy; Residential Installation; OCR; ReturnOnInvestment

• Abstract:

  This project proposes the development of a framework based on Optical Character Recognition (OCR) to calculate the Return on Investment (ROI) of residential solar energy installations. The importance of such a system stems from the growing adoption of renewable energy solutions in homes, aimed not only at environmental sustainability, but also at economic efficiency. In this context, the calculation of ROI emerges as a critical factor in assessing the viability and performance of solar energy investments. The core of this project is the combination of advanced image processing and machine learning techniques. This dual approach makes it possible to automate the collection and analysis of the data needed to calculate ROI, overcoming traditional methods that are often manual, time-consuming and prone to errors, because through OCR, the system is able to extract relevant information from documents and images, such as energy bills. This data, once scanned and processed, provides a solid basis for subsequent analysis. The next stage involves the use of machine learning algorithms, which are trained to interpret the extracted data and perform ROI-related calculations.