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@article{195690,
        author = {GAYATHRI T and MANIMEGALA M and DEVA HARSAR M M and HANS ROHIT Y},
        title = {AI-POWERED FRA ATLAS & WEBGIS DECISION SUPPORT SYSTEM},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {11},
        pages = {1649-1655},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=195690},
        abstract = {The Forest Rights Act (FRA), 2006 aims to recognize and secure the rights of forest-dwelling communities; however, its implementation is hindered by fragmented and non-digitized records, lack of spatial data integration, and absence of a centralized monitoring mechanism. This project proposes an AI-powered FRA Atlas integrated with a WebGIS-based Decision Support System (DSS) to address these challenges. The system digitizes and standardizes FRA records such as Individual Forest Rights (IFR), Community Rights (CR), and Community Forest Resource (CFR) using text extraction and Named Entity Recognition (NER). It further employs remote sensing and machine learning techniques to map key assets like agricultural land, forest cover, water bodies, and settlements. The WebGIS platform enables multi-layered visualization and tracking of FRA implementation across different administrative levels, while the DSS recommends suitable government schemes by linking beneficiaries with Central Sector Schemes. Overall, the system enhances transparency, improves accessibility to data, and supports informed, data-driven decision-making for effective FRA implementation and sustainable development.},
        keywords = {Forest Rights Act (FRA), WebGIS, Decision Support System (DSS), Artificial Intelligence (AI), Remote Sensing, Machine Learning, NER, Spatial Data Integration, Asset Mapping.},
        month = {April},
        }