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@article{182174,
        author = {Guruprasanna J K and Raksha K},
        title = {Nilayasutram An Advanced Approach for Gruha Vastu},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {2},
        pages = {1263-1266},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=182174},
        abstract = {This project introduces an intelligent Vastu Compliance Analyzer that modernizes traditional Vastu Shastra analysis through data-driven techniques. Using advanced processing image, optical character recognition (OCR), and machine learning, the system evaluates architectural floor plans for Vastu compliance. Uploaded plans are processed with OpenCV and Tesseract OCR to extract spatial and textual information, which is analyzed by a pre-trained model. Implemented in libraries of Python like pandas and scikit-learn, the system provides automated predictions, annotated visualizations via a Tkinter interface, and generates a detailed compliance report with corrective suggestions. By combining compass detection, 3x3 zoning, and room classification, the analyzer enhances accuracy and accessibility, bridging ancient principles with modern AI technology.},
        keywords = {AI in Architecture, Floor Plan Analysis, Machine Learning, OCR, Vastu Compliance.},
        month = {July},
        }