Authors: Bhuran sheikh, Vighnesh Muppawar, Jiya Khan Pathan, Suyog Madavie, Prof. Sachin Dhawas
Abstract: CompThe Pradhan Mantri Awas Yojana (PMAY) is a flagship initiative by the Government of India aimed at providing affordable housing to the rural and urban poor. However, at the local administrative level (Zila Parishad), the management of beneficiary data involves processing massive, decentralized Excel datasets. This manual approach leads to data redundancy, lack of real-time monitoring, and significant difficulty in identifying stalled projects. This paper proposes "Data Driven Housing Intelligence," a web-based analytical application designed to automate and centralize PMAY data management. Developed using the Python Flask framework, the system integrates bulk data ingestion, automated data cleaning using the Pandas library, and persistent storage in a structured SQLite database. It features a multi-level drill-down dashboard with interactive visualizations (Bar and Pie charts) for block-wise analysis. Furthermore, it introduces a "Visual Audit" mechanism allowing stage-wise photo uploads for transparency and an automated algorithm to flag delayed projects. The implementation results demonstrate a significant reduction in administrative overhead and improved data accessibility for government officials.
