From Pixels to Payouts -A Satellite Based Solution

The Pradhan Mantri Fasal Bima Yojana (PMFBY) stands as a crucial initiative for farmers’ protection, yet grapples with challenges like delayed claims, inaccurate loss assessments, and uneven aid distribution [1]. This project proposes an innovative solution that addresses these issues by introducing a precision agriculture and risk management framework. The current crop insurance policies rely on an area-based approach and limited weather indices, resulting in an inadequate assessment of individual crop health and losses [2]. This shortfall leads to unjust aid distribution, leaving deserving farmers underserved [3]. The proposed solution advocates for a paradigm shift, incorporating a personalized and technology-driven approach. By integrating remote sensing technology, machine learning algorithms, and comprehensive data analysis, the system optimizes insurance resource allocation, assessing crop and regional risk profiles with precision. Furthermore, the project implements advanced image processing, segmentation, and machine learning models, such as SVM and CNN, for crop detection and yield estimation. The Google Maps API enhances decision support through geo-mapping, providing a transparent and data-driven basis for aid distribution. This innovative approach fosters equity, transparency, and active farmer participation, overcoming the limitations of existing methodologies. With a focus on precision, transparency, and equity, the proposed solution aims to revolutionize the effectiveness of PMFBY, ensuring accurate assessment and targeted aid distribution for farmers facing crop stress and losses.