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Research Paper | Information Technology | India | Volume 13 Issue 2, February 2024

Enhancing Agricultural Forecasting in India through Drone - Based Image Processing: A Future Perspective on Food Supply Chain Management

Kunal Dhanda ^[4] | Sweta Sehrawat ^[4]

Abstract: This paper investigates the potential of drone - based image processing technology to revolutionize agricultural forecasting in India. With the agricultural sector facing numerous challenges in predicting food supply and market timings, this study introduces a novel approach that combines advanced drone technology with sophisticated image processing algorithms. The research aims to explore how this integration can provide accurate, real - time insights into crop stages, health, and yield estimations across various regions in India. The expected outcomes include a significant improvement in forecasting harvest times and quantities, thereby enhancing the efficiency of the food supply chain and aiding in better market planning. By analyzing data collected from drone surveys across diverse agricultural landscapes in India, this paper seeks to demonstrate the effectiveness of this technology in estimating crop yields based on field size and crop stage. Ultimately, this study aims to contribute to the advancement of agricultural practices in India, promoting food security and supporting the nation's growing demands in a sustainable manner.

Keywords: drone - based image processing, agricultural forecasting, crop yield estimation, market planning efficiency, food security

Edition: Volume 13 Issue 2, February 2024,

Pages: 260 - 262