A Multifunctional Mobile Application for Enhancing Paddy Farming Efficiency

Abstract

Paddy farming remains a cornerstone of Sri Lanka’s agricultural economy, yet productivity is often limited by inefficient resource use and dependence on traditional farming practices. This study presents a multifunctional mobile application designed to enhance paddy farming efficiency through intelligent monitoring, crop management, and decision support. The proposed system integrates modules for pest identification, irrigation scheduling, fertilizer recommendation, and market price forecasting. Using adaptive learning algorithms, the application analyses user behavior and environmental data to deliver personalized suggestions. Experimental evaluation demonstrates improvements in accuracy and timeliness of decision-making, leading to more sustainable and productive farming practices.