Abstract:
Agriculture, as the foundation of human nutrition and economic stability,requires innovative solutions to address challenges such as climate change,resource limitations, and crop diseases. Rice, a staple food for over half of theglobal population, demands alert monitoring to ensure healthy growth andoptimal yields. Traditional manual crop inspections in Pakistan are laborintensive,time- consuming, and often reactive rather than proactive, leading tocrop losses and inefficient resource use. This project introduces an integratedsystem that powers modern technology to enhance rice crop management. Thesystem captures images of rice plants through mobile devices or cameras, whichare then analyzed using machine learning models to detect common diseaseslike leaf blast, bacterial blight, and brown spot. Concurrently, IoT sensorsdeployed in the fields continuously monitor critical environmental parameterssuch as soil nutrients (NPK), moisture, pH, temperature, and humidity,providing real-time data. By producing disease detection results with sensordata, the system offers actionable insights and recommendations for preventivemeasures, enabling farmers to respond promptly and effectively. Thiscomprehensive approach facilitates early disease identification, resourceoptimization, and improved crop health, finally increasing rice productivity. Theproposed solution aims to empower farmers with accessible, data-driven tools topromote manageable agriculture and food security, especially in regions weak toclimatic and resource-related stresses.
Page(s):
129-129
DOI:
DOI not available
Published:
Journal: 4th International Conference of Sciences “Revamped Scientific Outlook of 21st Century, 2025” , November 12,2025, Volume: 1, Issue: 1, Year: 2025
Keywords:
Sustainable agriculture
,
environmental monitoring
,
Crop disease detection
,
IoT sensors
,
rice farming