Harnessing IoT and Data Analytics to Enhance Resource Efficiency and Crop Productivity in Smallholder Agriculture

This research focused on the development of a cost-effective IoT-enabled smart agriculture system meant to address the specific challenges that smallholder farmers are facing in Butaleja District (Uganda). The challenges included limited resources, dependence on traditional farming methods and vulnerability to climate change. The proposed system integrated low-cost IoT sensors to monitor critical environmental parameters such as soil moisture, temperature and weather conditions combined with cloud-based and offline edge analytics. It further provided real-time actionable insights to farmers via SMS (Short Message Service) and user-friendly platforms enabling improved irrigation management, optimized resource usage and enhanced crop productivity. Usability was prioritized through designing the system with the ability to operate in low-connectivity environments and ensuring ease of usage for farmers with minimal technical expertise. The system’s design and functionality were validated through the execution of multiple simulations proving its ability to accurately monitor environmental parameters, predict when irrigation is to happen using a machine learning model ensuring efficient irrigation management. The simulation also highlighted the effectiveness of integrating SMS notifications and real-time analytics, ensuring accessibility for farmers with minimal technological expertise. By addressing the unique needs of smallholder farmers, the study offers a scalable, sustainable and impactful solution for transforming agriculture in resource-constrained regions with potential applications beyond Uganda. Future work is intended to explore scaling the system to diverse agricultural contexts, assessing its socio-economic impacts and integrating renewable energy solutions to enhance sustainability.