IoT and Data Analytics for Resource Efficiency and Crop Productivity in Smallholder Agriculture

This research presents the design, development and evaluation of a cost-effective IoT-enabled smart agriculture system tailored to the needs of smallholder farmers in Butaleja District, Uganda. Addressing challenges such as limited resources, reliance on traditional practices and climate vulnerability, the system integrates low-cost sensors, offline edge and cloud analytics and SMS-based feedback to support irrigation and enhance decision-making in low-connectivity settings. Grounded in the Design Science Research (DSR) methodology, the study applies theories including Technology Acceptance Model (TAM), Diffusion of Innovations (DoI), Resource-Based View (RBV), Frugal Innovation, Socio-Technical Systems and Institutional Theory to ensure relevance, usability and scalability. Simulation results showed 99.83% accuracy in irrigation prediction with real-time insights and SMS alerts proving effective for farmers with minimal technical expertise. The system offers a replicable and sustainable solution for transforming agriculture in resource-constrained environments, with future work focusing on scalability, socio-economic impact assessment and integration of renewable energy solutions.