The integration of the Internet of Things (IoT) into agriculture is revolutionizing the way food is produced, managed, and distributed. By combining networks of smart sensors, advanced communication protocols, distributed computing, and artificial intelligence (AI), IoT-based smart farming systems allow for precision monitoring and management of agricultural resources. These systems enable farmers to optimize irrigation, monitor crop health, and make real-time, data-driven decisions, thereby addressing challenges such as water scarcity, climate variability, and the growing demand for food. This paper presents an expanded IoT-driven smart agriculture framework with modular architecture, incorporating a perception layer, network layer, compute layer, application layer, and end-user layer. The framework integrates AI-based predictive analytics, blockchain for supply chain transparency, and renewable energy-powered devices. A pilot implementation on a 5-hectare wheat farm demonstrated a 30% reduction in water usage, early disease detection accuracy of 92%, and improved scalability for multi-crop environments. Comparative analysis with conventional farming practices shows significant improvements in resource efficiency and operational sustainability. The paper provides a detailed literature review, system design, experimental methodology, and future research directions, with a focus on interoperability, cost-effectiveness, and sustainability.
Irfan et al. (Sat,) studied this question.