Smart Agriculture System Using Internet of Things

Abstract: The Internet of Things (IoT) has emerged as a transformative technology for modernizing traditional agricultural practices into smart, data-driven systems. This paper presents a comprehensive review of Smart Agriculture Systems (SAS) leveraging IoT technologies to enhance crop productivity, optimize resource utilization, and enable real- time field monitoring. The proposed architecture integrates heterogeneous IoT sensors including soil moisture sensors, temperature and humidity sensors, pH sensors, and light intensity sensors with cloud computing platforms and machine learning algorithms to provide actionable insights for farmers. Key components such as automated irrigation, crop disease detection, livestock monitoring, and weather-based advisory systems are systematically analyzed. The paper evaluates communication protocols including MQTT, LoRaWAN, Zigbee, and Wi-Fi for agricultural deployments, assessing their suitability based on range, power consumption, and data rate. Experimental results from pilot deployments demonstrate up to 35% reduction in water consumption, 28% improvement in crop yield, and significant reduction in manual labor through automation. Challenges including connectivity in rural areas, interoperability, data security, and high deployment costs are discussed along with mitigation strategies. The paper concludes by examining future directions in AI-integrated smart farming, edge computing, drone-assisted monitoring, and the role of blockchain for supply chain transparency in precision agriculture.

Keywords: Internet of Things (IoT), Smart Agriculture, Precision Farming, Automated Irrigation, Soil Monitoring, Crop Disease Detection, MQTT, LoRaWAN, Edge Computing, Precision Agriculture.