Intelligent Greenhouse Monitoring System Based on Raspberry Pi and Internet of Things Platform

The integration of Internet of Things (IoT) technology and low-cost computing hardware like Raspberry Pi is revolutionizing traditional agricultural practices. This paper presents a comprehensive design, implementation, and evaluation of an intelligent greenhouse monitoring system. The system architecture incorporates a multi-layered sensor network for real-time data acquisition on environmental parameters (temperature, humidity, soil moisture, light intensity, CO2), a Raspberry Pi 4B as the central edge computing unit for data processing and local decision-making, and a cloud-based IoT platform for remote monitoring, data analytics, and long-term storage. Advanced features include multi-mode control (manual/automatic/remote), a two-tier data fusion algorithm for enhanced measurement accuracy, and the preliminary integration of Convolutional Neural Networks (CNNs) for plant disease detection. A three-month field deployment demonstrated a 35% reduction in water consumption through automated irrigation, a 25% decrease in energy usage via optimized climate control, and a 15-20% increase in lettuce yield compared to conventional greenhouse management. Despite challenges in initial setup cost and technical complexity, the system proves to be a scalable, cost-effective, and sustainable solution for precision agriculture, with significant potential for future enhancements in AI and autonomous control.