(untitled) (Physical Education, Health and Social Sciences, 2026)
Precision agriculture (PA) and Internet of Things (IoT)-based smart irrigation represent transformative technologies for optimizing greenhouse vegetable production, addressing global challenges like population growth (projected 9.7 billion by 2050), water scarcity, and climate variability. This review synthesizes the integration of IoT sensors (soil moisture, EC, pH, microclimate monitors) with data analytics (AI/ML models) and automated actuators for real-time resource management in crops such as tomatoes, cucumbers, and peppers. Key components include wireless sensor networks (WSNs) using protocols like ZigBee/LoRa for data transmission, edge/fog computing for low-latency processing, and predictive algorithms (e.g., LSTM, SVM) that reduce water use by 20–50% while enhancing yield (10–30%) and nutrient efficiency. Case studies from China, Europe, and India demonstrate practical implementations, such as variable rate irrigation (VRI) and fertigation systems, achieving up to 40% energy savings and minimized leaching. Challenges encompass high initial costs, data security, and sensor accuracy in humid environments, with future directions emphasizing AI-driven digital twins, blockchain for traceability, and hybrid renewable energy integration for sustainable, resilient greenhouse systems.