Abstract: The developed system, “Nurturing Plant with Smart Water and AI Care for Sustainable Growth,” introduces a lightweight smart-agriculture framework that integrates IoT sensors and AI-based intelligence for real-time plant monitoring and automated care. Soil moisture, temperature, humidity, and water level are continuously measured using embedded sensors to provide precise environmental insights. A predictive machine learning-based irrigation mechanism analyzes current readings and historical patterns to supply the optimal amount of water, preventing both over-irrigation and water stress. In parallel, an AI image-processing module identifies plant diseases and nutrient deficiencies at an early stage, enabling timely intervention and reducing crop losses. The combined automation significantly minimizes manual effort, enhances water efficiency, and supports sustainable plant growth. With its modular and scalable design, the system is suitable for home gardening, greenhouse setups, and large-scale agricultural environments, demonstrating how IoT and AI can together improve plant health and resource management.

Keywords: Smart Agriculture, IoT, Artificial Intelligence, Deep Learning, YOLOv8, Leaf Disease Detection, Soil Monitoring, Smart Irrigation, ESP8266, RS485, Predictive Water Management, Real-Time Monitoring, Sustainable Farming, Machine Learning, Web Interface, Precision Agriculture, NPK Sensor, Automation System, Plant Health Analysis.

Downloads: | DOI: 10.17148/IARJSET.2025.121206