Sustainable farming and higher agricultural yields may arise from IoT adoption in agriculture. This research creates an IoT-based system to track leaf structures, a key indicator of plant health and growth. The system uses sensors to measure environmental conditions, leaf temperature, moisture, and chlorophyll content. Due to advanced data analytics and machine learning algorithms, the system provides accurate and useful crop health insights. By making smart irrigation, fertilization, and pest management decisions with real-time data, farmers can maximize resource utilization and productivity. This strategy boosts agricultural yield, lowers input costs, and promotes sustainable farming. Empirical results show that accuracy is achieved by up to 98.50%. This article also covers IoT monitoring system design, deployment, and performance evaluation. Technology-driven precision farming could alter modern agriculture with this technique.