International Journal of BIM and Engineering Science IJBES 2571-1075 10.54216/IJBES https://www.americaspg.com/journals/show/3334 2021 2021 Associate Professor, Department of Electrical and Electronics Engineering KIT-Kalaignarkarunanidhi Institute of Technology, Coimbatore, India K. K. Senior Manager, TVR Consulting Services Private Limited Gajularamaram, Medchal Malkangiri district, Hyderabad - 500055, Telegana, India Tatiraju V. Rajani Kanth Professor, Dept of ECE, Meenakshi Sundararajan Engineering College, Kodambakkam Chennai, India A. Babiyola Artificial Intelligence and Machine Learning, Sagar Institute of Research & Technology, Bhopal, India Haritima Mishra Smart agriculture leverages Internet of Things (IoT) technology to improve crop yield, resource efficiency, and environmental sustainability. This study presents an IoT-based smart agricultural monitoring system that integrates Wireless Sensor Networks (WSNs) with predictive analytics to monitor key environmental parameters, such as soil moisture, temperature, humidity, and light intensity, in real-time. The system utilizes WSNs to gather data from distributed sensor nodes and employs machine learning models for predictive analytics, enabling proactive decision-making for optimized irrigation, fertilization, and pest control. Experimental results demonstrate that the proposed system enhances resource usage by 40% and increases crop yield by 30% compared to traditional farming methods with Artificial Intelligence (AI). Additionally, the predictive analytics component achieves an accuracy of 92% in forecasting environmental conditions, aiding in timely interventions and minimizing crop stress. This IoT-based solution supports sustainable farming practices and offers scalability for various agricultural applications, including precision farming and greenhouse monitoring. 2025 2025 26 34 10.54216/IJBES.100104 https://www.americaspg.com/articleinfo/22/show/3334