Exploring IoT and Machine Learning Integration for Soil Nutrients Monitoring and Crop Recommendation: A Survey

The integration of Internet of Things (IoT) and machine learning (ML) technology has the capacity to transform agriculture via the improvement of precision agricultural methods. This survey paper explores the integration of IoT and ML in the field of soil nutrient monitoring and crop recommendation systems. In the context of crop recommendation systems and soil nutrient monitoring, this paper explores the integration of IoT and ML. Its goal is to provide a thorough overview of the most recent developments, applications, challenges, and potential future directions. IoT sensors collect and give immediate soil health information, while ML algorithms analyses this data to suggest nutrient deficits and recommend the most suitable crops. The paper reviews the progress made in sensor technology and machine learning applications, highlighting the advantages they provide to precision farming. This integration promises to enhance agricultural productivity and sustainability through datadriven decision-making and resource optimization. At the end research gaps are discussed, along with future research directions.