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 thecapacity 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 nutrientmonitoring and crop recommendation systems. In the context of crop recommendationsystems and soil nutrient monitoring, this paper explores the integration of IoT and ML. Itsgoal is to provide a thorough overview of the most recent developments, applications,challenges, and potential future directions. IoT sensors collect and give immediate soilhealth information, while ML algorithms analyses this data to suggest nutrient deficits andrecommend the most suitable crops. The paper reviews the progress made in sensortechnology and machine learning applications, highlighting the advantages they provide toprecision farming. This integration promises to enhance agricultural productivity andsustainability through datadriven decision-making and resource optimization. At the endresearch gaps are discussed, along with future research directions.