Revolutionizing Agriculture: A Comprehensive Evaluation of Smart Farming Systems and Crop Management through IoT and Machine Learning

Abstract

Smart farming systems, which use cutting-edge technology like the Internet of Things (IoT) and machine learning (ML), have completely transformed agricultural methods and crop management. This review paper assesses the present condition of intelligent agriculture systems, with a particular emphasis on recent advancements and uses of Internet of Things (IoT) and Machine Learning (ML). We do a thorough examination of the most recent scholarly works, pinpoint areas where further research is needed, and analyze the consequences of these technologies on the long-term viability of agriculture. The study emphasizes the efficacy of Internet of Things (IoT) in monitoring agricultural activities in real-time and achieving precise farming. Additionally, it demonstrates the predictive capabilities of Machine Learning (ML) in optimizing various agricultural operations. Notwithstanding the progress made, there are still obstacles to overcome in the form of data standards, economic feasibility, scalability, and user acceptance. This review seeks to thoroughly analyze these difficulties and suggest future research areas to improve the acceptance and effectiveness of smart farming systems. Data from multiple studies, tables, and flowcharts are employed to demonstrate the findings and bolster the conversation, offering a comprehensive foundation for comprehending the incorporation of IoT and ML in agriculture.