(untitled) (International Journal of Food and Nutritional Sciences, 2022)
Real-time crop monitoring and management have been made possible by the fusion of Internet of Things (IoT) and Machine Learning (ML) technologies, ushering in a revolutionary era in agriculture. The important conclusions and trends discussed in recent research publications and studies on this subject are briefly summarized in this abstract. IoT sensors that have been carefully placed in farming areas continually gather information on critical factors including soil moisture, temperature, humidity, and plant health. Rapidly identifying and categorizing agricultural diseases based on visual data has been shown to be successful using machine learning, especially deep learning approaches. Predictive modeling also makes use of past and current data to anticipate crop yields with accuracy, enabling efficient resource allocation and planning of the harvest. IoT and ML-powered smart irrigation systems provide effective water management, lowering water use while maintaining crop health. In order to control weeds and pests while using the fewest amount of pesticides possible, drones with sensors and machine learning algorithms are essential. Using IoT data analysis to enhance equipment performance, energy-efficient agricultural techniques lessen their effect on the environment and save money. Sensitive agricultural data is protected by data security and privacy protections, including secure data transfer methods and access limits. Despite continuing difficulties, research is being done to address issues including installation costs, farmer training, and standardization of IoT protocols. Future approaches include building energy-efficient IoT devices, strengthening the interpretability of ML models, and increasing data accuracy. Finally, IoT and ML are transforming crop management by bringing data-driven accuracy, sustainability, and resource efficiency to the agricultural sector. This abstract illustrates the potential advantages and difficulties in this quickly developing subject, with IoT and ML positioned to influence farming’s future for both environmental sustainability and food security.