IoT and Machine Learning in Agriculture: A Comparative Review of Smart Farming Solutions

Smart agriculture utilizes IoT and ML technologies to revolutionize traditional farming practices. IoT sensors collect real-time environmental data, which ML algorithms analyze for tasks like soil classification, crop yield prediction, and disease detection. Various ML techniques, including deep learning models, are employed to improve accuracy and efficiency of the system. Applications range from automated livestock monitoring to efficient water management. Hybrid models combining different ML approaches often achieve superior results. Smart agriculture shows great potential for enhancing crop yields, reducing waste, and promoting sustainable practices to address global food security concerns.