Drought Prediction for Farmers and Providing a Sustainable Farming Solution using IoT and Machine Learning

Drought is a severe natural event that affects agriculture greatly, particularly in regions where rain-fed agriculture is the main source of food. It has a major detrimental impact on society, the environment, and the lives of farmers. Drought prediction is an important component of early warning systems for drought management. Advances in machine learning (ML) and the Internet of Things (IoT) have demonstrated potential to improve drought prediction and provide sustainable farming solutions. In order to help farmers minimise the effects of drought and implement sustainable agricultural practices, we propose an IoT and ML drought prediction model in this work. We also discuss recommended farming practices that improve crop monitoring, irrigation, and decision-making through the use of IoT and ML technology. Along with outlining the model's limitations, we also provide recommendations for further research. In summary, our study aims to advance the field of drought prediction and sustainable farming practices by using the potential of IoT and ML technology.