IoT-Based Smart Agriculture: Real-Time Crop Monitoring and Yield Prediction for Sustainable Farming

In this case Internet of Things (IoT) based smart farming is a revolution sample for modernization of agriculture and made them more sustainable. This research aims at proposing a smart agriculture system that incorporates the IoT in monitoring crops cereals in their real-time yield prediction. Instead, through the network of sensors, cameras, and drones, the system continuously acquires data on soil moisture, temperature, light intensity, and the like. The above data is analyzed through machine learning models in a bid to forecast crop health, rates of growth, and more elaborately, yields. The system also lets farmers keep abreast of their fields, and act quickly if there are unfavorable conditions like pest or diseases, or water constraints. The analyses made concerning irrigation, fertilizer application and pest control are also informed by the predictive analytics model, adopting resource efficiency for maximum returns. The objective of this study will be to provide a proof of concept that IoT enabled solutions can be implemented and will have a positive impact on productivity and sustainability of agriculture. The IoT system gives the farmers timely requirements and the capability of future prognosis, thus enhancing the farming's efficiency in terms of crop production through precision farming. Apart from the issue of food insecurity this approach also takes care of the destruction of the environment by practices such as large scale monoculture farming by directing the society to the right course to a sustainable agriculture.