AI and IoT are changing precision agriculture, process automation, irrigation optimization, predicting the health of crops and animals, improving the supply chain, and making things more sustainable. AI and IoT technology help with big problems like a lack of agricultural supplies and a growing global population. AI, IoT, remote sensing, and GIS-powered precision agriculture goes beyond traditional farming to use data-driven strategies that make the most use of resources, increase crop yields, cut down on waste, and make farming more sustainable. This adjustment not only makes things work better, but it also encourages eco-friendly farming practices, which makes agriculture more resistant to climate change and resource depletion and lowers the growing need for food. Using AI and the Internet of Things (IoT) in precision farming has made it much easier to keep an eye on crops, manage resources, and make decisions. When used on the FAOSTAT dataset, a suggested precision farming (PF) method does better than the current classification methods, getting 98.65% accuracy, 98.32% precision, and 97.65% recall in just 0.23 seconds. This method also shows off the tools and methods that are important for PF and the tools that are used in modern farming in real time. When you combine IoT devices with machine learning, you can look at data in real time. This makes things more efficient, has less of an effect on the environment, and produces more. This is good for the environment and makes money. Using both in situ and mobile sensors is very important for predicting yields and making decisions based on those predictions. Also, radio frequency variables are needed to make wireless sensor networks (WSNs) work better in farming. But they are still worried about privacy issues, the intricacy of the technology, and the high expenses of putting it into practice.