Exploring Artificial Intelligence & Machine Learning in Precision Agriculture

Precision agriculture has been very fruitful in managing the technology to make farming become more productive and less resource consuming. The present paper deals with the applications of Artificial Intelligence (AI) and Machine Learning (ML) in precision agriculture by Google Earth Engine. GEE is a cloud platform, which provides a huge opportunity to build AI and ML derived insights of rich dataset satellite imagery and environmental variables. This research investigates how AI models and ML algorithms, through GEE, pave a way toward better decision-making in agriculture through accurate prediction of crop yields, disease detection, and analysis of soil health. It is estimated that such merging of AI and ML techniques could efficiently address the sustainability issues related to agricultural production, such as optimizing input use, reducing costs, and even lessening environmental impacts, solely through GEE data repositories and computation capacities. The present considers a means of future work towards the development of precision agriculture practices and methods with insights into the applicability of AI and ML methods in making agricultural productivity and sustainability more efficient.