Global warming, water shortages, and, most lately, an epidemic, all put strain on current food and agriculture manufacturing systems. The main aim of the research is to study smart agriculture monitoring systems using IoT and Drones. The research is designed to highlight the key characteristics of UAVs as well as artificial intelligence applications in understanding. CNN is utilised in detection and classification of spots on the leaves of plants thus enabling to highlight multiple diseases on the leaf. According to the research, an accuracy of almost 12% has been found as compared to the previous methods which had gained the accuracy of 75%. Sensors are considered to be the backbone of remote sensing that helps to provide all the information related to crops and its environment. This research also resulted in the creation of automated algorithms for producing prescription maps straight from mosaics of UAS pictures, demonstrating the economic and environmental benefits of UAS remote sensing. Therefore, it can be concluded that (UAVs) is known to as Unmanned Aerial Systems (UAS) to more accurately determine such fully advanced, safe, and profitable technologies that will enhance agricultural output profitability in the future.

Keywords: smart agriculture; Internet of Things; IoT and Drones; artificial intelligence; producing quality food; sustainability; IoT and Unmanned Aerial Vehicles