Applications of UAV-AD (Unmanned Aerial Vehicle-Agricultural Drones) in Precision Farming

India is an agricultural economy. Most of our population relies on agriculture for their daily earning and livelihood. The growth of this sector depends a lot on the quality and quantity of production, the consumption cycle, and the mechanisms adopted for distribution and storage. As the population increases, there is an increase in the demand for food grains, pulses, and other crops. The statistics have already revealed that the production from our farmlands is far below the true potential that they can yield. This reduction in yield could be due to several reasons like crop diseases, lack of infrastructure, lack of knowledge, mismanagement, and insufficient measures to curb the infections at the bud itself. Precision agriculture, i.e., the science of improving the yield of crops and facilitating technology-enabled management to ensure timely decisions, is an emerging field that is being slowly adopted in different parts of the world to increase agricultural production. Agricultural drones have played a significant role in assisting farming operations. They have been used to provide information about the farmlands and the soil’s condition, to monitor crop growth at different stages, to monitor any infestation in the field, and to gauge any intruder attack (human or animal). The drones are equipped with various sensors to capture the information, which is usually transmitted to the ground station using the cellular network. This book chapter implores the applications of agricultural drones in precision farming. The chapter discusses the impetus that led to precision agriculture. It also discusses the five main areas of application of drones in this field, i.e., crop spraying, crop monitoring, mapping and soil analysis, livestock monitoring, and seed planting. The various challenges faced in adopting drones, especially in the Indian economy, are also discussed. The chapter also proposes an Intelligent System for Precision Agriculture (ISPA) and its main components. It examines each component’s role and significance and the association between them to facilitate smooth data flow. The last section summarizes the learning and the open research areas.