Application of Drone Systems for Spraying Pesticides in Advanced Agriculture: A Review

Abstract

The farmers in agriculture fields face health problems due to diseases caused by pesticides and insecticides. Thousands of cases result in adverse health effects when spraying pesticides manually onto crop fields. The use of drones for spraying pesticides is a promising alternative to manual spraying. It represents a major emerging field in India. Therefore, this article is an attempt to explore the latest technological advances and applications in Hardware, Flight Controller (FC) & Electronic Speed Controller (ESC), Smart Agricultural Sensors, and Spraying Systems. To make a mention, a few key advancements in drone systems are: The crops can be monitored by the use of a multispectral camera, mounted on a drone. The drone spraying system makes use of GPS coordinates to auto-navigate GPS coordinates to spray the pesticides on the infected areas in real-time as soon as the camera takes a picture of the spraying area. Different types of nozzles are applied to lead to specific sprinkling speeds and adaption of Bluetooth Low Energy (BLE) via smartphone. Auto control of the quantity of pesticide as per the speed of the drone and use of Artificial Intelligence (AI) for smart drone path control. Along with challenges in spraying technology, the possible direction of future research is highlighted. These technology upgrades lead to precision spraying, along with uniformity and less time. It could attract more and more farmers to spray pesticides by drone and increase crop yields in the coming years.

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“…Based on the research results of Yuantari et al (2013) 85.2% of farmers do not pay attention to wind direction when spraying pesticides. Spraying operations are considered the most hazardous operations as operators have to deal with toxic chemicals and prolonged exposure (Borikar et al 2022;Mogili and Deepak 2018;Shaw and Valkumar 2020). Drone Sprayers provides an effective method for such operations by reducing the operating time by at least about a third compared to conventional (Mat Su 2018).…”