Autonomous Pesticide Sprayer Hexacopter
The project revolves around designing and implementing an autonomous pesticide sprayer hexacopter that will be capable of detecting potato disease using a computer vision module and spraying the infected areas only. The UAV can map out the whole field and generate a health map indicating healthy versus sick areas. This process begins with the drone taking off from home position till it reaches the first lane of the field, traversing the area in a zig-zag pattern looking for infected potato leaves. After generating the respective health map, the user interface will alarm the client on the possibility of having sick areas and ask permission to spray pesticides. Upon the client’s approval, the drone will head over to the designated area, hover for a small period and activate the pump to start the sprinkling process. This paper contains a detailed literature review, discussing multiple solutions for this application to pinpoint advantages and drawbacks of existing solutions. Additionally, this project is subject to several constraints, namely the outdoor environment that may be harsh for UAVs to operate. This approach will reduce the amount of wasted pesticides, eliminate the need for manual labor, and diminish the risk of exposure to harmful chemicals that are proven to be lethal in the long-term.Project Details
- Student(s): Rami M. Hjeij, Hassan H. Al Hakim, Hasan H. Ismail, Mostafa I. Rammal
- Advisor(s): Dr. Harag Margossian
- Year: 2023-2024