Abstract
Drones are used increasingly for agricultural surveillance. The limited flight range of drones poses a problem for surveillance of large, inaccessible areas. One possible solution is to place autonomous, solar-powered charging stations within the area of interest, where the drone can recharge during its mission. This paper designs and implements a software system for planning low-cost drone coverage of large areas. The software produces a feasible, cost-minimizing charging station placement, as well as a drone path specification. Multiple optimizations are required, which are formulated as integer linear programs. In extensive simulations, the resulting drone paths achieved 70–90 percent of theoretical optimal performance in terms of minimizing mission time for a given number of charging stations, for a variety of field configurations.
Highlights
Agricultural surveillance is an important part of ensuring optimal crop yields, by detecting problems in the growth process or during early stages so that proactive measures can be taken
Drones have been proposed as a solution to agricultural surveillance [6,7,8,9]
A drone flies over an agricultural area farm and collects image data that will be analyzed later for various applications, including weed detection and mapping [10,11,12,13]; growth monitoring [14,15,16]; crop health monitoring [17,18,19]; irrigation management [20,21]; yield prediction [22,23,24]; crop lodging detection [25,26,27]; and vineyard monitoring [28,29]
Summary
Agricultural surveillance is an important part of ensuring optimal crop yields, by detecting problems in the growth process or during early stages so that proactive measures can be taken. Surveillance of agricultural areas was conducted by human caretakers who personally surveyed the fields. Some researchers have proposed video surveillance systems with IP cameras in a wireless network for farms or forests [1,2,3,4,5] This technology can provide improved surveillance, several drawbacks remain, including the cost of the system for large area surveillance and the risk of blind spots. Positioning of cameras may be difficult, and image quality may not be sufficient To overcome those challenges, drones have been proposed as a solution to agricultural surveillance [6,7,8,9]. Most deployments have been located in developed countries
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