Online spraying quality assessment system of plant protection unmanned aerial vehicle based on Android client

Abstract We develop an online spraying quality assessment system of plant protection unmanned aerial vehicle (UAV) based on Android Client. The built-in location and motion system of mobile phone are used to acquire the GPS data, speed and height of the UAV placed with Android mobile phone. A pump operation endpoints extraction model based on double-threshold method is developed to determine the pump operation status (on/off) during UAV flight. Adaptive Gaussian Filtering is employed to improve the positioning accuracy. Some assessment indexes including overlap spray and blank spray rates indicating plant protection UAV spraying quality are proposed in this paper. The test results show that: ① the max deviation of the beginning/end point extracted by double-threshold model is 2 s, and the max deviation of total operation time is 4 s; ② adaptive Gaussian Filtering can effectively improve the accuracy of static and dynamic positioning. We take filter parameter σ = 1, to decrease the measured dynamic positioning deviation and avoid clear reduction of measured total distance (when σ > 1) by smartphone; ③ when σ = 1, the difference values of effective spray rate, the overlap spray rate and the blank spray rate between smartphone measuring and UAV recording are only 1.08％, 0.68％and 1.07％, respectively.