科研之友
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摘要
Poor realization of agronomic standards, low level of automation, time-consuming and labor-intensive farming are the main problems in traditional production process of vegetable. In order to improve vegetable cultivation intelligent and intensive level,reduce waste of production resources, an intelligent vegetable cultivation device was designed based on APP control, internet communications and image recognition technology, with the functions of remote control, precision sowing, quantitative dosing of liquid materials and weed recognition. The device mainly includes farming executing part, image processing part, STM32 microcontroller, and the APP which sends a command and control the device to work on the corresponding farming work. The precision seeding sowing worked through the gantry positioning and the cooperation of magnetic coupling tools and gas-suction sowing tools. By controlling the pump running time and monitoring flow volume with PVDF pressure sensor installed in the liquid pipeline interface, the liquid material was delivered quantitatively. Weed images were collected by CCD camera and recognition algorithm was developed based on BP neural network to obtain the weed location information. The test results show that the error rate of sowing was 2.75%, the passing rate of the plant spacing was up to 97.2%, no miss sowing occurs during the test; the error of the liquid delivery was within +/- 5.8 g; true positive rate, true negative rate and accuracy of weed recognition were above 95%.
- 出版日期2019-7
- 单位河南大学
