Diseased area recognition and pesticide spraying in farming lands by multicopters and image processing system

被引:0
|
作者
Rao Pittu V.S. [1 ]
Gorantla S.R. [1 ]
机构
[1] Electrical and Electronics Engineering, VFSTR, Vadlamudi, Guntur, Andhra Pradesh
来源
Journal Europeen des Systemes Automatises | 2020年 / 53卷 / 01期
关键词
Disease detection; Image acquisition; Path planning; Unmanned aerial vehicle (UAV)/ multicopter;
D O I
10.18280/jesa.530115
中图分类号
学科分类号
摘要
United Nations indexes that the world's population will increase drastically, it may increase by 20% and it will be around 970 crores by 2050. However this scenario requires 20% more food to serve this much population, but farming land is decreasing due to pollution, industrialization, and globalization. Cultivation these days is more difficult and increasing the labor cost and pesticides. Enough labor is not available, so labor charges are also increasing which reflects in expenditure for cultivation. In regular spraying system pesticides are sprayed in the whole field. This will increase pesticide costs and pollution. In this proposed system image acquiring Multicopter will move in a pre-defined path in the field is given in a Mission planner firmware. UAV while moving along the pre-defined path captures high-quality RGB pictures in the field and those captured images are tagged with a Global Positioning System (GPS). These pictures are processed by the image processing system using MATLAB software at the ground station and actual disease recognition from the database frame is done. Disease recognition is done along with the tag of the specific diseased area in the field. These tags can help the crew to identify the diseased area spot. This diseased area or plant GPS tag information is used for the creation of a path for pesticide spraying Multicopters and will spray the pesticide in a diseased area or a plant in the field. This will lead to the optimal usage of pesticides. © 2020 Lavoisier. All rights reserved.
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页码:123 / 130
页数:7
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