Aerial AI acquisition, inspecting and early warning method and device for water bank events
A waterfront and event technology, applied to alarms, computer components, character and pattern recognition, etc., can solve problems such as low efficiency, high time consumption, and long time consumption
Pending Publication Date: 2021-08-06
深圳块织类脑智能科技有限公司
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The manual inspection method consumes a long time and requires a lot of manpower. When many waterfronts need to be inspected, they face problems such as a lot of time and low efficiency. At the same time, many people on the waterfront cannot achieve
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[0047] In the following description, specific details such as specific system structures and technologies are presented for the purpose of illustration rather than limitation, so as to thoroughly understand the embodiments of the present application.
[0048] Before the official flight operation (or normalized acquisition operation) of the UAV, it is necessary to complete the process of determining the incident on the waterfront and the area to be investigated, pre-planning the corresponding route, and pre-loading the target detection model.
[0049] Combine below figure 1 Introduce and explain the UAV flight operation, specifically the related process of the air AI acquisition and early warning method for water-shore incidents before and during the flight operation of the UAV. figure 1 The process before the normal operation of the UAV (that is, steps S101-S103) is included in the process of the air AI acquisition and early warning method for water and shore incidents.
[0050...
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The invention discloses an aerial AI acquisition, inspecting and early warning method and device for water bank events. Inspection and acquisition inspection are performed on a water bank, and intelligent detection and intelligent early warning are performed on an event by utilizing the maneuverability of an unmanned aerial vehicle and an AI technology, so that the detection efficiency of a water bank acquisition task is improved, and the detection cost is reduced. The method comprises the steps that: to-be-detected image data of a to-be-detected area is acquired, the to-be-detected image data covers a water bank, and the to-be-detected image data is image data obtained by performing image acquisition on the to-be-detected area through a carried image acquisition device in the process that an unmanned aerial vehicle flies according to a pre-loaded route; the to-be-detected image data are input into a pre-loaded target detection model, an output image of the target detection model is obtained, the output image comprises a detection frame with a label, and the label is used for representing a collection and inspection task category of a water bank event to which the detection frame belongs; the output image is processed according to a preset distance threshold to obtain a detection result set; and early warning information is generated according to the detection result set.
Description
technical field [0001] The application belongs to the technical field of artificial intelligence and unmanned aerial vehicles, and in particular relates to an aerial AI survey and early warning method and device for water-shore incidents. Background technique [0002] At present, the water bank is generally inspected with the naked eye to determine whether there is sewage discharge, sand dredging or work sheds on the water bank. The manual inspection method takes a long time and requires a lot of manpower. When many waterfronts need to be inspected, they face problems such as a lot of time spent and low efficiency. At the same time, many people at the waterfront cannot reach them at all. [0003] In addition, with the continuous development of drone technology, the application of drones is becoming more and more extensive. It is the general trend to use the mobility and artificial intelligence technology of drones for aerial AI patrols. [0004] Aerial AI inspections replac...
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IPC IPC(8): G06K9/00G06K9/62G08B21/18
CPCG08B21/18G06V20/13G06V2201/07G06F18/24
Inventor 曾崛柯小龙恒朝李先美刘桂彬
Owner 深圳块织类脑智能科技有限公司