Risk monitoring method and device based on machine learning, storage medium and electronic equipment
A machine learning and machine learning model technology, applied in the field of risk monitoring based on machine learning, can solve the problems of loss, difficult sensor arrangement, low security monitoring accuracy, etc., and achieve the effect of accurate calculation and analysis
Pending Publication Date: 2020-03-27
PING AN TECH (SHENZHEN) CO LTD
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Problems solved by technology
[0002] Cracking and deformation of building structures are common technical problems at home and abroad. The tilting and deformation of building structures will lead to instability and collapse of buildings, especially for buildings with poor integrity or already damaged. Once the deformation limit is reached, great losses will be caused in an instant
[0003] At present, the monitoring of buildings is mostly performed by manual methods or the arrangement of sensors. Manual detection and observation have a long cycle and large errors, and it is impossible to collect dynamic data for analysis, which makes it difficult to effectively guarantee the safety of the building.
When using methods such as inclination sensors to monitor buildings, there are difficulties in the arrangement of sensors, and the detection of cracks in buildings, for example, is not in place.
In the existing technology, there is a problem that the accuracy rate of building safety monitoring is not high, and at the same time, it consumes more human resources.
Method used
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[0055] Example embodiments will now be described more fully with reference to the accompanying drawings. Example embodiments may, however, be embodied in many forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this application will be thorough and complete, and will fully convey the concepts of example embodiments to those skilled in the art. The described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided in order to give a thorough understanding of embodiments of the present application. However, those skilled in the art will appreciate that the technical solutions of the present application can be practiced without one or more of the specific details, or other methods, components, devices, steps, etc. can be used. In other instances, well-known technical solutions have not b...
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The invention relates to a risk monitoring method and device based on machine learning, a storage medium and electronic equipment, and belongs to the technical field of building monitoring, and the method comprises the steps: obtaining an inclination monitoring image of a building, and periodically obtaining a crack monitoring image of the building; acquiring a periodic inclination according to the inclination monitoring image, and acquiring periodic crack element data according to the crack monitoring image; generating a plurality of input data streams according to each periodic inclination and the periodic crack element data associated with each periodic inclination; generating a base data flow according to all the periodic gradients and all the periodic crack element data; and obtaininga predetermined number of input data streams in the plurality of input data streams to form an attack stream, and inputting the attack stream into a machine learning model to obtain a risk value of the building. According to the method, the attacked flow is generated based on the building inclination and crack data of the building monitoring image, and the risk value of the building is efficiently and accurately monitored through the machine learning model.
Description
technical field [0001] The present application relates to the technical field of building monitoring, in particular, to a risk monitoring method, device, storage medium and electronic equipment based on machine learning. Background technique [0002] Cracking and deformation of building structures are common technical problems at home and abroad. The tilting and deformation of building structures will lead to instability and collapse of buildings, especially for buildings with poor integrity or damage. Once the deformation limit is reached, great losses will be caused in an instant. [0003] At present, the monitoring of buildings is mostly carried out by manual methods or the arrangement of sensors. Manual detection and observation have a long cycle and large errors, and it is impossible to collect dynamic data for analysis, making it difficult to effectively guarantee the safety of the building. When using methods such as inclination sensors to monitor buildings, there is ...
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IPC IPC(8): G06K9/00G06N20/00
CPCG06N20/00G06V20/41G06V20/52
Inventor王红伟
OwnerPING AN TECH (SHENZHEN) CO LTD