CN112386171A - Intelligent cleaning method and system for building property - Google Patents
Intelligent cleaning method and system for building property Download PDFInfo
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- CN112386171A CN112386171A CN202011296220.5A CN202011296220A CN112386171A CN 112386171 A CN112386171 A CN 112386171A CN 202011296220 A CN202011296220 A CN 202011296220A CN 112386171 A CN112386171 A CN 112386171A
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- A—HUMAN NECESSITIES
- A47—FURNITURE; DOMESTIC ARTICLES OR APPLIANCES; COFFEE MILLS; SPICE MILLS; SUCTION CLEANERS IN GENERAL
- A47L—DOMESTIC WASHING OR CLEANING; SUCTION CLEANERS IN GENERAL
- A47L11/00—Machines for cleaning floors, carpets, furniture, walls, or wall coverings
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- A—HUMAN NECESSITIES
- A47—FURNITURE; DOMESTIC ARTICLES OR APPLIANCES; COFFEE MILLS; SPICE MILLS; SUCTION CLEANERS IN GENERAL
- A47L—DOMESTIC WASHING OR CLEANING; SUCTION CLEANERS IN GENERAL
- A47L11/00—Machines for cleaning floors, carpets, furniture, walls, or wall coverings
- A47L11/40—Parts or details of machines not provided for in groups A47L11/02 - A47L11/38, or not restricted to one of these groups, e.g. handles, arrangements of switches, skirts, buffers, levers
- A47L11/4011—Regulation of the cleaning machine by electric means; Control systems and remote control systems therefor
Abstract
The invention provides an intelligent cleaning method and system for building property, wherein the method comprises the following steps: acquiring a monitoring image at fixed time; acquiring a ground monitoring image; splicing the ground monitoring images to obtain a ground monitoring image of a public area; judging whether the pedestrian density in the public area is smaller than a preset threshold value or not; if yes, inputting a public area ground monitoring graph to a pre-trained cleanliness recognition model to recognize each area to be cleaned; marking each area to be cleaned in a ground monitoring graph of a public area; gridding the marked public area ground monitoring graph, and acquiring a grid to be cleaned; generating an automatic cleaning path according to the current position of the cleaning robot and the grid to be cleaned; and navigating the cleaning robot according to the automatic cleaning path. The invention has the automatic cleaning function, can maintain good property cleanliness, can obviously improve cleaning efficiency and reduce labor cost, and has strong practicability.
Description
Technical Field
The invention relates to the technical field of property management, in particular to an intelligent building property cleaning method and system.
Background
The property refers to various houses which are already put into use and matched equipment, facilities and sites thereof. The property may be in the form of office buildings, commercial buildings, residential quarters, villas, industrial parks, hotels, factories, warehouses, and the like. The property can be large or small, and the size of the property can reach thousands of square meters or even larger; moreover, the construction and the control range of each property are greatly different due to different building structures. All properties have in common the need to maintain good cleanliness, but it is not an easy matter to maintain a certain cleanliness in all directions based on the area size, construction and frequent movement of people of the properties. Not only needs a large amount of management personnel to supervise and manage; but also requires a significant amount of cleaning staff to engage. Which are both a significant cost and labor input.
Based on the above, the invention provides an intelligent building property cleaning method and system, which can well solve the problems.
Disclosure of Invention
The technical problem to be solved by the invention is as follows: the intelligent cleaning method and the intelligent cleaning system for the building property can intelligently clean and maintain good cleanliness, and greatly reduce labor input.
In order to solve the technical problems, the invention adopts the technical scheme that:
an intelligent building property cleaning method comprises the following steps:
setting a camera to comprehensively monitor a public area of a building;
acquiring monitoring images of all cameras at fixed time;
deleting the non-ground area image in the monitoring image to obtain a ground monitoring image;
splicing the ground monitoring images to obtain a ground monitoring image of a public area;
judging whether the pedestrian density in the public area is smaller than a preset threshold value according to the public area ground monitoring image;
if yes, inputting the public area ground monitoring graph to a pre-trained cleanliness recognition model, and recognizing each area to be cleaned in the public area ground monitoring graph through the cleanliness recognition model;
marking each area to be cleaned in the public area ground monitoring graph;
gridding the marked public area ground monitoring graph, and acquiring a grid to be cleaned;
acquiring a current position of the cleaning robot; generating an automatic cleaning path according to the current position and the grid to be cleaned;
and navigating the cleaning robot according to the automatic cleaning path.
Further, still include:
when the navigation of the automatic cleaning path is finished, acquiring the monitoring image of each camera;
and acquiring a corresponding public area ground monitoring image according to the monitoring image, and inputting the public area ground monitoring image into the cleanliness identification model to acquire the task completion degree.
Further, still include:
and when the task completion degree is lower than a preset threshold value, regenerating an automatic cleaning path according to the obtained public area ground monitoring graph.
Further, the step of judging whether the pedestrian density in the public area is smaller than a preset threshold value according to the public area ground monitoring map comprises the following steps:
inputting the public area ground monitoring graph to a pre-trained pedestrian density recognition model, and acquiring the pedestrian density of the public area through the pedestrian density recognition model;
and judging whether the pedestrian density is smaller than a preset threshold value or not.
Further, the splicing the ground monitoring images to obtain a ground monitoring image of a public area includes:
and splicing the ground monitoring images according to the camera positioning information corresponding to the ground monitoring images and the BIM corresponding to the buildings to obtain a public area ground monitoring image consisting of sub-public area ground monitoring images of all floors.
Further, still include:
building a BIM (building information model) corresponding to a building, and displaying the grid to be cleaned in the BIM;
and displaying the current position of the cleaning robot and the task execution condition through the BIM model, wherein the task execution condition comprises that the cleaned grid to be cleaned is displayed as green and the uncleaned grid to be cleaned is displayed as red.
Further, the generating an automatic sweeping path according to the current position and the grid to be cleaned comprises:
and taking the current position of the cleaning robot as an initial node and each grid to be cleaned as a target node, generating a shortest path which can traverse all the target nodes from the initial node, and defining the shortest path as an automatic cleaning path.
The invention provides another technical scheme as follows:
an intelligent building property cleaning system comprises a camera, a cleaning robot and a server; the camera and the cleaning robot are respectively connected with the server;
the camera is used for comprehensively monitoring the public area of the building;
the cleaning robot is used for receiving and executing a navigation instruction of the server and cleaning a specified area;
the server side comprises a storage medium, a computer program is stored on the storage medium, and when the computer program is executed by a processor of the server side, the server side can realize the following steps:
acquiring monitoring images of all cameras at fixed time;
deleting the non-ground area image in the monitoring image to obtain a ground monitoring image;
splicing the ground monitoring images to obtain a ground monitoring image of a public area;
judging whether the pedestrian density in the public area is smaller than a preset threshold value according to the public area ground monitoring image;
if yes, inputting the public area ground monitoring graph to a pre-trained cleanliness recognition model, and recognizing each area to be cleaned in the public area ground monitoring graph through the cleanliness recognition model;
marking each area to be cleaned in the public area ground monitoring graph;
gridding the marked public area ground monitoring graph, and acquiring a grid to be cleaned;
acquiring a current position of the cleaning robot; generating an automatic cleaning path according to the current position and the grid to be cleaned;
and navigating the cleaning robot according to the automatic cleaning path.
Further, when executed by the processor of the server, the program can further realize the following steps:
when the navigation of the automatic cleaning path is finished, acquiring the monitoring image of each camera;
further, when executed by the processor of the server, the program can further realize the following steps:
acquiring a corresponding public area ground monitoring image according to the monitoring image, and inputting the public area ground monitoring image into the cleanliness identification model to acquire a task completion degree;
and when the task completion degree is lower than a preset threshold value, regenerating an automatic cleaning path according to the obtained public area ground monitoring graph.
Further, when the step of judging whether the pedestrian density in the public area is less than the preset threshold value according to the public area ground monitoring map is executed by the program, the execution includes:
inputting the public area ground monitoring graph to a pre-trained pedestrian density recognition model, and acquiring the pedestrian density of the public area through the pedestrian density recognition model;
and judging whether the pedestrian density is smaller than a preset threshold value or not.
Further, when executed by the processor of the server, the program can further realize the following steps:
building a BIM (building information model) corresponding to a building, and displaying the grid to be cleaned in the BIM;
and displaying the current position of the cleaning robot and the task execution condition through the BIM model, wherein the task execution condition comprises that the cleaned grid to be cleaned is displayed as green and the uncleaned grid to be cleaned is displayed as red.
Further, the program, when executing the step of generating an automatic sweeping path according to the current position and the grid to be cleaned, comprises:
and taking the current position of the cleaning robot as an initial node and each grid to be cleaned as a target node, generating a shortest path which can traverse all the target nodes from the initial node, and defining the shortest path as an automatic cleaning path.
The invention has the beneficial effects that: whether automatic cleaning work is carried out or not can be judged regularly according to the pedestrian density in the public area, so that the cleaning efficiency is improved, and the influence on pedestrians is reduced; all areas to be cleaned can be automatically identified according to the current monitoring image of the public area, the areas to be cleaned are converted into grids to be cleaned for identification, an automatic cleaning path is generated by combining the current position of the cleaning robot, then the cleaning robot is navigated to move to perform cleaning one by one, and the targeted, intelligent, automatic and efficient cleaning is realized. More importantly, the implementation of the invention can avoid supervision and management work of managers and cost investment of a large number of cleaning personnel, replaces manpower with intelligence, and obviously improves the cleaning efficiency.
Drawings
FIG. 1 is a schematic flow chart of intelligent cleaning of building property according to an embodiment of the present invention;
FIG. 2 is a schematic structural diagram of a building property intelligent management system according to a second embodiment of the present invention;
fig. 3 is a labeled and meshed ground monitoring map of a public area corresponding to a certain floor and an automatic cleaning path generated thereby according to an embodiment of the present invention.
Detailed Description
In order to explain technical contents, achieved objects, and effects of the present invention in detail, the following description is made with reference to the accompanying drawings in combination with the embodiments.
Example one
The embodiment provides an intelligent cleaning method for building property, referring to fig. 1, which may include the following steps:
firstly, laying in earlier stage
Cameras are needed to monitor the public areas of the building in a comprehensive manner. Preferably, the camera target of the camera is set as the ground so as to improve the efficiency and accuracy of subsequently acquiring the ground monitoring image.
A cleaning robot with an automatic cleaning function and a positioning function is provided, wherein the automatic cleaning function at least comprises two basic cleaning functions of sweeping and mopping. Preferably, a cleaning robot can be respectively equipped corresponding to each floor of the building, thereby further improving the cleaning efficiency.
Second, management and cleaning Process
Firstly, the monitoring images of all the cameras are obtained at regular time, namely the current monitoring image of the public area is obtained. And then deleting the non-ground area image in the monitoring image to obtain a ground monitoring image. If the camera directly monitors the ground, the efficiency is greatly improved in the step, and the ground monitoring image can be obtained at a high speed.
Secondly, according to the positioning information of the camera, splicing the corresponding ground monitoring images, and restoring to obtain a ground monitoring image of the public area. The ground monitoring map of the public area only needs to show the ground surface pattern and the pedestrians on the ground surface. An exemplary graph is shown in fig. 3 (excluding the grid and paths in the graph).
In a preferred embodiment, the ground monitoring images can be spliced according to camera positioning information corresponding to the ground monitoring images and a Building Information Modeling (BIM) corresponding to a building, so as to obtain a three-dimensional public area ground monitoring (model) map composed of sub-public area ground monitoring maps of each floor. The three-dimensional public area ground monitoring graph can ensure that the corresponding relation between the ground monitoring area and each floor is accurate and error-free, and errors are less prone to occur in the subsequent analysis process.
And then, judging whether the pedestrian density in the public area is less than a preset threshold value according to the ground monitoring image of the public area. In a specific example, the public area ground monitoring graph can be input to a pre-trained pedestrian density recognition model, and the pedestrian density of the public area is obtained through the pedestrian density recognition model; and judging whether the pedestrian density is smaller than a preset threshold value or not. In another embodiment, pedestrian density may also be determined by image recognition and analysis of a public area ground monitoring map.
If the pedestrian density in the public area is smaller than the preset threshold value, the number of pedestrians in the public area is proved to be less, and the cleaning work is suitable to be carried out at the moment, so that the next step can be carried out. If the pedestrian density in the public area is larger than or equal to the preset threshold value, the fact that more pedestrians are in the public area is proved to be unfavorable for cleaning, and therefore the next step is not recommended to be carried out, and the next judgment period is continuously waited.
And if the cleaning work is determined to be carried out, inputting the public area ground monitoring graph to a pre-trained cleanliness recognition model, and recognizing each area to be cleaned in the public area ground monitoring graph through the cleanliness recognition model. The cleanliness identification model can be an optimization model obtained by deep learning and training a certain number of floor monitoring maps in public areas of buildings with high cleanliness and a certain number of floor monitoring maps with low or low cleanliness as different label data, and is used for identifying whether areas with unsatisfactory cleanliness exist in the input floor monitoring maps.
And if the public area ground monitoring graph has the area to be cleaned, the server side clearly marks the area to be cleaned identified by the cleanliness identification model. On one hand, the subsequent operation can be made clear through marking, and the accuracy is improved; on the other hand, the public area ground monitoring graph marked with the area to be cleaned can also be sent to a designated terminal for displaying, so that managers can conveniently know and check all areas needing to be cleaned in each period.
Then, gridding the marked public area ground monitoring graph, and obtaining the grid to be cleaned, referring to fig. 3, the oblique line grid therein is the grid not to be cleaned, that is, each area to be cleaned is further refined into at least one grid to be cleaned. Thus, for the internal treatment of the cleaning robot, the specific position and range needing cleaning can be more conveniently determined; and also facilitates more accurate positioning of the cleaning robot to the location to be cleaned. Thereby realizing more excellent and more efficient cleaning work.
Then, the current position of the cleaning robot (the position of the circular grid in fig. 3) is acquired, and an automatic sweeping path (the schematic path in fig. 3) is generated according to the current position and the grid to be cleaned. In a specific example, the current position of the cleaning robot may be used as an initial node, each determined mesh to be cleaned is used as a target node, and then N feasible paths that can traverse (reach) all the target nodes from the initial node are generated to obtain a path set; and then calculating the path length of each feasible path in the path set, and defining the shortest path as an automatic cleaning path.
And then, navigating the cleaning robot according to the automatic cleaning path. The cleaning robot reaches each target node, namely the grid to be cleaned, in sequence according to the received navigation instruction, then carries out full-automatic cleaning work, and automatically enters the navigation and cleaning with the next target node as a destination after the grid to be cleaned is cleaned. For example, please refer to the path marked in fig. 3, which is a cleaning robot that guides the cleaning robot to pass through the five paths and automatically cleans the five grids according to the illustrated path by using path branch 1, path branch 2, path branch 3, path branch 4 and path branch 5 as navigation paths in sequence.
Preferably, during the cleaning process of the cleaning robot, the grid to be cleaned is displayed in a BIM model created in a specified terminal corresponding to a building; and displaying the current position of the cleaning robot and the task execution condition through the BIM model, wherein the task execution condition comprises that the cleaned grid to be cleaned is displayed as green and the uncleaned grid to be cleaned is displayed as red. Therefore, a user can conveniently master the execution condition of the current cleaning task, know the working state of the cleaning robot, and be more beneficial to systematic and intelligent management.
And finally, after the automatic cleaning path navigation is finished, namely the cleaning robot finishes all cleaning tasks of the grid to be cleaned, the task completion condition of the cleaning robot can be checked in the following way, so that the cleanliness of the property can be more accurately mastered, and meanwhile, the fault condition of the cleaning robot can be timely eliminated.
Firstly, acquiring current monitoring images of all cameras; and acquiring a corresponding public area ground monitoring image according to the current monitoring image, and inputting the public area ground monitoring image into the cleanliness identification model to acquire the task completion degree. The task completion degree can be determined according to the percentage of the number of the grids to be cleaned determined according to the area to be cleaned output by the cleanliness identification model and the total number of the grids to be cleaned corresponding to the task. The whole process is the same as the process of identifying the area to be cleaned in the timing cleaning work, the aim is to acquire the area to be cleaned, only the triggering time is different, the timing cleaning work is the timing triggering, and the checking task completion condition is triggered when the cleaning robot completes the task.
Further, when the task completion degree is lower than a preset threshold value, an automatic cleaning path is regenerated according to the public area ground monitoring graph (obtained in the inspection process) obtained at this time, then the original cleaning robot or the new cleaning robot is navigated, and the cleaning is carried out again aiming at the area which does not reach the standard, so that the cleanliness of the property public area is always maintained in an ideal state.
Example two
The embodiment corresponds to the first embodiment, and provides an intelligent building property cleaning system, please refer to fig. 2, which includes a camera, a cleaning robot and a server; the camera and the cleaning robot are respectively connected with the server;
the camera is used for comprehensively monitoring the public area of the building; preferably, the imaging target is a ground surface area of the common area.
The cleaning robot is used for receiving and executing a navigation instruction of the server and cleaning a specified area;
the server includes a storage medium, on which a computer program is stored, and when the program is executed by a processor of the server, all the steps that can be implemented by the server in the first embodiment can be implemented.
The detailed steps are not repeated in detail, and refer to the description of the first embodiment for details.
As can be understood from the foregoing description, those skilled in the art can understand that all or part of the processes in the foregoing technical solutions can be implemented by instructing related hardware through a computer program, where the program can be stored in a computer-readable storage medium, and when executed, the program can include the processes executed by the server in the foregoing first embodiment. The program can also realize the beneficial effect of server side acquisition after being executed by the processor.
The storage medium may be a magnetic disk, an optical disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), or the like.
In summary, the intelligent management method and system for building property provided by the invention can regularly judge whether to perform automatic cleaning work according to the pedestrian density in the public area, thereby improving the cleaning efficiency and reducing the influence on pedestrians; all areas to be cleaned can be automatically identified according to the current monitoring image of the public area, the areas to be cleaned are converted into grids to be cleaned for identification, an automatic cleaning path is generated by combining the current position of the cleaning robot, then the cleaning robot is navigated to move to perform cleaning one by one, and the targeted, intelligent, automatic and efficient cleaning is realized. More importantly, the implementation of the invention can avoid supervision and management work of managers and cost investment of a large number of cleaning personnel, replaces manpower with intelligence, and obviously improves the cleaning efficiency. Therefore, the automatic cleaning machine has an automatic cleaning function, can maintain good property cleanliness, can remarkably improve cleaning efficiency and reduce labor cost, and has strong practicability.
The above description is only an embodiment of the present invention, and not intended to limit the scope of the present invention, and all equivalent changes made by using the contents of the present specification and the drawings, or applied directly or indirectly to the related technical fields, are included in the scope of the present invention.
Claims (10)
1. An intelligent building property cleaning method is characterized by comprising the following steps:
setting a camera to comprehensively monitor a public area of a building;
acquiring monitoring images of all cameras at fixed time;
deleting the non-ground area image in the monitoring image to obtain a ground monitoring image;
splicing the ground monitoring images to obtain a ground monitoring image of a public area;
judging whether the pedestrian density in the public area is smaller than a preset threshold value according to the public area ground monitoring image;
if yes, inputting the public area ground monitoring graph to a pre-trained cleanliness recognition model, and recognizing each area to be cleaned in the public area ground monitoring graph through the cleanliness recognition model;
marking each area to be cleaned in the public area ground monitoring graph;
gridding the marked public area ground monitoring graph, and acquiring a grid to be cleaned;
acquiring a current position of the cleaning robot; generating an automatic cleaning path according to the current position and the grid to be cleaned;
and navigating the cleaning robot according to the automatic cleaning path.
2. The intelligent building property cleaning method as claimed in claim 1, further comprising:
when the navigation of the automatic cleaning path is finished, acquiring the monitoring image of each camera;
and acquiring a corresponding public area ground monitoring image according to the monitoring image, and inputting the public area ground monitoring image into the cleanliness identification model to acquire the task completion degree.
3. The intelligent building property cleaning method as claimed in claim 2, further comprising:
and when the task completion degree is lower than a preset threshold value, regenerating an automatic cleaning path according to the obtained public area ground monitoring graph.
4. The intelligent building property cleaning method as claimed in claim 1, wherein the determining whether the pedestrian density in the public area is less than a preset threshold value according to the public area ground monitoring map comprises:
inputting the public area ground monitoring graph to a pre-trained pedestrian density recognition model, and acquiring the pedestrian density of the public area through the pedestrian density recognition model;
and judging whether the pedestrian density is smaller than a preset threshold value or not.
5. The intelligent building property cleaning method as claimed in claim 1, wherein said stitching the ground monitoring images to obtain a ground monitoring map of a public area comprises:
and splicing the ground monitoring images according to the camera positioning information corresponding to the ground monitoring images and the BIM corresponding to the buildings to obtain a public area ground monitoring image consisting of sub-public area ground monitoring images of all floors.
6. The intelligent building property cleaning method as claimed in claim 1, further comprising:
building a BIM (building information model) corresponding to a building, and displaying the grid to be cleaned in the BIM;
and displaying the current position of the cleaning robot and the task execution condition through the BIM model, wherein the task execution condition comprises that the cleaned grid to be cleaned is displayed as green and the uncleaned grid to be cleaned is displayed as red.
7. The intelligent building property cleaning method as claimed in claim 1, wherein the generating of the automatic cleaning path according to the current position and the grid to be cleaned comprises:
and taking the current position of the cleaning robot as an initial node and each grid to be cleaned as a target node, generating a shortest path which can traverse all the target nodes from the initial node, and defining the shortest path as an automatic cleaning path.
8. An intelligent building property cleaning system is characterized by comprising a camera, a cleaning robot and a server; the camera and the cleaning robot are respectively connected with the server;
the camera is used for comprehensively monitoring the public area of the building;
the cleaning robot is used for receiving and executing a navigation instruction of the server and cleaning a specified area;
the server side comprises a storage medium, a computer program is stored on the storage medium, and when the computer program is executed by a processor of the server side, the server side can realize the following steps:
acquiring monitoring images of all cameras at fixed time;
deleting the non-ground area image in the monitoring image to obtain a ground monitoring image;
splicing the ground monitoring images to obtain a ground monitoring image of a public area;
judging whether the pedestrian density in the public area is smaller than a preset threshold value according to the public area ground monitoring image;
if yes, inputting the public area ground monitoring graph to a pre-trained cleanliness recognition model, and recognizing each area to be cleaned in the public area ground monitoring graph through the cleanliness recognition model;
marking each area to be cleaned in the public area ground monitoring graph;
gridding the marked public area ground monitoring graph, and acquiring a grid to be cleaned;
acquiring a current position of the cleaning robot; generating an automatic cleaning path according to the current position and the grid to be cleaned;
and navigating the cleaning robot according to the automatic cleaning path.
9. The intelligent building property cleaning system of claim 8, wherein the program, when executed by the server-side processor, further performs the steps of:
when the navigation of the automatic cleaning path is finished, acquiring the monitoring image of each camera;
acquiring a corresponding public area ground monitoring image according to the monitoring image, and inputting the public area ground monitoring image into the cleanliness identification model to acquire a task completion degree;
and when the task completion degree is lower than a preset threshold value, regenerating an automatic cleaning path according to the obtained public area ground monitoring graph.
10. The intelligent building property cleaning system of claim 8, wherein the program, when executed by the server-side processor, further performs the steps of:
building a BIM (building information model) corresponding to a building, and displaying the grid to be cleaned in the BIM;
and displaying the current position of the cleaning robot and the task execution condition through the BIM model, wherein the task execution condition comprises that the cleaned grid to be cleaned is displayed as green and the uncleaned grid to be cleaned is displayed as red.
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| CN115167483A (en) * | 2022-09-07 | 2022-10-11 | 湖南海讯供应链有限公司 | Agricultural product storage system and management method thereof |
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