Abnormity management method and property management system for AI intelligent property

Abstract

The invention relates to an abnormity management method for AI intelligent property and a property management system, the method is used for a control unit of the property management system, the control unit is connected with a database, and the method comprises the following steps: dividing a planar graph of a property community into three types of areas; obtaining three term sets of the three types of regions, obtaining intra-group noun results, and comparing the three term sets with the intra-group noun results to obtain three abnormal noun; and according to the three abnormal nouns, obtaining a corresponding property solution and sending the property solution to the mobile terminal. An existing property management company is prone to work omission when facing abnormal problems, and it is difficult to ensure that community owners obtain good service experience. According to the scheme provided by the invention, intelligent decision-making of property management can be realized for abnormal problems existing in the community.

Description

Technical Field

[0001] The present invention relates to the field of intelligent property management, and in particular to an abnormality management method and a property management system for AI intelligent properties. Background Art

[0002] As a property management company, it is crucial to maintain a good relationship with the owners of the community. The contract service period of a property management company is generally two to three years. During this service period, some community owners may express dissatisfaction and voices for changing the property management company will emerge. If no measures are taken to deal with such voices, the property management company will easily be replaced by the owners through voting at the next election.

[0003] Therefore, more and more property management companies are using intelligent software or systems to improve management efficiency during the service period. However, the property managers of property management companies are highly mobile and can only deal with routine problems reported by owners, but are prone to omissions in work when faced with abnormal problems, making it difficult to ensure that community owners receive a good service experience; therefore, the industry needs to design a property management solution to solve the above problems. Summary of the invention

[0004] The technical problem to be solved by the present invention is: how to design a property management solution that can achieve intelligent decision-making for property management in response to abnormal problems existing in a community.

[0005] In the process of providing solutions for property communities, the inventors discovered that the key reason why property management companies were unable to be re-elected in the election for a new term was the application of special funds for the community (limited funds). They failed to spend money on reasonable places for renovation, which led to dissatisfaction among most owners and thus failed to obtain votes from most owners. The application of special funds for the community was not only affected by the property owners' committee, but also by the owner group. Many owners would constantly strengthen their views in the owner group chat, causing the voices of most other owners to be drowned out. Therefore, the present invention proposes an abnormal management method and property management system for AI smart properties.

[0006] In a first aspect, the present invention proposes an abnormality management method for AI smart property, the method is used for a control unit of a property management system, the control unit is connected to a database, the method comprises: S1, dividing the floor plan of the property quarters into three types of areas; S2, obtaining three sets of terms for the three types of areas, and obtaining noun results within the groups, comparing the three sets of terms and the noun results within the groups, and obtaining three abnormal nouns; S3, obtaining corresponding property solutions according to the three abnormal nouns and sending them to a mobile terminal.

[0007] Its further technical solution is that S1 divides the floor plan of the property community into three types of areas, including: S11, obtaining a preset floor plan of the property community, and identifying a first area of ​​a first attribute, a second area of ​​a second attribute, and a third area of ​​a third attribute in the floor plan of the property community.

[0008] Its further technical solution is that S11 obtains the floor plan of a preset property district, identifies the first area of ​​the first attribute, the second area of ​​the second attribute, and the third area of ​​the third attribute in the floor plan of the property district, including: obtaining the floor plan of a preset property district, identifying the buildings of the first color with a color wheel parameter of 0-20, the public facilities of the second color with a color wheel parameter of 110-130, and the site areas of the third color with a color wheel parameter of 230-250 in the floor plan of the property district.

[0009] Its further technical solution is that, in S2, three sets of terms for three types of areas are obtained, and noun results within the groups are obtained, and the three sets of terms and noun results within the groups are compared to obtain three abnormal nouns, including: from the preset noun correspondence, a set of architectural noun terms included in the building, a set of facility noun terms included in the public facilities, and a set of regional noun terms included in the site area are obtained; from the chat information of the owner group, a list of the first number of speaking users within a preset time period is obtained, and N sentences within the preset time period are grouped based on the first number of speaking users, to obtain a first number of chat text groups ; Perform internal word frequency statistics within each of the first number of chat text groups, then cluster the results of the internal word frequency statistics to obtain clustered words, select a representative word for each of the second number of clustered words obtained after clustering, and then use the second number of representative words as the second number of in-group noun results; based on a preset intelligent semantic model, screen from the building noun term set, the facility noun term set, and the regional noun term set, and respectively screen out noun terms whose semantic similarity with the in-group noun results exceeds a preset threshold as abnormal nouns, and obtain abnormal building nouns, abnormal facility nouns, and abnormal regional nouns.

[0010] Its further technical solution is that S3, based on three abnormal nouns, obtains the corresponding property solutions and sends them to the mobile terminal, including: S31, selects part of the floor plans from the floor plans of all other communities in the database, obtains the property management reference information of the community corresponding to the partial floor plans, converts the property management reference information into a property solution and sends it to the mobile terminal.

[0011] Its further technical solution is that the database includes floor plans of property communities and floor plans of other communities; the S31 selects part of the floor plans from the floor plans of all other communities in the database, obtains property management reference information of the communities corresponding to the part of the floor plans, converts the property management reference information into a property solution and sends it to the mobile terminal, including: obtaining floor plans of all other communities in the database, converting the floor plans of all other communities into a floor plan set containing buildings of a first color, public facilities of a second color, and site areas of a third color; comparing the floor plan of the property community with each image in the floor plan set in turn, and obtaining a plurality of benchmark communities corresponding to the images with the highest color similarity; respectively Retrieve the graphic information of the decision-making processes of multiple benchmark communities, as well as the owner voting results corresponding to the graphic information of the decision-making processes for voting; identify the building abnormality decision reference information associated with the building abnormality noun, identify the facility abnormality decision reference information associated with the facility abnormality noun, and identify the regional abnormality decision reference information associated with the regional abnormality noun from the graphic information of the decision-making processes of multiple benchmark communities; determine whether the building abnormality decision reference information, the facility abnormality decision reference information, and the regional abnormality decision reference information correspond to the owner voting results; if none of the three types of reference information correspond to the owner voting results, send the building abnormality decision reference information, the facility abnormality decision reference information, and the regional abnormality decision reference information of multiple benchmark communities to the mobile terminal of the staff of the property owners' committee.

[0012] Its further technical solution is that the method also includes: if the three types of reference information correspond to at least one owner voting result, according to the correspondence between the decision process graphic information and the owner voting result, the building abnormality voting result corresponding to the building abnormality decision reference information, or the facility abnormality voting result corresponding to the facility abnormality decision reference information, or the regional abnormality voting result corresponding to the regional abnormality decision reference information is retrieved; the building abnormality decision reference information, facility abnormality decision reference information, regional abnormality decision reference information of multiple benchmark communities, and at least one of the building abnormality voting result, facility abnormality voting result, and regional abnormality voting result are all sent to the mobile terminal of the staff of the property owners' committee.

[0013] In a second aspect, the present invention provides a property management system, which is used to execute the abnormal management method as described in the first aspect. The property management system can realize intelligent decision-making of property management for abnormal problems existing in a community.

[0014] In summary, more and more property management companies are using intelligent software or systems to improve management efficiency during the service period to ensure that they can be "smoothly re-elected" when the next contract expires. However, the property managers of property management companies have a high turnover rate and can only deal with routine problems reported by owners. Once faced with abnormal problems, they are prone to work omissions, making it difficult to ensure that community owners have a good service experience. Based on this, the present invention proposes an abnormal management method and property management system for AI smart properties, which can achieve intelligent decision-making in property management for abnormal problems existing in the community. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0016] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0017] Figure 1 The present invention is a flowchart of the abnormal management method for AI smart property.

[0018] Figure 2 Another flowchart of the abnormal management method for AI smart property according to the present invention.

[0019] Figure 3 This is another flow chart of the abnormal management method for AI smart property according to the present invention.

[0020] Figure 4 A system schematic diagram of the property management system described in the present invention.

[0021] Figure 5 Another system schematic diagram of the property management system described in the present invention.

[0022] Figure 6 A schematic diagram of a framework of the electronic device described in the present invention. DETAILED DESCRIPTION

[0023] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0024] It should be understood that when used in this specification and the appended claims, the terms "include" and "comprises" indicate the presence of described features, integers, steps, operations, elements and / or components, but do not exclude the presence or addition of one or other features, integers, steps, operations, elements, components and / or combinations thereof.

[0025] It should also be understood that the terms used in the present specification are only for the purpose of describing specific embodiments and are not intended to limit the present invention. As used in the present specification and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include plural forms.

[0026] It should be further understood that the term "and / or" used in the present description and the appended claims refers to one or any combination and all possible combinations of the associated listed items, and includes these combinations.

[0027] As used in this specification and the appended claims, the term "if" may be interpreted as "when" or "upon" or "in response to determining" or "in response to detecting," depending on the context. Similarly, the phrases "if it is determined" or "if [described condition or event] is detected" may be interpreted as meaning "upon determination" or "in response to determining" or "upon detection of [described condition or event]" or "in response to detecting [described condition or event]," depending on the context.

[0028] Example 1 See also Figures 1 to 3 , among which Figure 1 The present invention provides a flowchart of an abnormality management method for AI smart property. The present invention provides an abnormality management method for AI smart property, the method is used for a control unit of a property management system, the control unit is connected to a database, and the method includes: S1, divide the floor plan of the property community into three types of areas.

[0029] S2, obtaining three term sets of three types of regions, and obtaining noun results within the group, comparing the three term sets and the noun results within the group, and obtaining three abnormal nouns.

[0030] S3, select a part of the floor plan from the floor plans of all other communities in the database, obtain the property management reference information of the community corresponding to the part of the floor plan, convert the property management reference information into a property solution and send it to the mobile terminal.

[0031] The technical effect of the abnormal management method described in S1 to S3 is that it can realize intelligent decision-making of property management for abnormal problems existing in the community. Optionally, the three term sets are respectively a building noun term set, a facility noun term set, and a regional noun term set; the three abnormal nouns are respectively building abnormal nouns, facility abnormal nouns, and regional abnormal nouns.

[0032] In one embodiment, see Figure 4 as well as Figure 5 As shown, the method is used for a control unit of a property management system, and the property management system also includes a database, and the control unit is connected to the database; in another embodiment, the property management system is connected to a database of an external device, specifically, the control unit is connected to a database of an external device.

[0033] In one embodiment, the step S1 divides the floor plan of the property community into three types of areas, including: S11, obtaining a floor plan of a preset property district, and identifying a first area of ​​a first attribute, a second area of ​​a second attribute, and a third area of ​​a third attribute in the floor plan of the property district.

[0034] Among them, the preset floor plan of the property community can be an electronic version. Those skilled in the art know the definition of the electronic version of the floor plan of the property community and can also obtain it through existing means.

[0035] In one embodiment, the step S11 of acquiring a floor plan of a preset property community and identifying a first area of ​​a first attribute, a second area of ​​a second attribute, and a third area of ​​a third attribute in the floor plan of the property community includes: S101, obtaining a preset floor plan of a property district, identifying buildings with a first color having a color wheel parameter of 0-20, public facilities with a second color having a color wheel parameter of 110-130, and site areas with a third color having a color wheel parameter of 230-250 in the floor plan of the property district.

[0036] After S101, see Figure 2 As shown, the abnormality management method for AI smart property includes: S102, obtaining three term sets for three types of areas, and obtaining noun results within the group, comparing the three term sets and the noun results within the group, and obtaining three abnormal nouns; S103, according to the three abnormal nouns, obtaining corresponding property solutions and sending them to the mobile terminal.

[0037] Among them, those skilled in the art know that the color wheel is Color-Wheel, and the color wheel parameters are parameters of Color-Wheel, and the unit is angle, and the value range of the color wheel parameters is 0 to 360. In the plan view of the property community, except for buildings and public facilities, the rest of the community area belongs to the site area; that is, the plan view of the property community includes the area outside the community, buildings, public facilities, and site area, and the latter three belong to the community area.

[0038] The technical effects of the above scheme include processing the floor plans of all other cells, avoiding errors caused by inconsistent semantic calibers, and then obtaining a plurality of benchmark cells, avoiding the defect of high error rate in screening cells, that is, the obtained benchmark cells are more accurate and more valuable for reference.

[0039] In one embodiment, see Figure 3 As shown, S2 obtains three sets of terms for three types of regions, obtains noun results within the groups, compares the three sets of terms and the noun results within the groups, and obtains three abnormal nouns, including: S201, obtaining, from preset noun correspondences, a set of architectural noun terms included in a building, a set of facility noun terms included in a public facility, and a set of regional noun terms included in a site area.

[0040] S202, obtaining a first number of speaking user lists within a preset time period from the chat information of the owner group, and grouping N sentences within the preset time period based on the first number of speaking user lists to obtain a first number of chat text groups.

[0041] S203, performing internal word frequency statistics on the first number of chat text groups, then clustering the results of the internal word frequency statistics to obtain clustered words, and selecting a representative word for each of the second number of clustered words obtained after clustering, and then using the second number of representative words as the second number of in-group noun results.

[0042] S204, based on the preset intelligent semantic model, screen from the building noun term set, the facility noun term set, and the regional noun term set, and respectively screen out the noun terms whose semantic similarity with the noun results in the group exceeds a preset threshold as abnormal nouns, and obtain abnormal building nouns, abnormal facility nouns, and abnormal regional nouns.

[0043] In the above scheme, the preset noun correspondence relationship is understandable to those skilled in the art; further, the acquisition of the set of architectural noun terms contained in the building, for example, the building includes a lobby, corridor, elevator, etc., all of which belong to the set of architectural noun terms and are also known in the art; similarly, the facilities include carports, pavilions, fitness equipment, garbage recycling stations, etc., and the areas include green belts, roads, pool areas, etc., all of which are known in the art.

[0044] In the above scheme, the first number of speaking user lists within a preset time period are obtained from the chat information of the owner group, that is, within the preset time period, all chat information of the owner group (such as WeChat group) is indiscriminately selected, and the senders of these chat information constitute the speaking user list.

[0045] The N sentences within the preset time period are grouped based on the first number of speaking user lists, that is, the text sentences of the same user in the speaking user lists are grouped as one group; therefore, the number of chat text groups corresponding to the ten speaking user lists is also ten, even if one of the users speaks more and accounts for more than half, there is only one chat text group corresponding to the user in the end.

[0046] Furthermore, the internal word frequency statistics within each group, that is, the scope of the internal word frequency statistics does not exceed the chat text group, and each chat text group does not interfere with other groups. The first number is greater than or equal to the second number, because clustering means partial merging, and after clustering, the first number is reduced to the second number.

[0047] The first number of chat text groups are subjected to internal word frequency statistics within each group, and then the results of the internal word frequency statistics are clustered to obtain clustered words. The results can be semantically clustered or synonyms can be merged (the degree of semantic similarity can be customized); the second number of noun results within the groups are all representative words or nouns.

[0048] In one embodiment, the abnormal building nouns, abnormal facility nouns, and abnormal regional nouns correspond to lobby, carport, and green belt, respectively, that is, the abnormal building noun (lobby), the abnormal facility noun (carport), and the abnormal regional noun (green belt). The inventor distinguishes the three in the scheme because the public opinion of the owner group is randomly guided, and different owners have different concerns. Owners with loud voices will express their wishes in a stronger way, and the weight of the topic heat distribution will be destroyed through frequent group chats. In the case of limited special funds for community property, it affects the topics that should have been discussed.

[0049] For example, when disputes arise in the lobby, carport, and green belt (if there are disputes in reality, the group chat will discuss these three topics and thus be captured), considering that discussing the renovation of the carport all the time will be biased, and owners with electric vehicles and owners without electric vehicles can easily "argue" in the owner group, resulting in a small number of speeches by owners who are concerned about the renovation of the lobby and the renovation of the green belt being covered up (the votes of these owners are easily lost). In addition, the property managers in the owner group have a large and unstable turnover, and it takes a lot of time to read the chat records of the owners one by one. Even if they really take the time to read them, it is difficult to fully identify which issues the owners really care about, that is, which issues are urgently in need of renovation. Based on the above-mentioned problems, the solution described in the present invention significantly improves the efficiency of identifying owner topics, avoids the omission of property management decisions due to the random divergence of public opinion in the owner group, and is conducive to ensuring that more community owners have a good service experience, thereby helping to increase the probability of the property management company being re-elected in the next election.

[0050] In one embodiment, S3, according to the three abnormal terms, obtains corresponding property solutions and sends them to the mobile terminal, including: S31, select a partial floor plan from the floor plans of all other communities in the database, obtain property management reference information of the community corresponding to the partial floor plan, convert the property management reference information into a property solution and send it to the mobile terminal.

[0051] In one embodiment, the step S31, selecting a partial plan from the plan of all other communities in the database, obtaining property management reference information of the community corresponding to the partial plan, converting the property management reference information into a property solution and sending it to the mobile terminal, includes: S301, obtaining the floor plans of all other communities in the database, and converting the floor plans of all other communities into a floor plan set including buildings of a first color, public facilities of a second color, and site areas of a third color.

[0052] S302, comparing the floor plan of the property community with each image in the floor plan set in turn, and obtaining a plurality of benchmark communities corresponding to the images with the highest color similarity.

[0053] S303, respectively retrieve the decision-making process graphic information of multiple benchmark communities, and generate the owner voting results corresponding to the decision-making process graphic information.

[0054] S304, identifying building anomaly decision reference information associated with building anomaly nouns, identifying facility anomaly decision reference information associated with facility anomaly nouns, and identifying area anomaly decision reference information associated with area anomaly nouns from the decision process graphic information of multiple benchmarking communities.

[0055] S305, determining whether the building abnormality decision reference information, the facility abnormality decision reference information, and the area abnormality decision reference information correspond to the owner's voting result.

[0056] S306: If none of the three types of reference information corresponds to the owner's voting results, the building abnormality decision reference information, facility abnormality decision reference information, and regional abnormality decision reference information of multiple benchmark communities are sent to the mobile terminal of the staff of the property owners' committee.

[0057] In the above scheme, the benchmark community is the name of the residential community; among the decision-making process graphic information of multiple benchmark communities, there are two situations, the first is the decision-making process graphic information without voting, and the second is the decision-making process graphic information for generating voting. The above method retrieves the "decision-making process graphic information for generating voting" without paying attention to the decision-making process graphic information for generating voting. Among them, step S303 retrieves the owner's voting results corresponding to the decision-making process graphic information for generating voting as a whole (this step is not subdivided); however, which reference information corresponds to the owner's voting results and which reference information does not correspond can only be obtained after the judgment of step S305.

[0058] In the above scheme, the database may be a database of a property management company, and the property management company itself may obtain or own the floor plans of its own property districts and other districts. The floor plan of the property district is sequentially compared with each image in the floor plan set, which may be at the same scale or at different scales; the comparison may be a color comparison or a color similarity comparison, and the definition of color similarity is known in the art, for example, crimson is similar to vermilion under most conditions, but not under certain conditions.

[0059] In the above scheme, the decision-making process graphic information of multiple benchmark communities is retrieved respectively, which can be a record of the resolution of the property management committee, a property announcement, or a record of the resolution plus a property announcement; the number of the multiple benchmark communities can be any integer greater than 3, for example, 5, 10, or 50, which can be defined by the property management company or the property management committee according to the workload. The reference information for identifying building abnormality decisions associated with building abnormality nouns can be reference information for identifying original words containing building abnormality nouns, or reference information for identifying words whose semantic similarity with building abnormality nouns is greater than a threshold.

[0060] In one embodiment, the abnormality management method for AI smart property further includes: S307, if the three types of reference information correspond to at least one owner voting result, based on the correspondence between the decision process graphic information and the owner voting result, retrieve the building abnormality voting result corresponding to the building abnormality decision reference information, or the facility abnormality voting result corresponding to the facility abnormality decision reference information, or the area abnormality voting result corresponding to the area abnormality decision reference information.

[0061] S308, sending the building abnormality decision reference information, facility abnormality decision reference information, regional abnormality decision reference information of multiple benchmark communities, and at least one of the building abnormality voting results, facility abnormality voting results, and regional abnormality voting results to the mobile terminal of the property management committee staff.

[0062] In the above scheme, if the three types of reference information correspond to at least one owner voting result, that is, the building abnormal decision reference information, the facility abnormal decision reference information, and the regional abnormal decision reference information (three types of reference information in total), in the previous discussion of other communities, in addition to the decision-making process, there is also a community where the owner voted, or two communities, or three communities. Among them, the correspondence between the decision-making process graphic information and the owner voting results, that is, the discussion and voting on the same topic, the property has relevant records, which can be obtained by technical personnel in this field.

[0063] The embodiment of the present invention further provides a property management system, wherein the control unit of the property management system is used to execute the abnormal management method as described in any of the above embodiments. The function of the property management system is to realize intelligent decision-making of property management for abnormal problems existing in a community.

[0064] In summary, more and more property management companies are currently using intelligent software or systems to improve management efficiency during the service period; however, the property managers of property management companies have high mobility and can only deal with routine problems reported by owners, but are prone to work omissions when faced with abnormal problems, making it difficult to ensure that community owners have a good service experience; based on this, the present invention proposes an abnormal management method and property management system for AI smart properties, which can achieve intelligent decision-making for property management in response to abnormal problems existing in the community.

[0065] Example 2 See also Figure 6 , Figure 6 This is a block diagram of an electronic device provided by the present invention. The electronic device can be a terminal or a server, wherein the terminal can be an electronic device with communication functions such as a smart phone, a tablet computer, a laptop computer, a desktop computer, a personal digital assistant, and a wearable device.

[0066] It includes a processor 111 , a communication interface 112 , a memory 113 , and a communication bus 114 , wherein the processor 111 , the communication interface 112 , and the memory 113 communicate with each other via the communication bus 114 .

[0067] The memory 113 is used to store computer programs.

[0068] In one embodiment of the present invention, the processor 111 is used to implement the method provided by any one of the aforementioned method embodiments when executing the program stored in the memory 113 .

[0069] It should be understood that in the embodiment of the present application, the processor 111 may be a central processing unit (CPU), and the processor 502 may also be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. Among them, the general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0070] It is understood by those skilled in the art that all or part of the processes in the method for implementing the above embodiment can be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a storage medium, which is a computer-readable storage medium. The computer program is executed by at least one processor in the computer system to implement the process steps of the embodiment of the above method.

[0071] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in the above description according to function. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions, but such implementation should not be considered to be beyond the scope of the present invention.

[0072] In the several embodiments provided by the present invention, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of each unit is only a logical function division, and there may be other division methods in actual implementation. For example, units or components can be combined or integrated into another system, or some features can be ignored or not executed.

[0073] The steps in the method of the embodiment of the present invention can be adjusted in order, combined and deleted according to actual needs. The units in the device of the embodiment of the present invention can be combined, divided and deleted according to actual needs. In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0074] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a storage medium. Based on this understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, terminal, or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention.

[0075] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0076] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

[0077] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed by the present invention, and these modifications or replacements should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be based on the protection scope of the claims.

Claims

1. An abnormality management method for AI smart property, characterized in that: The method is used for a control unit of a property management system, the control unit is connected to a database, and the method comprises: S1, divide the floor plan of the property community into three types of areas; S2, obtaining three sets of terms for three types of regions, obtaining noun results within the groups, comparing the three sets of terms and the noun results within the groups, and obtaining three abnormal nouns; S3, based on the three abnormal nouns, obtain the corresponding property solutions and send them to the mobile terminal.

2. The abnormality management method for AI smart property according to claim 1 is characterized in that: S1 divides the floor plan of the property community into three types of areas, including: S11, obtaining a floor plan of a preset property district, and identifying a first area of ​​a first attribute, a second area of ​​a second attribute, and a third area of ​​a third attribute in the floor plan of the property district.

3. The abnormality management method for AI smart property according to claim 2 is characterized in that: The step S11, obtaining a floor plan of a preset property community, and identifying a first area of ​​a first attribute, a second area of ​​a second attribute, and a third area of ​​a third attribute in the floor plan of the property community, includes: A preset floor plan of a property district is obtained, and buildings of a first color with a color wheel parameter of 0-20, public facilities of a second color with a color wheel parameter of 110-130, and site areas of a third color with a color wheel parameter of 230-250 are identified in the floor plan of the property district.

4. The abnormality management method for AI smart property according to claim 3 is characterized in that: S2, obtains three sets of terms for three types of regions, obtains noun results within the groups, compares the three sets of terms and the noun results within the groups, and obtains three abnormal nouns, including: From the preset noun correspondence, obtain the building noun term set contained in the building, the facility noun term set contained in the public facility, and the regional noun term set contained in the site area; Obtaining a first number of speaking user lists within a preset time period from the chat information of the owner group, and grouping N sentences within the preset time period based on the first number of speaking user lists to obtain a first number of chat text groups; Performing internal word frequency statistics within each of the first number of chat text groups, clustering the results of the internal word frequency statistics to obtain clustered words, selecting a representative word from each of the second number of clustered words obtained after clustering, and then using the second number of representative words as the second number of in-group noun results; Based on the preset intelligent semantic model, the noun terms whose semantic similarity with the noun results in the group exceeds the preset threshold are screened out as abnormal nouns from the architectural noun term set, the facility noun term set, and the regional noun term set, and the abnormal architectural nouns, the abnormal facility nouns, and the abnormal regional nouns are obtained.

5. The abnormality management method for AI smart property according to claim 4 is characterized in that: S3, according to the three abnormal terms, obtains the corresponding property solutions and sends them to the mobile terminal, including: S31, select a partial floor plan from the floor plans of all other communities in the database, obtain property management reference information of the community corresponding to the partial floor plan, convert the property management reference information into a property solution and send it to the mobile terminal.

6. The abnormality management method for AI smart property according to claim 5 is characterized in that: The database includes the floor plan of the property community and the floor plans of other communities; S31, selecting a part of the floor plans from the floor plans of all other communities in the database, obtaining property management reference information of the community corresponding to the part of the floor plan, converting the property management reference information into a property solution and sending it to the mobile terminal, includes: Obtain the floor plans of all other communities in the database, and convert the floor plans of all other communities into a set of floor plans including buildings of the first color, public facilities of the second color, and site areas of the third color; The floor plan of the property community is compared with each picture in the floor plan set in turn to obtain multiple benchmark communities corresponding to the pictures with the highest color similarity; Retrieve the graphic information of the decision-making process of multiple benchmark communities, and the voting results of the owners corresponding to the graphic information of the decision-making process for voting; From the decision process graphic information of multiple benchmarking communities, identify the building abnormality decision reference information associated with the building abnormality noun, identify the facility abnormality decision reference information associated with the facility abnormality noun, and identify the regional abnormality decision reference information associated with the regional abnormality noun; Determine whether the building abnormal decision reference information, facility abnormal decision reference information, and regional abnormal decision reference information correspond to the owner's voting results; If none of the three types of reference information corresponds to the owner's voting results, the building abnormal decision reference information, facility abnormal decision reference information, and regional abnormal decision reference information of multiple benchmark communities will be sent to the mobile terminal of the property owners' committee staff.

7. The abnormality management method for AI smart property according to claim 6 is characterized in that: The method further comprises: If the three types of reference information correspond to at least one owner voting result, the building abnormality voting result corresponding to the building abnormality decision reference information, or the facility abnormality voting result corresponding to the facility abnormality decision reference information, or the regional abnormality voting result corresponding to the regional abnormality decision reference information is retrieved according to the correspondence between the decision process graphic information and the owner voting result; The building abnormality decision reference information, facility abnormality decision reference information, regional abnormality decision reference information of multiple benchmark communities, and at least one of the building abnormality voting results, facility abnormality voting results, and regional abnormality voting results are all sent to the mobile terminal of the property management committee staff.

8. A property management system, characterized in that: The property management system is used to execute the abnormality management method as described in any one of claims 1 to 7.

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