KR102066196B1 - System and method for analyzing and processing defects in apartment houses using artificial intelligence based on machine learning algorithm - Google Patents

Abstract

The present invention relates to a system and method for analyzing and processing defects of apartment houses by using artificial intelligence based on a machine learning algorithm. According to the present invention, when information on a defect generated in an apartment house and information on a facility material where a defect is generated are registered, a defect repair processing model for estimating a defect repair method for the facility material where the defect is generated, a type of a facility material to be used for defect repair, and a defect repair company to perform the defect repair is generated by machine learning the registered facility material and information on the defect with respect to a corresponding facility material, properties of the facility material where the defect is generated, the defect repair method for the defect, the type of the facility material to be used for the defect repair, a name of the defect repair company, evaluation content for a result of processing the defect repair, and whether defect repair is re-requested, and a defect repair method suitable for a corresponding defect, a facility material to be used for the defect repair, and a defect repair company can be customized and recommended by applying the information on the defect, which is registered in a manager or a resident terminal, to the defect repair processing model.

Description

SYSTEM AND METHOD FOR ANALYZING AND PROCESSING DEFECTS IN APARTMENT HOUSES USING ARTIFICIAL INTELLIGENCE BASED ON MACHINE LEARNING ALGORITHM}

The present invention relates to a system and method for analyzing and processing faults in apartment houses using artificial intelligence based on a machine learning algorithm, and more particularly, to construct various types of faults generated in apartment houses as big data, and The present invention relates to a system and method for analyzing and processing defects of a multi-family house which automatically analyzes the machine learning algorithm using a machine learning algorithm and then presents an appropriate defect repair method using artificial intelligence based on the machine learning algorithm.

In Korea, the lack of housing has emerged as a social problem due to the rapid increase in the population and the concentration of population in large cities since the rapid industrialization and urbanization since the 1960s. In order to resolve such housing shortages, we have supplied large quantities of supply-oriented apartments. As housing prices stabilize and housing prices stabilize with the increase in the number of apartments, the consumer's awareness of housing is rapidly changing to higher quality and higher functionality.However, the commodity, which is composed of a variety of materials and components, is a construction environment, a related system, Constructed by a complex process, there is a limit to the complete supply of multi-family housing, and thus various defects occur.

Multi-family housing is defined by the Housing Management Decree as "multi-family housing of more than 300 households", "multi-family housing with lifts," or "central housing with central heating." The legal grounds related to defects occurring in such apartments are prescribed by the Civil Law, Collective Building Act, Housing Act, and Basic Act on Construction Industry.The Housing Act describes defects as “cracking, sagging, torsion, settlement, damage, collapse, leakage due to construction errors. , Defects such as leaks, malfunctions in operation or function, poor attachment or grounding, poor test, and poor granularity may cause malfunctions in buildings, facilities, aesthetics, or safety. ”

The following is the analysis of the types of defects in the construction work, window work, furniture work, and paint work, which show a high incidence among construction defects.

(1) Paper work

The most common occurrence rate of construction works showed 24.45% of tearing papers, followed by seam defects of 20.89%, uplift of 15.01%, and base surface defects of 10.97%.

(2) Window construction work

Window construction works are divided into wood windows and PL windows according to the materials of windows. First, the types of defects of wood windows are the most common defects of the wrapping paper attached to the surface of wood windows (28.38%). The incidence rate was 19.63% and 9.81% caulking failure. In the case of PL windows, the most frequent occurrence of mud crevices was 28.96%, with PL caulking defects 26.34%, crescent defects 10.37%, and piece cover defects 9.42%.

(3) Painting work

In the painting work, the most frequent occurrence rate is 41.01% of the base surface of the coating, and 35.85% of the defective coating condition and 12.37% of the defects are caused by the poor surface.

(4) Furniture construction

In the case of furniture construction, the most common gap was 22.50% at the separation distance between the installed furniture and the wall or other furniture.The vertical and horizontal defects of the furniture installation were 21.70%, and 20.20% of the unconstructed constructions according to the site conditions. Opening and closing faults of drawers and doors are 9.5%.

The above-mentioned repairs for various types of defects can be identified by the tenant or manager, and the apartment management office submits the documents documenting the defects, the apartment management office classifies the defects, and notifies the apartment builders according to the classification. Internally, the process is performed.

In this process, the tenant should record where the defect occurred in the defect record document, and the management office classifies the document into annual, sector, and facility (by location) and organizes it into a file folder for further processing.

Existing defect management process is manual, and there is a problem that the defects cannot be repaired in a timely manner due to lack of records, errors in classification, and errors in document management.

In addition, the types of defects and the types of facility materials used for repair are so diverse that it is difficult to manage them systematically, and which facility materials should be selected and applied in order to repair them. It is not easy to judge how to repair the defect using the equipment and whether it is good to ask the repair company for the repair. As a result, tenants or managers frequently request defect repairs after repairs are completed.

This is because even the same type of defects may have different causes of generational defects, and different methods for repairing defects may be caused.

Recently, a system for managing defect reception, management, and defect repair using mobile has been developed. However, such a mobile defect repair system is convenient only in that it can be easily received by requesting a fault repair in a generation. It does not provide customized defect repair service for each defect occurrence factor, the tenant's satisfaction is not high, and there is a problem that the cost of repairing defects takes much from the contractor's point of view.

Patent Registration No. 10-1078780 Patent Registration No. 10-1985889 Patent Publication No. 10-2015-0125787

The present invention was invented to improve the above problems, when receiving the defect information and defects occurred in the multi-unit housing facility information, the facility information and the defects occurred on the received facility materials and the corresponding facility materials Machine learning about the nature of the defects, the method of repairing the defect, the type of facility materials used for the repair, the name of the repair company, the evaluation results of the result of the repair, and whether or not to request repairs again. Create a repair process model that infers the repair method for the generated facility materials, the type of facility materials used for the repair, and the repair company that will perform the repair, and the defect information received from the manager or tenant's terminal. Applied to the repair treatment model, the defect repair method corresponding to the fault, the facility materials used for the repair and the fault The purpose of the present invention is to provide a system and method for analyzing and processing defects of apartment houses that can recommend self-repairing companies by using artificial intelligence based on machine learning algorithms.

In order to achieve the above object, the system for analyzing and processing the defect of the multi-family housing according to the present invention by using the artificial intelligence based on the machine learning algorithm, the defect information and defects generated in the multi-family housing from the terminal of the administrator or tenant A defect receiving unit for receiving facility material information; A defect classification recorder for classifying the defect information received by the defect receiving unit by facility material category and recording the defect information in a DB; Facility material management unit for matching the type of facility materials used or planned to be used in the apartment house and the properties of each facility material to store in the facility material DB; Defect repair company designation unit for designating a defect repair method for the defect received by the defect receiving unit, the type of facility materials used for the repair and the defect repair company to store in the defect repair company designated DB; A defect repair request unit for requesting a defect repair by transferring the received contents of the defect, a method of repairing a defect, and a kind of facility material used for the repair to a defect repair company designated by the defect repair company designation unit; When the designated defect repair company completes the defect repair, the manager or the tenant terminal receives the evaluation contents of the defect repair result and whether the repair is requested again, and stores the result in the defect repair result DB. Defect repair evaluation unit for re-requesting defect repair by delivering the relevant information to the defect repair company; Defective information on the facility materials and the corresponding facility materials recorded in the defect information DB, the nature of the facility material in which the defects are stored in the facility material DB, the method of repairing defects on the defects stored in the defect repair company designated DB, and defect repair Types of facility materials used, name of the repair company, and the contents of the evaluation of the repair results stored in the defect repair result DB and whether or not the request for defect repair is requested again. A repair process model generation unit for generating a repair process model for inferring a repair method and a type of facility material used for repair and a repair service provider to perform the repair; And applying defect information on the facility materials received by the defect receiving unit to the defect repair model, and a method for repairing defects received from a manager or a tenant's terminal, types of facility materials used for defect repair, and defect repair companies. Includes a defect repair method recommendation section.

On the other hand, in order to achieve the above object, the method of analyzing and processing the defect of the multi-family housing according to the present invention by using the artificial intelligence based on the machine learning algorithm, the defect information and defects generated in the multi-family house from the administrator or the tenant's terminal A defect reception step of receiving the facility material information that has occurred; A defect classification recording step of classifying the received defect information by facility material category and recording it in the defect information DB; Defect repair company designation step for designating defect repair method, type of facility materials used for defect repair and defect repair company and storing it in defect repair company designation DB; Defect repair request step that delivers the defect contents, defect repair method and the type of equipment used for the repair to the designated defect repair company to request the repair; When the designated defect repair company completes the defect repair, it receives the evaluation contents of the defect repair result from the administrator or the tenant's terminal and whether the defect is re-requested, and stores it in the defect repair result DB. Defect repair evaluation step of re-requesting defect repair by delivering related information to defect repair company; Defective information on facility materials recorded in the defect information DB and the corresponding facility materials, the nature of the facility material in which the defects are stored in the facility material DB, the method of repairing defects stored in the defect repair company designated DB, and the facilities used for the repair Type of material and defect repair company name and defect repair result The evaluation contents of the defect repair result stored in the DB and the machine repair (request of defect repair request) and the defect repair method and defects for the facility materials where the defect occurred. A step of generating a repair process model for generating a repair process model for inferring a type of facility material used for repair and a repair service for performing the repair work; And applying defect information on the received facility materials to the above-mentioned repair model for defects, and recommending a method for repairing defects received from the terminal of the manager or tenant, types of facility materials used for the repair, and defect repair companies. Repair method recommendation step.

According to the present invention having the above configuration, the following effects can be achieved.

First of all, upon receiving mobile / online defect information and facility material information from the manager or tenant, the defect is repaired by designating the method for repairing the defect, the type of facility material used for the defect repair, and the repair company. If the defect is not satisfactory through evaluation of the defect repair process, collect various information about the entire process of requesting the defect repair as big data, and collect the collected big data into machine learning ( Machine Learning) By using artificial intelligence based on algorithm, defect repair method that can infer the defect repair method for the defected facility material, the type of facility material used for the defect repair, and the defect repair company suitable for the defect repair You can create a model.

Using such a repair model, the defect repair method for defects received from the manager or tenant's terminal, the type of facility materials used for the repair, and a defect repair company suitable for repairing the defect are customized. You can do it.

After all, even if the same type of defects are used in different repair methods and repairs, considering the various situations such as the direction of the home of the household where the defect occurred, such as trend, west, south, or north, the weather at the time of the defect, etc. Since the facility materials and defect repair companies can be recommended, the tenant's satisfaction with the result of the defect repair process is increased, and the construction company can reduce the trouble and cost of having to repair the defect again.

In addition, if the types of facility materials that can be used for the repair of the defect and the method of repairing the defects using the facilities are limited compared to the types of facility materials that can be used for other types of repair, the properties of the facilities are similar. If the quality of facilities is different, we can recommend companies that are good at repairing defects.If the properties of facility materials are different from each other, we can place more weights on the properties of facilities. I can recommend it.

In summary, since all work on the reception and processing of defects is done on the web and mobile basis, it is convenient to use and can be quickly processed, and because big data is learned and analyzed by machine learning algorithms, More precisely, the more accurate defects can be processed and the cloud-based services can be used to minimize human resources and costs.

1 is a block diagram of a system for analyzing and processing defects in a multi-family house according to an exemplary embodiment of the present invention using artificial intelligence based on a machine learning algorithm.
2 is a flow chart of a method for analyzing and processing defects in a multi-family house according to an exemplary embodiment of the present invention using artificial intelligence based on a machine learning algorithm.
3 is a flow chart of a method for generating a first repair process model and a second repair process model when generating a repair process model based on a machine learning algorithm according to a preferred embodiment of the present invention.
4 is a flowchart of a method for generating a third defect repair model and a fourth defect repair model when generating a repair process model based on a machine learning algorithm according to a preferred embodiment of the present invention.

Advantages and features of the present invention, and methods for achieving them will be apparent with reference to the embodiments described below in detail with reference to the accompanying drawings.

However, the present invention is not limited to the embodiments disclosed below, but may be implemented in various different forms.

In this specification, the embodiments are provided so that the disclosure of the present invention may be completed and the scope of the present invention may be completely provided to those skilled in the art.

And the present invention is only defined by the scope of the claims.

Thus, in some embodiments, well known components, well known operations, and well known techniques are not described in detail in order to avoid obscuring the present invention.

In addition, the same reference numerals throughout the specification refer to the same components, and the terminology (discussed) used herein is for the purpose of describing the embodiments are not intended to limit the invention.

As used herein, the singular forms "a", "an" and "the" include plural unless the context clearly dictates otherwise, and the elements and acts referred to as 'comprises' or 'do' not exclude the presence or addition of one or more other components and acts. .

Unless otherwise defined, all terms used in the present specification (including technical and scientific terms) may be used as meanings that can be commonly understood by those skilled in the art.

In addition, the terms defined in the commonly used dictionary are not ideally or excessively interpreted unless they are defined.

Hereinafter, with reference to the accompanying drawings will be described a preferred embodiment of the present invention.

Referring to FIG. 1, a system for analyzing and processing a defect of an apartment house using artificial intelligence based on a machine learning algorithm includes a terminal 100 used by a manager or a tenant and a defect processing server 200 operated by a construction company. do. The terminal 100 is installed with a dedicated app 110 that can receive a defect repair, the defect receiving app 110 provides a convenient interface for receiving various types of defects occurred in the apartment house, taking a picture of the defect There is also a function to upload.

The defect processing server 200 includes a big data processing system and has a function of performing various analyzes and inferences on defect repair using a machine learning algorithm.

The defect processing server 200 is a defect receiving unit 210, a defect classification recorder 220, a facility material management unit 230, a defect repair company designation unit 240, a defect repair request unit 250, a defect repair evaluation unit 260 ), The defect repair process model generation unit 270 and the defect repair method recommendation unit 280. In addition, the household floor plan management unit 290, the weather information management unit 300 and the defect occurrence situation determination unit 310 may be further provided.

The defect receiving unit 210 receives defect information generated in the apartment house and facility material information in which the defect occurred from the terminal 100 of the manager or the tenant.

Explaining the paperwork as an example, defects that are mainly generated in paperwork are tearing of paper, seam failure, lifting, poor surface, poor adhesion, poor finish, and the like.

Bad surface of the paper is mainly caused by neglected construction and use of improper materials by the paperworker, and the area where the surface of the seam is smoothly contacted with smooth paste must be kept straight so that the cutting is advantageous. In addition, it is necessary to carefully select the medium considering the construction environment. In this case, the defect on the joint surface of the island becomes the defect information, and the island corresponds to the information of the facility material where the defect occurred.

Lifting paper medium is caused by poor quality of the surface before construction, poor construction quality due to low temperature during construction, and poor construction. The paper work is the finishing process, and the smoothness of the ground has a big influence. Therefore, the mortar base is finished with chaebol and jeongbeomil, and the edges, corners, corners, etc. are evenly selected, the angles are applied accurately and smoothly, and the cracks are filled with putty. In addition, the construction time of the construction work is preferable to avoid the winter season, by the input of skilled skilled workers can prevent the lower due to immature construction. Here, the uplifting site becomes the defect information, which corresponds to the information of the facility material where the defect occurred.

Poor adhesion and finishing defects of paper media are caused by unfaithful construction of paperworkers and lack of adhesion of paperwork pools. It is necessary to check the quality of the paperwork for the paperwork and precisely close installation of paperworkers. Here, bad paper adhesion and bad paper finishing are defective information, and the paper is the information of the facility material where the bad paper occurred.

As described above, the defect receiving unit 210 may receive various defect information and facility material information having a defect related to the papering work occurring in the apartment house from the manager or the tenant's terminal 100.

Wastewater Resources and Measures Defect Type cause Measures
Tearing -Carelessness of other process technicians
-Lack of rehabilitation after construction
Inappropriate choice of medium -Pre-training and supervision of skilled workers
-Installation of rejuvenation material after completion of flood work
-Use of durable paper Bad joint -Construction by unskilled workers
-Lack of adhesion of paper paste -Input of skilled craftsmen
-Material quality check of papering pool
Uplifting -Bad surface quality
-Improper construction environment
-Construction by unskilled workers -Thoroughly inspect and clean the surface smoothness before construction
-Winter construction is prohibited
-Input of skilled craftsmen Poor Adhesion / Poor Finish -Lack of adhesion of paper paste
-Construction by unskilled workers -Material quality check of papering pool
-Input of skilled craftsmen

On the other hand, if the coating work to be described as an example, the defect type of the coating is generated in the order of bear, poor coating state, poor surface, unconstructed, voids. When painting, the suitable temperature is 15 ~ 30 ℃ and the humidity is 75% or less. Particular care should be taken during rainy and winter construction to prevent discoloration due to climate.

Here, the information of defects, poor painting conditions, poor cotton, etc. becomes defect information, and the painting corresponds to the information of the facility material where the defects occurred.

Subsidiaries and Countermeasures of Painting Works Defect Type cause Measures Poor paint
Defect -Bad background
-Construction under undried surface
-Improper use of paint
-High temperature and high humidity construction environment -Thoroughly putty work
-Construction after checking surface dry
-Selection of materials in consideration of types, ingredients, properties, diluents, etc.

In many apartments there are many similar defects of almost the same type, and the same continues. The causes of such defects are caused by neglect of supervision on site, construction by unskilled workers, inadequate construction environment, defects in materials and lack of inspection.

In the above, it was confirmed about the various defect information received by the defect receiving unit 210 and the information on the facility materials in which the defect occurred. The present invention relates to the contents of analyzing the defects based on the machine learning algorithm based on artificial intelligence and suggesting an appropriate defect repair method.

The defect classification recorder 220 classifies the defect information received by the defect receiving unit 210 by facility material category and records the defect information in the DB.

Facility material management unit 230 matches the type of facility materials used or planned to be used in the apartment house and the properties of each facility material to store in the facility material DB. Facility materials DB is the property of all materials used in multi-unit houses, that is, whether the material is strong or weak in the summer, should be careful in summer or winter, strong or weak in humidity, easy to discolor or not discolored, durability The properties of all facility materials are matched and stored, such as strong or weak.

Defect repair company designation unit 240 designates a defect repair method for the defect received by the defect receiving unit 210, the type of facility materials used for the repair and the defect repair company and stores in the defect repair company designation DB. When a defect is received from the manager or the tenant's terminal 100, the contractor's defect repair manager designates the appropriate defect repair method, facility materials used for the defect repair, and a defect repair company to be responsible for the defect repair. Store it in the designated defect repair company DB.

For example, when a defect repair manager receives a defect about a lifted up paper and photographs of the defected part, he / she designates a method of flooding the excited part, a paper used for the excited part, and a paper company to perform the flood work. Store in the defect repair company designated DB.

If the defect requesting unit 250 delivers the defect contents received above, the defect repairing method, and the type of facility material used for the defect repair to the defect repair company designated by the defect repair company designation unit 240, the defect repair request is made. The contents are sent to the administrator terminal of the defect repair company.

The defect repair evaluation unit 260, upon completion of the defect repair by the designated defect repair company, receives the evaluation contents of the defect repair result and the request for repair of the defect from the administrator or the tenant terminal 100, and shows the defect repair result DB. If you request to repair the defect, you will be requested to repair the defect by delivering the relevant information to the repair company. The evaluation may be given a score such as 50 to 100 points, or may be given a grade such as A to D. If the result of defect repair is insufficient after assigning score or grade, the repair may be requested again. If the result of the repair is satisfactory, the repair can be completed. Such evaluations and re-requests are stored in the defect repair result DB.

Defect repair model generation unit 270 is a defect information on the facility material and the corresponding facility material recorded in the defect information DB and the nature of the defect occurred in the facility material DB and the defects stored in the defect repair company designated DB Defect repair method, machine type used for defect repair, name of defect repair company, defect assessment result of DB repair result stored in DB and machine learning Create a repair process model that infers the repair method for the generated facility materials, the type of facility materials used for the repair, and the repair company to perform the repair.

Defect repair model generation unit 270 uses a model consisting of a number of parameters, facilities that occurred by using a variety of data stored in the defect information DB, facility materials DB, defect repair company designated DB, defect repair processing result DB We will learn how to optimize the defect repair method for materials, the types of facility materials used for defect repair, and the defect repair company to perform the repair.

The defect repair model generation unit 270 performs supervised learning. Supervised learning is a method of machine learning to infer a function from training data.

Supervised learning has a variable to predict in the data, that is, the result value (y), and it is used to learn the combination of input variables (x) to make y = f (x) function that can predict y value as best as possible. . By knowing the exact y values, we can evaluate how well we have learned.

For example, the cause of the occurrence of the uplift corresponding to the defect of the paperwork is not one of the causes, but there are various types of defects according to various situations of each generation. Also, the properties of the paper are different, such as whether they are resistant to heat, weak to heat, strong to humidity, or weak to humidity. As a result, there may be various defect repair methods for repairing floating land according to each generation situation.

In addition, the skill of the company performing the repair of the paper may also be different. As we will see below, different generations use the same paper at the same time, and even in the event of uplifting, the direction of the house is a trend, so the sun is too hot in the morning and the direction of the house is south, so the sun is relatively hot. How to repair a house that has not been lifted is the quality of the paper may vary depending on the proficiency of the company performing the repair and the quality and price of the paste applied to the paper.

Defect repair model generation unit 270 is to determine the name of the site where the defect occurred, various types of defects of the site, the nature of the various site, the address of each generation where the defect occurred, the location of the household where the defect occurred, the location of the household, the direction and weather conditions Such as various defect repair methods considered, names of various vendors, proficiency of defect handling through the evaluation, evaluation contents of the defects, and whether or not they are requesting repairs for defects or are satisfied with the defect repair results. By using various data as input variables (x), we generate a repair process model that predicts the result (y).

The result of the repair method to be used for the paper defect and the paper company to handle the fault may correspond to the result value (y). In addition, the result value y may include a paper used for the repair of defects. By machine learning using various defect-related data, a defect repair model such as y = f (x) is generated.

In the present invention, it is preferable to use a classification model among a classification model and an estimation model of supervised learning.

The classification model has an input variable (x) and a target variable (y), which combines x variables to create a function that predicts the variable (y '). In other words, it predicts the y 'variable as yes or no. That is, as described above, a defect repair method is used to predict a defect repair method using a combination of various defect related data, a paper used for defect repair, and a contractor to handle the fault repair.

Since the probability can be predicted as yes based on 0.5 or more and 0.5 or more and 0.5 or more, the prediction result may not be one but several. In other words, the predicted result using the defect repair process model is that y1 = {processed by the C contractor using the D defect repair method using the A and B paper pools}, y2 = {using the A and E paper pools There are two ways that the F dealer can deal with the D defect repair method. Of course, the prediction result may be more, and the repair method recommendation unit 280 to be described below will recommend any one of these.

The criterion of probability (0.5) can be adjusted slightly to suit each analysis result while analyzing. As an analysis method, any one of logistic regression, SVM, and random forest can be used.

The defect repair method recommendation unit 280 applies the defect information on the facility materials received by the defect receiving unit 210 to the defect repair process model, and the defect repair method for the defect received from the terminal 100 of the manager or the tenant, We recommend the type of facility materials used for the repair and the repair company. Recommend the prediction result of the repair process model, and if there are several prediction results, one of them can be recommended.

If the defect repair method recommendation unit 280 recommends a defect repair method, a type of facility material used for defect repair, and a defect repair company, the defect repair company performs the repair, and the manager or tenant After the evaluation, the defect repair model generation unit 270 can also increase the prediction accuracy of the defect repair model by machine learning the process for recommendation and evaluation.

The household floor plan management unit 290 stores floor plan information for each household of the multi-family house in a floor plan DB, and receives the address information from the manager or resident's terminal 100, such as 101 apartment 1201, Hannam-dong, Yongsan-gu, the address. Search in the floor plan DB to display the floor plan of the Korean apartment 101 101 1201, Hannam-dong, Yongsan-gu, where a defect occurred in the terminal 100 of the manager or the tenant.

When the manager or tenant's terminal 100 inputs the above address information in the defect receiving app 110, the household floor plan manager 290 searches for the household floor plan of the corresponding address in the floor plan DB by the manager or the tenant's terminal 100 ), And the defect application app 110 displays the floor plan.

The floor plan of the household where the defect has occurred is automatically displayed on the input screen of the defect application app 110, and the defect information is inputted by clicking the position where the defect has occurred in the floor plan received by the household floor plan manager 290. In the floor plan, several rooms can be displayed. Among them, click the exact location where the defect occurred and input defect information. The defect information can be written and entered directly, but it can also be entered by selecting a detailed defect by using a tree type menu. At this time, photographs of defects can be taken and uploaded.

Through such a process, the defect receiving unit 210 receives information on the location of the defect in the floor plan of the household where the defect has occurred, information on the facility material having the defect, and defect information.

In detail, the household floor plan manager 290 stores floor plan information for each household and direction information of the house for each household in the apartment house together in the floor plan DB. For example, 101, 1201, Korea Apartment 101-dong, Hannam-dong, Yongsan-gu, stores the direction of west, south, north. Of course, there may be more directions, such as southeast.

The defect receiving unit 210 receives information on the location of the defect from the floor plan of the household where the defect has occurred, facility material information and defect information on which the defect has occurred at the manager or tenant's terminal 100, and at the household floor plan management unit 290. Further information about the direction of the house is received using the location of the household where the defect occurred. Depending on the direction of the house, the degree of sunshine is different depending on the season, and the degree of sunshine is important information because it affects the paperwork and painting work.

In addition, if the direction of the house is different according to the detailed position of the house of each household, the household floor plan management unit stores different direction information for each location together in the floor plan DB. For example, suppose that 120 rooms in 101, 101-dong, Hannam-dong, Yongsan-gu, have four rooms.

The defect receiving unit 210 receives the direction information of the house corresponding to the position of the house where the defect occurred in the household floor plan management unit 290. For example, if two defects are received in two rooms in 101, 1201, Hankook-dong, Hannam-dong, Yongsan-gu, room 1 is southward and room 3 is trend.

The weather information management unit 300 takes weather information by region and date and time of the Korea Meteorological Administration, stores and manages it in a weather information DB.

The defect receiving unit 210 receives the date information on the occurrence of the defect in the terminal 100 of the manager or the tenant, and receives the weather information corresponding to the date of the defect and the location of the house where the defect occurred in the weather information management unit 300. . For example, when the defect occurrence date received at # 101, 1201, Hana-dong, Hannam-dong, Yongsan-gu, is August 10, 2019, the weather information management unit 300 will provide the weather information corresponding to the location of the Korean apartment in Hannam-dong, Yongsan-gu, August 10, 2019. Receive

Defect repair model generation unit 270 is the case that the type of facility materials that can be used for the repair of the defect and the method of defect repair using the facility materials is limited compared to the type of facility materials that can be used for other types of repair For example, if the properties of the facility materials are similar to each other, the first defect repair model is generated by giving more weight to the skill of the defect repair company.

However, when the properties of the facility materials are different from each other, the second repair and repair model is generated by giving weight to the property of the facility more than the skill of the defect repair company.

For example, the types of facility materials that can be used for repairing torn defects among the types of defects in the construction work and the method of repairing them using the corresponding facility materials are less than half of the types of facility materials that can be used for repairing defects in adhesion and defects. In this case, if the properties of facility materials that can be used for tearing paper are similar to each other due to their weakness in high temperature and humidity, the first defect should be evaluated by placing more emphasis on the proficiency of the company through the evaluation of the repair company than the facility materials and the repair method. Create a maintenance model. Among the input variables (x), the number 1, which can recommend defect repair companies that have been evaluated as having a good fault repair by giving 3 ~ 5% weight to the skill of defect repair companies compared to the type and nature of facility materials and defect repair methods. Create a repair process model.

However, if the properties of the facility materials that can be used for defect repair or poor defect repair are different from each other, a second repair and repair model that can recommend facility materials with excellent adhesion by weighting the properties of the facility materials is 3 to 5%. Create

Defect repair model generation unit 270 corresponds to the location information of the defect in the household where the defect occurred, the location of the house in the household where the defect occurs if the property of the facility material that can be used for the repair is sensitive to temperature and humidity Create a repair process model including the direction information of the house, the date of occurrence of the defect and the weather information corresponding to the location of the house on the date.

In detail, when the defect location, the direction of the house, and the weather information may affect the property of the facility material, a third defect repair model is generated by placing a heavy weight on the type and property of the facility material. Among the various defect repair-related data used as input variables (x), a third defect repair model is generated by giving a weight of 3 to 5% to the type and property of facility materials.

For example, in the case of painting, the location of defects in the house and the direction of the house are well-sunrided because the properties of the facilities are sensitive to temperature and humidity. And a 3 to 5% weighting property to generate a third defect repair model that can recommend facility materials that exhibit excellent quality even in high temperature and high humidity environments.

In addition, when the defect location, the direction of the house, and the weather information are irrelevant to the situation that may affect the properties of the facility materials, the fourth defect repair treatment model is generated by placing a heavy weight on the skill of the defect repair company.

The location of the fault and the direction of the house where the fault occurred at home is not a sunny place, and if the weather is also cool, the skill of the defect repair company may be affected more than the quality of the facility materials. Create a fourth defect repair model that can recommend defect repair companies that have been evaluated to be good at fault repair by giving a weight of ~ 5%.

Considering various situations in three dimensions as described above, by applying different repair and repair models optimized for the situation, the facilities used for the repair and repair of defects according to the location and environment of each household, even for the same type of defect It is possible to recommend material types and defect repair companies to increase the satisfaction of residents and minimize the cost of defect repair.

The defect receiving unit 210 receives a plurality of defect information generated at different locations of the same household from the manager or the tenant's terminal 100, and if the property of the facility material that can be used for the defect repair is sensitive to temperature and humidity. The repair method recommending unit 280 applies a third defect repair model for each fault occurring in the same household when the fault location, the direction of the house, and the weather information may affect the properties of the facility materials. In addition, the type of facility materials used for the repair of defects and the repair companies are recommended.

For each defect, if the location of the defect, the direction of the house, and the weather information are irrelevant to the circumstances that may affect the properties of the equipment, apply the fourth defect repair model to determine the method of repair and the equipment used for the repair. Recommended types and defect repair companies.

In other words, when a fault is received from rooms in different locations in the same house, each fault location in the household, the direction of the room where the fault occurred, and weather information may affect the properties of the facility. Apply the repair model and apply the fourth repair model if the fault location, direction of the room where the defect occurred, and weather information cannot affect the properties of the facility materials. Recommended methods, types of facility materials used for defect repair, and defect repair companies.

Defect occurrence status determination unit 310 is a fault location for the generation occurred in the household, the direction of the house corresponding to the location of the house where the defect occurred, the weather information corresponding to the location of the house on the date of the defect occurs Determine if the situation is likely to affect

Specifically, the defect occurrence situation determination unit 310 comprehensively considers the location of the room where the defect occurred, the direction of the room where the defect occurred, and whether the date of occurrence of the defect is cool or hot using the floor plan information of the household. It is determined whether or not the situation is likely to affect the nature of the facility materials. At this time, if the direction of the room is well received sunlight even in the location of the room where the defect occurs, it can be determined by calculating the distance from the window of the room to the location of the defect in the room. In other words, when the direction of the room is a trend or southeast, the sun enters deep into the room. Therefore, unlike when the direction of the room is south, the probability that a defect occurs in the inner position of the room will affect the properties of the equipment. Is higher.

In addition, when the direction is a trend and south-east direction, when south direction, the score is given differently to determine.

The defect repair method recommender 280 selectively applies one of the third fault repair model and the fourth fault repair model according to the judgment result of the fault condition determination unit 310 to use the fault repair method and fault repair. Recommended types of facility materials and defect repair companies.

1 to 4, a method of analyzing and processing defects of an apartment house using artificial intelligence based on a machine learning algorithm is performed in the following order.

Duplicate description of the contents described above in detail will be omitted.

The defect receiving unit 210 receives defect information and defects occurring in a multi-family house from the terminal 100 of the manager or tenant (S210).

The defect classification recorder 220 classifies the received defect information by facility material category and records the defect information in the DB (S220).

Defect repair company designation unit 240 designates a defect repair method, the type of facility materials used for the repair and the defect repair company for the received defect and stores in the defect repair company designation DB (S230).

The defect repair request unit 250 transmits the defect contents received to the designated defect repair company, the defect repair method, and the type of facility material used for the defect repair and requests for the defect repair (S240).

The defect repair evaluation unit 260, upon completion of the defect repair by the designated defect repair company, receives the evaluation contents for the defect repair result and the request for repair of the defect from the administrator or the tenant terminal 100, and shows the defect repair result DB. Store in (S250). When requesting for a repair of defects, the related information is delivered to the corresponding repair company and the request for defect repair is made again (S260).

Defect repair model generation unit 270 is a defect information on the facility material and the corresponding facility material recorded in the defect information DB and the nature of the defect occurred in the facility material DB and the defects stored in the defect repair company designated DB Machine learning is conducted by machine learning on the method of repairing defects, the type of facility materials used in the repair, the name of the repair company and the evaluation result of the repair process stored in the DB, and whether the repair request is re-requested. Generate a defect repair process model that infers the defect repair method for the generated facility materials, the type of facility materials used for the fault repair, and the fault repair company to perform the fault repair (S270).

The defect repair method recommending unit 280 applies defect information on the received facility materials to the defect repair model, and uses the fault repair method for the fault received by the manager or the tenant's terminal 100, and the facility used for the fault repair. Recommend the type of material and defect repair company (S280). Referring to Figure 2, according to the method recommended by the defect repair method recommendation unit 280, the defects received by the designated defect repair company delivered to the request for defect repair, evaluation of the result of the repair process, rehabilitation request The decision is made. This process is also learned using a machine learning algorithm.

The defect receiving step (S210) is subjected to the following detailed procedure.

First, when receiving the address information from the terminal 100 of the manager or the tenant, the address is retrieved from the floor plan DB and transmitted so that the floor plan of the household where the defect has occurred is displayed on the terminal 100 of the manager or the tenant.

In addition, the manager or tenant's terminal 100 inputs defect information by clicking a position where a defect has occurred in the floor plan received from the household floor plan manager 290.

The manager or the tenant's terminal 100 receives the information on the location of the defect, the facility material information and the defect information from the floor plan of the household where the defect occurred, and the household floor plan management unit 290 receives the household of the household where the defect occurred. Receive direction information.

Finally, receiving the date information on the occurrence of the defect from the terminal 100 of the administrator or the tenant, and receives the weather information corresponding to the date of the defect and the location of the house where the defect occurred in the weather information management unit 300.

Referring to Figure 3, the step of generating a repair process model (S270) is the type of facility materials that can be used for the repair of the defect and the method of repair using the corresponding repair materials of the facility materials that can be used for other types of repair In the limited case compared with the type (S271), if the properties of the facility materials are similar to each other (S272), the weight of the defect repair company's proficiency is increased to generate a first defect repair model (S273), and the properties of the facility materials are If different from each other, the weight of the facility material is greater than the skill of the defect repair company to create a second repair process model (S274).

Referring to Figure 4, the step of generating a repair process model (S270) is the defect location information in the generation where the defect occurs, if the property of the facility material that can be used for the repair (S275) Generates a repair process model including the direction information of the house corresponding to the location of the house where the defect occurred, the date of the occurrence of the defect and the weather information corresponding to the location of the house on the date.

Specifically, when the defect location, the direction of the house, the weather information is likely to affect the properties of the facility materials (S276), the third defect repair treatment model is generated by placing a heavy weight on the types and properties of the facility materials (S277). ), If the defect location, the direction of the house, the weather information is irrelevant to the situation that may affect the properties of the facility materials (S276) to create a fourth defect repair treatment model by placing a heavy weight on the skill of the defect repair company (S278). ).

When receiving defect information generated from different locations of the same household from the administrator or tenant's terminal 100 in the defect reception step, and the nature of the facility materials that can be used for the repair of the defect is sensitive to temperature and humidity (S275) Recommended repair method is as follows.

The defect repair method recommendation step (S280) applies a third defect repair process model for each fault occurring in the same household when the position of the fault, the direction of the house, and the weather information may affect the properties of the facility materials (S276). (S277) Recommend defect repair method, type of facility materials used for defect repair, and defect repair company.

For each defect, if the defect location, the direction of the house, and the weather information are not related to the situation that may affect the property of the facility materials (S276), apply the fourth defect repair model (S278) We recommend the type of equipment used and the repair company.

According to the present invention, the types and properties of the paper used in different generations in different environments (home orientation, temperature, etc.), the types and properties of the grasses used for the papering, and the repair of the defective papers, By learning the method using a machine learning algorithm based on supervised learning, when the manager or tenant receives the information related to the defect generated in the apartment, the customized defect repair method for the household, the facility materials to be used for the defect repair and the appropriate We can recommend a defect repair company. In addition, by constructing and analyzing various defects occurring in multi-unit houses on a nationwide basis in the cloud based on big data, it is possible to systematically and accurately analyze various defect occurrence situations.

Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art to which the present invention pertains can implement the present invention in other specific forms without changing the technical spirit or essential features, The embodiments are to be understood in all respects as illustrative and not restrictive.

In addition, the scope of the present invention is specified by the appended claims rather than the detailed description, and all changes or modifications derived from the meaning and scope of the claims and their equivalent concepts are included in the scope of the present invention. Should be interpreted as

100.Administrator or tenant's terminal
110 ... Let's Receive Apps
200 ... Let's handle the server
210 ... let's go
220 ... Classification Record
230.Facility Materials Management Department
240.Defective repair company designation department
250 Repair request
260 ...
Defective repair model generation unit
280 ... Repair of Recommends
290 households floor plan management department
300. Weather Information Management Department
310.Defective situation determination unit

Claims (14)

A defect receiving unit for receiving defect information and defects occurring in a multi-family house from a manager or a tenant's terminal;
A defect classification recorder for classifying the defect information received by the defect receiving unit by facility material category and recording the defect information in a DB;
Facility material management unit for matching the type of facility materials used or planned to be used in the apartment house and the properties of each facility material to store in the facility material DB;
Defect repair company designation unit for designating a defect repair method for the defect received by the defect receiving unit, the type of facility materials used for the repair and the defect repair company to store in the defect repair company designated DB;
A defect repair request unit for requesting a defect repair by transferring the received contents of the defect, a method of repairing a defect, and a kind of facility material used for the repair to a defect repair company designated by the defect repair company designation unit;
When the designated defect repair company completes the defect repair, the manager or the tenant terminal receives the evaluation contents of the defect repair result and whether the repair is requested again, and stores the result in the defect repair result DB. Defect repair evaluation unit for re-requesting defect repair by delivering the relevant information to the defect repair company;
Defective information on the facility materials and the corresponding facility materials recorded in the defect information DB, the nature of the facility material in which the defects are stored in the facility material DB, the method of repairing defects on the defects stored in the defect repair company designated DB, and defect repair Types of facility materials used, name of the repair company, and the contents of the evaluation of the repair results stored in the defect repair result DB and whether or not the request for defect repair is requested again. A repair process model generation unit for generating a repair process model for inferring a repair method and a type of facility material used for repair and a repair service provider to perform the repair; And
Apply the defect information on the facility materials received by the defect receiving unit to the defect repair model, and find out how to repair the defects received from the manager or the tenant's terminal, the type of facility materials used for the repair, and the repair company. Including recommended repair method recommendation,
The defect repair model generation unit generates a variety of defects in consideration of the name of the land where the defect occurred, various types of defects of the land, various properties of the land, the address of each generation where the fault occurred, the location of the household, the location of the household, the direction of the house, and the weather conditions. Various data such as repair methods, names of various companies, the proficiency of the defectors through evaluation, evaluation contents of the defects, and whether they are requested to repair the defects or are satisfied with the results of the repairs Create a repair process model that predicts the result value (y) by learning using the input variable (x),
The result value (y) outputs the defect repair method to be used for the paper defect, the paper company to handle the defect and the paper to be used for the fault repair.
The defect repair treatment model generating unit is a location information of the defect location within the household where the defect occurred, the location of the house where the defect occurred in the household when the property of the facility material that can be used for the repair is sensitive to temperature and humidity Create a repair process model including the direction information, the date the defect occurred and the weather information corresponding to the location of the house on the date,
If the fault location, the direction of the house, and the weather information are likely to affect the properties of the facility materials, the third defect repair model is created by giving a weight to the type and property of the facility materials. In the case of painting work, since the properties of the facilities are very sensitive to temperature and humidity, the location of the defects in the house and the direction of the house are well-done in the sun. We recommend facility materials that show excellent quality over a certain standard even in high temperature and high humidity environment.
If the defect location, the direction of the house, and the weather information are irrelevant to the situation that may affect the properties of the facility materials, the fourth defect repair model is created by placing a heavy weight on the skill of the defect repair company. The location of the fault in the house and the direction of the house are not a sunny place, and if the weather is also cool, the skill of the defect repair company may be affected more than the quality of the facility materials. Recommend a defect repair company that has received a certain score or more and is rated as having a certain weight.
When the defect receiving unit receives a plurality of defect information generated at different locations of the same household from the manager or the tenant's terminal, and the property of the facility material that can be used for the defect repair is sensitive to temperature and humidity.
The defect repair method recommending unit applies the third defect repair process model when the fault location, the direction of the house, and the weather information may affect the properties of the facilities for each fault occurring in the same household. Recommend the type of facility materials used for the repair and the repair company
For each fault, if the fault location, direction of the house, and weather information are not related to the situation that may affect the properties of the facility materials, apply the fourth defect repair model above to determine the method of repair Recommend type and defect repair company,
The location of the defect, the direction of the house corresponding to the location of the house where the defect occurred, and whether the weather information corresponding to the location of the house on the date of the defect is likely to affect the properties of the facilities. Further comprising a defect occurrence situation determination unit to determine,
The defect occurrence status determination unit uses the floor plan information of the household to consider the location of the room where the defect occurred, the direction of the room where the defect occurred, and whether the date of occurrence of the defect is in good or hot weather. Determine whether or not the situation is likely to affect the situation, if the direction of the room is well received sunlight even in the location of the room where the defect occurs, calculate by determining the distance from the window of the room to the location of the occurrence of the defect,
When the direction of the room is a trend or south-east, the sun enters deep into the room. Therefore, unlike the case where the room is south-facing, the occurrence of defects in the inner position of the room is likely to affect the properties of the facilities.
The defect repair method recommending unit selectively applies one of the third defect repair model and the fourth defect repair treatment model according to the judgment result of the fault occurrence situation determination unit, and the types and defects of facility materials used for the repair. A system that analyzes and processes defects in multi-family houses, characterized by recommending repair companies, using artificial intelligence based on machine learning algorithms.
The method according to claim 1,
When the floor plan information for each household of the apartment house is stored in a floor plan DB and receives address information from the terminal of the manager or the tenant, the floor plan is searched for the corresponding address in the floor plan DB and the floor plan of the household where the defect occurs in the terminal of the manager or the tenant Further comprising a household floor plan management unit to display the,
When entering the address information, the manager or the tenant's terminal automatically displays a floor plan of the household where the defect has occurred on the input screen, and enters the defect information by clicking a location where the defect has occurred in the floor plan,
The defect receiving unit uses an artificial intelligence based on a machine learning algorithm to detect defects in a multi-family house, wherein the defect receiving unit receives information on the location of the defect in the floor plan of the household in which the defect occurred, information on the facilities materials and the defect information on which the defect occurred. Analysis and processing system.
The method according to claim 2,
The household floor plan management unit stores the floor plan information for each household and direction information of the house for each household in the apartment house together in a floor plan DB,
The defect receiving unit receives the information on the location of the defect in the floor plan of the household where the defect has occurred, the information of the facility materials and the defect information on the defect occurred at the terminal of the manager or the tenant, and the household of the household where the defect occurred in the household floor plan management unit. A system for analyzing and processing defects of an apartment house using artificial intelligence based on a machine learning algorithm, characterized by further receiving direction information.
The method according to claim 3,
When the direction of the house is different according to the detailed position of the house of each household, the household floor plan management unit stores different direction information for each location together in the floor plan DB,
The defect receiving unit analyzes and processes a defect of a multi-family house using artificial intelligence based on a machine learning algorithm, characterized in that the household floor plan management unit receives direction information of a house corresponding to the position of the house where the defect occurred.
The method according to claim 3,
It further includes a weather information management unit to take the weather information by region, date and time of the Korea Meteorological Administration to store and manage in the weather information DB,
The defect receiving unit receives the date information on the occurrence of the defect at the terminal of the manager or the tenant, and the weather information management unit receives weather information corresponding to the date of the defect and the location of the house where the defect occurred. A system that analyzes and processes defects using artificial intelligence based on machine learning algorithms.
The method according to claim 1,
The defect repair processing model generating unit, if the type of facility materials that can be used for the repair of the defect and the method of defect repair using the facility materials is limited compared to the type of facility materials that can be used for other types of repair, facility materials If the properties are similar to each other, the first defect repair model is created by giving more weight to the skill of the repair shop.
If the properties of the facility materials are different from each other, the AI of the apartment building is based on the machine learning algorithm. System for analysis and processing.
delete delete delete A defect reception step of receiving defect information generated in a multi-family house and facility material information having a defect from a manager or a tenant's terminal;
A defect classification recording step of classifying the received defect information by facility material category and recording it in the defect information DB;
Defect repair company designation step for designating defect repair method, type of facility materials used for defect repair and defect repair company and storing it in defect repair company designation DB;
Defect repair request step that delivers the defect contents, defect repair method and the type of equipment used for the repair to the designated defect repair company to request the repair;
When the designated defect repair company completes the defect repair, it receives the evaluation contents of the defect repair result from the administrator or the tenant's terminal and whether the defect is re-requested, and stores it in the defect repair result DB. Defect repair evaluation step of re-requesting defect repair by delivering related information to defect repair company;
Defective information on facility materials recorded in the defect information DB and the corresponding facility materials, the nature of the facility material in which the defects are stored in the facility material DB, the method of repairing defects stored in the defect repair company designated DB, and the facilities used for the repair Type of material and defect repair company name and defect repair result The evaluation contents of the defect repair result stored in the DB and the machine repair (request of defect repair request) and the defect repair method and defects for the facility materials where the defect occurred. A step of generating a repair process model for generating a repair process model for inferring a type of facility material used for repair and a repair service for performing the repair work; And
By applying the defect information on the received facility materials to the above-mentioned defect repair model, defect repair method for defects received from the manager or tenant's terminal, recommending repair method, type of facility materials used for defect repair, and defect repair company Including method recommendation steps,
The defect repair model generation step,
The name of the site where the defect occurred, the various types of the site, the nature of the site, the address of each generation where the site occurred, the location of the household, the location of the house, the direction of the house and the weather conditions, Use various data as input variables (x) such as the name, the proficiency of the defector through the evaluation, the evaluation contents of the defect, and whether the defect is re-requested for the defect or whether the defect is satisfied. To generate a repair process model that predicts the result value (y)
The result value (y) outputs the defect repair method to be used for the paper defect, the paper company to handle the defect and the paper to be used for the fault repair.
The defect repair model generation step,
If the nature of the facility materials that can be used for the repair is sensitive to temperature and humidity, defect location information in the household where the defect occurred, direction information of the house corresponding to the location of the house where the defect occurred, and the date of the defect. And generating a repair process model including weather information corresponding to the location of the house on the corresponding date,
If the fault location, the direction of the house, and the weather information are likely to affect the properties of the facility materials, the third defect repair model is created by giving a weight to the type and property of the facility materials. In the case of painting work, since the properties of the facilities are sensitive to temperature and humidity, the location of the defects in the house and the direction of the house are well-lit, and if the weather is somewhat hot, the type and properties of the facilities are prescribed. We recommend facility materials that show excellent quality over a certain standard even in high temperature and high humidity environment.
If the defect location, the direction of the house, and the weather information are irrelevant to the situation that may affect the properties of the facility materials, the fourth defect repair model is created by placing a heavy weight on the skill of the defect repair company, and the fourth defect repair model. The location of the fault in the house and the direction of the house are not a sunny place, and if the weather is also cool, the skill of the defect repair company may be affected more than the quality of the facility materials. Recommend a defect repair company that has received a certain score or more and is rated as having a certain weight.
When receiving defect information generated from different locations of the same household from the manager or tenant's terminal in the defect reception step, and the nature of the facility materials that can be used for the repair of the defect is sensitive to temperature and humidity
The defect repair method recommendation step,
For each defect that occurred in the same household, the location of the defect, the direction of the house, and the meteorological information that may affect the properties of the facility materials. Recommend material type and defect repair company,
For each fault, if the fault location, direction of the house, and weather information are not related to the situation that may affect the properties of the facility materials, apply the fourth defect repair model above to determine the method of repair Recommend type and defect repair company,
The location of the defect, the direction of the house corresponding to the location of the house where the defect occurred, and whether the weather information corresponding to the location of the house on the date of the defect is likely to affect the properties of the facilities. The method may further include determining a defect occurrence situation.
The fault occurrence determination step may be performed by considering the location of the room where the defect occurred, the direction of the room where the defect occurred, and whether the date of occurrence of the defect is cool or hot using the floor plan information of the household. Determine whether or not the situation is likely to affect the nature, and if the direction of the room is well received sunlight even in the location of the room where the defect occurs, by calculating the distance from the window of the room to the location of the occurrence of the defect,
When the direction of the room is a trend or south-east, the sun enters deep into the room. Therefore, unlike the case where the room is south-facing, the occurrence of defects in the inner position of the room is likely to affect the properties of the facilities.
The defect repair method recommendation step is to apply one of the third repair process model and the fourth repair process model according to the judgment result of the fault occurrence situation determination step, and the type of facility materials used for the repair method and the repair of the fault. And a method of analyzing and processing faults of the multi-family house, which is characterized by recommending a defect repair company, using artificial intelligence based on a machine learning algorithm.
The method according to claim 10,
The defect acceptance step,
A generation plan view display step of receiving the address information from the terminal of the manager or the tenant, searching for the corresponding address in the plan view DB, and transmitting the generated floor plan to the terminal of the manager or the tenant;
A fault information input step of the manager or the tenant terminal inputting fault information by clicking a position where a fault has occurred in the plan view received from a household plan view management unit;
Receive information on the location of the defect, facility material information, and defect information from the floor plan of the household where the defect occurred from the manager or the tenant's terminal, and receive direction information of the home of the household where the defect occurred from the household floor plan management unit. To let the information received step; And
And receiving weather information from the terminal of the administrator or tenant and receiving weather information corresponding to the date of the defect and the location of the house where the defect occurred from the weather information management unit. A method of analyzing and processing faults in apartment houses using artificial intelligence based on machine learning algorithms.
The method according to claim 10,
The defect repair model generation step,
If the types of facility materials that can be used for the repair of the defect and the method of repairing the defects using the facilities are limited compared to the types of facility materials that can be used for other types of repair, the nature of the facilities should be similar. The first defect repair model is created by placing more weight on the proficiency of the repair company, and when the properties of the facility materials are different from each other, the weight of the facility material is greater than the proficiency of the repair company. Method for analyzing and processing the defect of the multi-family house, characterized by generating a machine learning algorithm based on artificial intelligence.
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