KR20240080098A - Method of providing estimates about heating plumbing repairs and installations and electronic device thereof - Google Patents

Abstract

A method of providing a quote regarding heating pipe repair and installation, which is performed by an electronic device according to an embodiment of the present disclosure, includes a first customer terminal device among a plurality of customer terminal devices, an expert quote or an expert quote regarding heating pipe repair and installation. transmitting information for generating one of the self-quotes, in response to receiving a request for generating the expert quotation from the first customer terminal device, providing the first customer with information necessary for generating the expert quotation; Requesting to a terminal device, receiving a request for an expert quotation corresponding to the request from the first customer terminal device, an expert quotation for heating pipe repair and installation corresponding to the request for an expert quotation from the expert terminal device It may include receiving a quotation from an expert regarding repair and installation of heating pipes to the first customer terminal device.

Description

METHOD OF PROVIDING ESTIMATES ABOUT HEATING PLUMBING REPAIRS AND INSTALLATIONS AND ELECTRONIC DEVICE THEREOF}

This disclosure relates to technology for providing estimates for heating piping repair and installation.

To repair or install heating pipes, you should call a company and have their experts inspect the condition of the heating pipes. The expert provides information to the customer based on the test results. In other words, users had the inconvenience of having to always call technical experts to repair and install heating pipes, and it took a long time to receive an estimate. Additionally, from the customer's perspective, there is a problem that it is difficult to clearly understand the details of the quotation and it is difficult to determine whether the quotation is at an appropriate level.

According to various embodiments of the present disclosure, the technical problem is to enable customers to easily and quickly receive estimates from experts by simply uploading photos related to heating pipes.

According to various embodiments of the present disclosure, the technical problem is to enable customers to easily and quickly receive quotations by entering information about heating piping construction themselves.

A method of providing a quote regarding heating pipe repair and installation, which is performed by an electronic device according to an embodiment of the present disclosure, includes a first customer terminal device among a plurality of customer terminal devices, an expert quote or an expert quote regarding heating pipe repair and installation. transmitting information for generating one of the self-quotes, in response to receiving a request for generating the expert quotation from the first customer terminal device, providing the first customer with information necessary for generating the expert quotation; Requesting to a terminal device, receiving a request for an expert quotation corresponding to the request from the first customer terminal device, an expert quotation for heating pipe repair and installation corresponding to the request for an expert quotation from the expert terminal device It may include receiving a quotation from an expert regarding repair and installation of heating pipes to the first customer terminal device.

According to one embodiment, the information required to generate the expert quotation and the request for the expert quotation may include a photo of a distributor and a photo of at least one temperature controller.

According to one embodiment, inputting a photo of the distributor into a first correlation model, obtaining information about the number of spheres of the distributor from the first correlation model, and obtaining information about the number of spheres of the distributor from the expert. It further includes the step of transmitting to a terminal device, wherein the first correlation model uses a set of photos of a plurality of distributors as input data for training, according to a machine learning algorithm, and the number of spheres of the distributor corresponding to each of the plurality of distributors. It may be an artificial intelligence model built by using a set of information about as training output data and modeling the correlation between the training input data and the training output data.

According to one embodiment, the step of storing information about the number of the dispenser in the form of a block in the node of the first customer terminal device in a blockchain network formed with each of the plurality of customer terminal devices as a node, the first In response to storing information about the number of the dispenser in block form in the node of the customer terminal device, it further includes obtaining a reward, and transmitting the obtained reward to the first customer terminal device, The reward may be a cryptocurrency mined based on information about the number of coins of the dispenser and delivered to a cryptocurrency wallet allocated to the first customer terminal device.

According to one embodiment, in response to receiving a request for generating the self-quote from a second customer terminal device among the plurality of customer terminal devices, the information necessary for generating the self-quote is sent to the second customer terminal device. requesting, from the second customer terminal device, receiving a self-quotation request request containing information necessary for generating the self-quotation, based on the information necessary for generating the self-quotation, heating pipe repair It may further include generating a self-quotation regarding installation, and transmitting the self-quotation regarding heating pipe repair and installation to the second customer terminal device.

According to one embodiment, the information required to generate the self-quotation is information about the type of building to be constructed, information about the square footage of the building to be constructed, information about the construction year of the building to be constructed, information about the number of thermostats, and actuators. It may be characterized as including information on the number, information on the number of distributors, information on the presence or absence of a controller, and information on the presence or absence of a constant flow valve.

According to one embodiment, the step of generating the self-quotation includes generating a quotation for a temperature controller based on information about the number of thermostats and a unit price of the thermostat, information about the number of actuators, and a unit price of the actuator. Based on this, generating an estimate for the actuator, generating an estimate for the distributor based on information about the number of pieces of the distributor and a distributor unit price corresponding to the number of pieces of the distributor, information about the presence or absence of the controller, and Based on the unit price of the controller, generating an estimate for the controller, generating an estimate for the constant flow valve based on the information regarding the presence or absence of the constant flow valve and the unit price of the constant flow valve, and Generating the self-quotation based on a quote related to the driver, a quote related to the distributor, a quote related to the controller, a quote related to the constant flow valve, a predetermined construction cost, and a predetermined price of piping accessories. may include.

According to one embodiment, the self-quotation request request includes information about the product desired by the customer of the second customer terminal device among entry-level products or premium products, the unit price of the temperature controller, the unit price of the actuator, The unit price of the distributor, the unit price of the controller, and the unit price of the constant flow valve may be determined based on information input by the manager about the product desired by the customer.

According to one embodiment, inputting information about the type of building to be constructed, information about the square footage of the building to be constructed, and information about the construction year of the building to be constructed into a second correlation model, and the second correlation model It further includes a step of obtaining information on the number of temperature controllers, information on the number of drivers, information on the number of distributors, information on the presence or absence of a controller, and information on the presence or absence of a constant flow valve, and the second correlation model is, According to a machine learning algorithm, a set of information about a plurality of building types, information about the square footage of a plurality of buildings, and information about the construction years of the plurality of buildings are used as training input data, and the temperature corresponding to each of the plurality of buildings is set as training input data. A set of information on the number of regulators, information on the number of actuators, information on the number of distributors, information on the presence or absence of a controller, and information on the presence or absence of a constant flow valve are set as training output data, and the training input data and the training An artificial intelligence model built by modeling the correlation between power output data can provide estimates for heating pipe repair and installation.

According to various embodiments of the present disclosure, a customer can easily and quickly receive a quote from an expert by simply uploading a photo related to the heating pipe.

According to various embodiments of the present disclosure, a customer can easily and quickly receive an estimate by entering information regarding heating piping construction.

The effects that can be obtained from the exemplary embodiments of the present disclosure are not limited to the effects mentioned above, and other effects not mentioned are common knowledge in the technical field to which the exemplary embodiments of the present disclosure belong from the following description. It can be clearly derived and understood by those who have it. That is, unintended effects resulting from implementing the exemplary embodiments of the present disclosure may also be derived by those skilled in the art from the exemplary embodiments of the present disclosure.

1 is a diagram illustrating a system for operating a service that provides estimates for heating pipe repair and installation according to various embodiments of the present disclosure.
2 is a block diagram of an electronic device according to various embodiments.
Figure 3 is a diagram illustrating a home screen of an application according to various embodiments of the present disclosure.
Figure 4 is a diagram illustrating a 3-second quote page of an application according to various embodiments of the present disclosure.
FIG. 5A is a diagram illustrating an expert estimate page of an application according to various embodiments of the present disclosure. FIG. 5B is a diagram illustrating a self-quotation page of an application according to various embodiments of the present disclosure.
6 is a flowchart of an operation of an electronic device according to various embodiments of the present disclosure.
7 is a flowchart of an operation of an electronic device according to various embodiments of the present disclosure.

FIG. 1 is a diagram illustrating a system 10 that operates a service that provides estimates for heating pipe repair and installation according to various embodiments of the present disclosure. According to one embodiment, the service may be called a 3-second quote service.

The system 10 according to various embodiments may include an electronic device 110, a plurality of customer terminal devices 120, and a plurality of expert terminal devices 130. The electronic device 110 may be wired or wirelessly connected to a plurality of customer terminal devices 120 and a plurality of expert terminal devices 130 through a communication network. The customer terminal device 120 may refer to a terminal device owned by a customer, and the expert terminal device 130 may refer to a terminal device owned by an expert in heating pipe repair and installation. In this drawing, for convenience of explanation, one customer terminal device 120 and one expert terminal device 130 are shown as included in the system 10, but a plurality of customer terminal devices each owned by a plurality of customers ( Of course, 120 and a plurality of expert terminal devices 130 owned by each of the plurality of experts may be included in the system 10.

The electronic device 110 according to various embodiments may be a server device that operates a service that can provide estimates for heating pipe repair and installation to the customer terminal device 120. The service may be operated through an application. The customer can download the application through the customer terminal device 120 and use the service through the application. The estimate disclosed in this document may mean a cost estimate for repairing heating pipes or installing heating pipes.

When a customer according to various embodiments wishes to repair or install a heating pipe, he or she may access the application through the customer terminal device 120. The customer can select either an expert quote or a self-quote through the customer terminal device 120. For example, if a customer wishes to receive a quote from an expert, the customer can select the expert quote. For example, if a customer wishes to generate and receive a quote themselves, the customer can select self-quotation.

If the customer selects an expert quotation, the customer terminal device 120 may transmit a request for generating an expert quotation to the electronic device 110. In response to the request, the electronic device 110 may request the customer terminal device 120 for information necessary to generate an expert quotation. A detailed description of the necessary information will be described later. A customer may transmit an expert quotation request request containing necessary information for generating an expert quotation to the electronic device 110. Thereafter, the electronic device 110 may transmit the expert quotation request request to the expert terminal device 130. The electronic device 110 may receive an estimate for repair and installation of heating pipes corresponding to a request for an expert estimate from the expert terminal device 130 . The electronic device 110 may transmit a quote regarding heating pipe repair and installation to the customer terminal device 120 . Accordingly, the customer can easily and easily receive expert estimates for heating pipe repair and installation by entering the necessary information to generate the expert estimate.

When the customer selects self-quotation, the customer terminal device 120 may transmit a request for generating a self-quote to the electronic device 110. In response to the request, the electronic device 110 may request the customer terminal device 120 for information necessary to generate a self-quotation. A detailed description of the necessary information will be described later. The customer may transmit a self-quotation request request containing information necessary to generate a self-quote to the electronic device 110. The electronic device 110 may generate an estimated quotation based on information needed to generate the self-quotation. The electronic device 110 may transmit the generated estimated quotation to the customer terminal device 120. Accordingly, the customer can easily and easily receive a self-quotation for heating pipe repair and installation by entering the necessary information to create a self-quotation.

The electronic device 110 according to various embodiments may provide a certain compensation to the customer terminal device 120 that has completed the service. Rewards may be, for example, points that can be used when using the service, or may be cryptocurrency (or coins).

Figure 2 is a block diagram of an electronic device 110 according to various embodiments.

The electronic device 110 according to one embodiment includes a processor 111, a memory 113, a communication circuit 115, and a database 117. The electronic device 110 according to one embodiment may be a server device for operating the above-described system 10. The processor 111 may include at least one device disclosed in this document or may perform at least one method disclosed in this document. The memory 113 may store information related to the above-described method or store a program implementing the above-described method. Memory 113 may be volatile memory or non-volatile memory.

The processor 111 can execute programs and control the electronic device 110. The code of the program executed by the processor 111 may be stored in the memory 113. The electronic device 110 may be connected to an external device (eg, a personal computer or a network) through an input/output device (not shown) and exchange data. The processor 111 may be operatively connected to components of the electronic device 110. The processor 111 may load commands or data received from other components of the electronic device 110 into the memory 113, process the commands or data stored in the memory 113, and store the resulting data.

The communication circuit 115 may establish a communication channel with an external device (e.g., a customer terminal device 120 or an expert terminal device 130) and transmit and receive various data with the external device. According to various embodiments, the communication circuit 115 may include a cellular communication module and be configured to connect to a cellular network (eg, 3G, LTE, 5G, Wibro, or Wimax). According to various embodiments, the communication circuit 115 includes a short-range communication module and can transmit and receive data with an external device using short-range communication (e.g., Wi-Fi, Bluetooth, Bluetooth Low Energy (BLE), UWB). However, it is not limited to this.

The database 117 can store various information. The database 117 may store information received from each of the plurality of customer terminal devices 120 under the control of the processor 111. The database 117 according to various embodiments may store a first correlation model that has been learned (constructed) so that information about the number of spheres of the dispenser is output when a photo of the dispenser is input. The first correlation model uses a set of photos of a plurality of distributors as input data for training, according to a machine learning algorithm, and uses a set of information about the number of spheres of the distributor corresponding to each of the plurality of distributors as output data for training. , It may be an artificial intelligence model built by modeling the correlation between the training input data and the training output data.

The database 117 according to various embodiments, when inputting information about the type of building to be constructed, information about the square footage of the building to be constructed, and information about the construction year of the building to be constructed, information about the number of thermostats and the number of actuators are provided. A second correlation model that has been learned (built) to output information about the distributor, information about the number of distributors, information about the presence or absence of a controller, and information about the presence or absence of a constant flow rate valve can be stored. The second correlation model uses, according to a machine learning algorithm, a set of information about a plurality of building types, information about the square footage of a plurality of buildings, and information about the number of years of construction of the plurality of buildings as training input data, and uses the plurality of buildings as training input data. A set of information on the number of thermostats corresponding to each building, information on the number of actuators, information on the number of distributors, information on the presence or absence of a controller, and information on the presence or absence of a constant flow valve are used as training output data, and the above training is performed. It may be an artificial intelligence model built by modeling the correlation between input data for training and the output data for training.

According to various embodiments, quotation request data for a plurality of customers stored in the database 117 may be used as training data for developing an artificial intelligence model. Quote request data for multiple customers can be used to build an artificial intelligence model to generate optimal quotes.

FIG. 3 is a diagram illustrating a home screen 300 of an application according to various embodiments of the present disclosure. Specifically, FIG. 3 is a diagram illustrating the home screen 300 of an application that operates a service that provides estimates for heating pipe repair and installation.

According to various embodiments, a customer may run an application that provides a service that provides estimates for heating pipe repair and installation through the customer terminal device 120. When executing the application, the customer terminal device 120 may display the home screen 300 as shown in FIG. 3. The home screen 300 according to various embodiments may include a region selection area 310, a service selection area 320, and a bottom menu area 330.

The customer terminal device 120 according to various embodiments may display a region selection icon 311 in the region selection area 310 through which the customer can select the region of the house in which he or she wants to repair or install heating pipes. The customer can select the region selection icon 311 to search and/or select the region of the home to receive a quote.

The customer terminal device 120 according to various embodiments displays a 3-second quotation icon 321 for a 3-second quotation service and a free visit quotation request icon 323 for a quotation request service through a free visit in the service selection area 320. ), the K-heating floor plan icon 325, and the AS visit request icon 327 to request an AS visit can be displayed. For example, to receive an expert quote or a self-quote, the customer may select the 3-second quote icon 321. For example, in order to visit a home for free and receive a quote, the customer may select the free home quote request icon 323. For example, to receive service related to the K-heating floor plan, the customer may select the K-heating floor plan icon 325. For example, to request an AS visit, the customer may select the AS visit request icon 327.

The customer terminal device 120 according to various embodiments has a home screen icon 331, a 3-second quote icon 333, and a free visit icon 335 in the lower menu area 330, similar to the service selection area 320. ), K-Heating floor plan icon (337), and My Page icon (339) can be displayed. The customer terminal device 120 may display the home screen 300 as shown in FIG. 3 in response to a user input for selecting the home screen icon 331. The customer terminal device 120 may display customer information and customer quotation request information in response to a user input of selecting the My Page icon 339.

FIG. 4 is a diagram illustrating a 3-second quote page 400 of an application according to various embodiments of the present disclosure. Specifically, the customer terminal device 120 may display the 3-second quote page 400 of FIG. 4 in response to a user input of selecting the 3-second quote icon 321 on the home screen 300 of FIG. 3. .

According to various embodiments, the 3-second quote page 400 may display an explanatory text 410 related to the 3-second quote page. Explanatory text 410 may be, for example, “The estimated cost may change depending on the selection of premium and entry-level materials. For an expert quote, please upload a photo of your distributor and thermostat so you can check it on My Page as quickly as possible. In the case of self-quotation, the phrase may say, “Please enter simple customer information and you can check the price quote in 3 seconds.” The above-described explanatory text 410 is exemplary, and of course, various explanatory phrases regarding the 3-second quotation service can be displayed.

According to various embodiments, the 3-second quote page 400 may include an expert quote icon 421 for providing an expert quote and a self-quotation icon 423 for providing a self-quote.

According to one embodiment, if the customer wishes to receive an expert estimate for heating pipe repair and installation, he or she may select the expert estimate icon 421. According to one embodiment, if the customer wishes to receive a self-quotation for heating pipe repair and installation, he or she may select the self-quotation icon 423.

FIG. 5A is a diagram illustrating an expert estimate page 510 of an application according to various embodiments of the present disclosure. In the 3-second quote page 400 shown in FIG. 4 , in response to a user input for selecting the expert quote icon 421, the customer terminal device 120 may display the expert quote page 510.

According to various embodiments, when receiving a user input for selecting the expert quotation icon 421, the customer terminal device 120 may transmit a request for generating an expert quotation to the electronic device 110. In response to receiving the request, the electronic device 110 may transmit information necessary to generate an expert quote to the customer terminal device 120. Information needed to generate an expert quote may be, for example, a photo of a distributor and a photo of at least one thermostat. At least one thermostat may mean, for example, a photo of the thermostat in each room of a house to be constructed.

Referring to FIG. 5A , an expert quotation page 510 according to various embodiments may include a description area 511 related to the expert quotation page, an upload area 513, and an expert quotation request area 515.

The customer terminal device 120 according to various embodiments may display a detailed explanation about the expert quotation through the description area 511 about the expert quotation page. The customer terminal device 120 may display explanatory text regarding the expert estimate through the description area 511. For example, the customer terminal device 120 displays in the description area 511, “Expert quotation is suitable for those who need an easier and more accurate quotation. Please upload a photo of your distributor and a thermostat to receive the quote as quickly as possible. You can display explanatory text such as “I will reply with a quotation promptly. You can check the quotation amount within 24 hours on my page.” The above-described explanatory phrases are illustrative, and of course, various explanatory phrases regarding the expert estimate can be displayed in the corresponding explanation area 511.

The upload area 513 according to various embodiments may include a distributor photo upload area 513a and at least one temperature controller photo upload area 513b. The customer terminal device 120 may display an icon for uploading (attaching) a photo of the dispenser along with a guide to the dispenser in the dispenser photo upload area 513a. Information about the dispenser may be, for example, "Please upload a photo of the dispenser. The dispenser is located at the bottom of the sink. If you are not sure, please contact the management office." The above-described guidance text is illustrative, and of course, various guidance text can be displayed. Customers can upload a photo of the distributor by selecting the icon for uploading a photo of the distributor.

The customer terminal device 120 may display an icon for uploading (attaching) at least one thermostat photo along with information about the thermostat in the at least one thermostat photo upload area 513b. Instructions for at least one thermostat may be, for example, “Please upload photos of thermostats in all rooms.” The above-described guidance text is illustrative, and of course, various guidance text can be displayed. The customer can upload at least one thermostat photo by selecting the icon for uploading at least one thermostat photo.

When the upload of the distributor photo and at least one thermostat photo is completed, the customer may select the expert quotation request icon 515a displayed in the expert quotation request area 515. In response to a user input of selecting the expert quotation request icon 515a, the customer terminal device 120 may transmit to the electronic device 110 an expert quotation request request including a photo of the dispenser and a photo of at least one thermostat. there is. In this case, the customer terminal device 120 may display a completion notice indicating that the quotation request has been completed through a pop-up window. For example, the completion notice may be something like "We will respond within 24 hours after requesting a quote. You can check the quote response result on My Page." The above-described completion guidance text is illustrative, and of course, various completion guidance texts can be displayed.

According to one embodiment, the electronic device 110 transmits, to the expert terminal device 130, an expert quotation request request including a photo of a dispenser and a photo of at least one thermostat received from the customer terminal device 120. You can. In this case, the expert can check a photo of the customer's dispenser and a photo of at least one temperature controller through the expert terminal device 130 and generate an expert quotation based on these. A professional estimate may include, for example, what to repair or install, and an estimated cost.

According to one embodiment, the electronic device 110 may input a photo of the dispenser received from the customer terminal device 120 into the first correlation model. The first correlation model uses a set of photos of a plurality of distributors as input data for training, according to a machine learning algorithm, and uses a set of information about the number of spheres of the distributor corresponding to each of the plurality of distributors as output data for training. , It may be an artificial intelligence model built by modeling the correlation between the training input data and the training output data. That is, the first correlation model may be an artificial intelligence model learned to output information about the number of mouths of the dispenser when a photo of the dispenser is input. The number of ports of the distributor may be, for example, 3 ports, 4 ports, 5 ports, or 6 ports. In general, because the price of a distributor varies depending on the number of distributors, it is important to accurately check the number of distributors for which repair or installation is desired. Using the artificial intelligence model described above, information about the number of mouths of the dispenser can be accurately confirmed in the photo of the dispenser sent by the customer. The machine learning model may be, for example, one of a deep neural network, a convolutional neural network, a recurrent neural network, a reinforcement learning model, or a machine learning model for classification-regression analysis.

According to one embodiment, the electronic device 110 is a blockchain network formed with each of a plurality of customer terminal devices 120 as nodes, and the distributor is connected to the node of a specific customer terminal device 120. Information about punctuation can be stored in block form. In response to storing information about the number of dispensers in block form in the node of the specific customer terminal device 120, the electronic device 110 may obtain a reward. The electronic device 110 may transmit the acquired reward to a specific customer terminal device 120. For example, the reward may be a point that can be used when using the service, or it may be a cryptocurrency (or coin).

FIG. 5B is a diagram illustrating a self-quotation page 520 of an application according to various embodiments of the present disclosure.

According to various embodiments, when receiving a user input for selecting the self-quotation icon 423, the customer terminal device 120 may transmit a request for generating a self-quotation to the electronic device 110. In response to receiving the request, the electronic device 110 may transmit information necessary to generate a self-quote to the customer terminal device 120. The information required to create a self-quotation includes, for example, information about the type of building to be constructed, information about the square footage of the building to be constructed, information about the construction year of the building to be constructed, information about the number of thermostats, and the number of actuators. information, information about the number of distributors, information about the presence or absence of a controller, and information about the presence or absence of a constant flow valve.

Referring to FIG. 5B, the self-quotation page 520 according to various embodiments may include a description area 521, an information input area 523, and a self-quotation request area 525 regarding the self-quotation page 520. You can.

The customer terminal device 120 according to various embodiments may display a detailed explanation regarding the self-quotation through the description area 521 regarding the self-quotation page 520. The customer terminal device 120 may display explanatory text regarding self-quotation through the description area 521. For example, the customer terminal device 120 displays in the description area 521, “Self-quotation is suitable for those who need the fastest quotation. If you select the required information about your distributor and thermostat, you will receive an estimate immediately. You can display explanatory text such as “You can check the price quote.” The above-described explanatory phrases are exemplary, and of course, various explanatory phrases regarding self-quotation can be displayed in the corresponding explanation area 521.

The information input area 523 according to various embodiments may be an area where information necessary to generate a self-quotation is input. Through the information input area 523, the customer receives information about the type of building to be constructed, information about the square footage of the building to be constructed, information about the construction year of the building to be constructed, information about the number of temperature controllers, and information about the number of actuators. Information, information about the number of distributors, information about the presence or absence of a controller, and information about the presence or absence of a constant flow valve can be entered.

For example, the customer can input whether the building to be constructed is an apartment, a villa, an officetel, or a house through the information input area 523. For example, the customer can enter whether the size of the building to be constructed is 10 pyeong, 20 pyeong, 30 pyeong, 40 pyeong, 50 pyeong, 60 pyeong, 70 pyeong, or 80 pyeong or more. there is. For example, the customer can input the number of thermostats through the information input area 523. For example, the customer can input the number of actuators through the information input area 523. For example, the customer can input the number of dispensers through the information input area 523. For example, through the information input area 523, the customer can input whether there is a controller, whether there is no controller, or whether even if there is a controller, they do not wish to replace it. For example, through the information input area 523, the customer can input whether there is a constant flow valve, whether there is a constant flow valve, or whether even if there is a replacement valve, the customer does not wish to replace it.

When the necessary information has been entered, the customer terminal device 120 may transmit a self-quotation request request including the necessary information for generating a self-quotation to the electronic device 110. The electronic device 110 may generate a self-quotation regarding heating pipe repair and installation based on information required to generate a self-quotation. The electronic device 110 may transmit the generated self-quotation to the customer terminal device 120.

According to one embodiment, the electronic device 110 may generate an estimate for the temperature controller based on information about the number of temperature controllers and the unit price of the temperature controller. The electronic device 110 may generate an estimate for a driver based on information about the number of drivers and the unit price of the driver. The electronic device 110 may generate an estimate for the dispenser based on information about the number of mouths of the dispenser and the unit price of the dispenser corresponding to the number of mouths of the dispenser. The electronic device 110 may generate an estimate for the controller based on the information regarding the presence or absence of the controller and the unit price of the controller. The electronic device 110 may generate an estimate for the constant flow rate valve based on the information regarding the presence or absence of the constant flow rate valve and the unit price of the constant flow rate valve.

The electronic device 110 includes an estimate for the temperature controller, an estimate for the driver, an estimate for the distributor, an estimate for the controller, an estimate for the constant flow valve, a predetermined construction cost, and a predetermined price of piping accessories. Based on this, the self-quote can be generated. For example, the electronic device 110 may include an estimate for the temperature controller, an estimate for the driver, an estimate for the distributor, an estimate for the controller, an estimate for the constant flow valve, a predetermined construction cost, and a predetermined piping. By adding up the prices of all accessories, you can create the self-quote.

The customer terminal device 120 may display a save quotation icon 525a and a recalculate icon 525b in the self-quotation request area 525. If the save quote icon 525a is selected, the information entered by the current customer and the self-quote created accordingly can be saved. If the recalculate icon 525b is selected, the information currently entered by the customer can be reset and the self-quotation page 520 can be displayed again.

According to one embodiment, the self-quotation request may include information about the product desired by the customer among entry-level products or premium products. For example, a customer may select either an entry-level product or a premium product, and electronic device 110 may generate a self-quote based on the selected type of product. Here, the unit price of the temperature controller, the unit price of the driver, the unit price of the distributor, the unit price of the controller, and the unit price of the constant flow valve may be determined based on information about the product desired by the customer. For example, if the customer selects an entry-level product, the unit price of the temperature controller may be 100,000 won, and if the customer selects a premium product, the unit price of the temperature controller may be 200,000 won.

According to one embodiment, the electronic device 110 may input information about the type of building to be constructed, information about the square footage of the building to be constructed, and information about the construction year of the building to be constructed into the second correlation model. there is. The electronic device 110 may obtain information about the number of temperature controllers, information about the number of drivers, information about the number of distributors, information about the presence or absence of a controller, and information about the presence of a constant flow valve from the second correlation model. The second correlation model uses, according to a machine learning algorithm, a set of information about a plurality of building types, information about the square footage of a plurality of buildings, and information about the number of years of construction of the plurality of buildings as training input data, and uses the plurality of buildings as training input data. A set of information on the number of thermostats corresponding to each building, information on the number of actuators, information on the number of distributors, information on the presence or absence of a controller, and information on the presence or absence of a constant flow valve are used as training output data, and the above training is performed. It may be an artificial intelligence model built by modeling the correlation between input data for training and the output data for training.

FIG. 6 is a flowchart of the operation of the electronic device 110 according to various embodiments of the present disclosure.

Referring to the operation flowchart 600, in operation 610, the processor 111 of the electronic device 110 performs heating pipe repair with the first customer terminal device 120 among the plurality of customer terminal devices 120. and transmit information to generate either a professional quote or a self-quote for the installation. The first customer can select either an expert quote or a self-quote regarding heating pipe repair and installation through the first customer terminal device 120.

In operation 620, the processor 111 according to various embodiments, in response to receiving a request for generating an expert quotation from the first customer terminal device 120, provides information necessary for generating an expert quotation to the first customer. A request can be made to the terminal device 120. Information needed to generate an expert quote may include a photo of the distributor and a photo of at least one thermostat.

The processor 111 according to various embodiments may receive, from the first customer terminal device 120, a request for an expert quote including a photo of a dispenser and a photo of at least one thermostat in operation 630. The first customer may upload a photo of the dispenser and a photo of at least one temperature controller through the first customer terminal device 120, and the first customer terminal device 120 may upload a photo of the dispenser and a photo of the at least one temperature controller to the electronic device 110. You can send a photo of at least one thermostat.

The processor 111 according to various embodiments may transmit the expert quotation request request including a photo of the dispenser and a photo of at least one temperature controller to the expert terminal device 130 in operation 640. The processor 111 transmits a photo of the dispenser and a photo of at least one temperature controller received from the first customer terminal device 120 to the expert terminal device 130, and sends a request for an expert quotation to the expert terminal device 130. Can be transmitted. An expert can generate an expert estimate through the expert terminal device 130. A professional estimate may include, for example, items needing repairs or installation related to heating piping and an estimated cost.

According to one embodiment, the processor 111 may input a photo of the distributor into the first correlation model. The processor 111 may obtain information about the number of spheres of the divider from the first correlation model. The processor 111 may transmit information about the number of dispensers to the expert terminal device 130. The first correlation model uses a set of photos of a plurality of distributors as input data for training, according to a machine learning algorithm, and uses a set of information about the number of spheres of the distributor corresponding to each of the plurality of distributors as output data for training. , It may be an artificial intelligence model built by modeling the correlation between the training input data and the training output data. That is, the processor 111 may transmit a photo of the dispenser to the expert terminal device 130, and may also transmit information about the number of mouths of the dispenser to the expert terminal device 130 along with the photo of the dispenser. In this case, experts can generate more accurate estimates.

The processor 111 according to various embodiments may receive, from the expert terminal device 130, an expert quotation for repair and installation of heating pipes corresponding to the expert quotation request in operation 650. The expert terminal device 130 may transmit the generated expert estimate to the electronic device 110 .

The processor 111 according to various embodiments may transmit an expert quote regarding heating pipe repair and installation to the first customer terminal device 120 in operation 660. The processor 111 may transmit the expert quotation received from the expert terminal device 130 to the first customer terminal device 120.

According to one embodiment, the processor 111 provides information about the number of the dispenser to the node of the first customer terminal device 120 in a blockchain network formed with each of the plurality of customer terminal devices 120 as nodes. It can be stored in block form. The processor 111 may obtain a reward in response to storing information about the number of the dispenser in block form in the node of the first customer terminal device 120. The processor 111 may transmit the obtained reward to the first customer terminal device 120. The reward may be a cryptocurrency mined based on information about the number of coins of the dispenser and delivered to a cryptocurrency wallet allocated to the first customer terminal device 120.

According to this embodiment, the first customer may be provided with an expert quote on heating pipe repair and installation by uploading a photo of the distributor and a photo of at least one thermostat through the first customer terminal device 120. .

FIG. 7 is a flowchart of the operation of the electronic device 110 according to various embodiments of the present disclosure.

Referring to the operation flowchart 700, in operation 710, the processor 111 according to various embodiments provides an expert quote regarding heating pipe repair and installation to the second customer terminal device 120 among the plurality of customer terminal devices 120. Alternatively, you can send us your information to create one of our self-quotes. The second customer can select either an expert quote or a self-quote regarding heating pipe repair and installation through the second customer terminal device 120.

The processor 111 according to various embodiments, in operation 720, in response to receiving a request for generating a self-quotation from the second customer terminal device 120, provides information necessary for generating a self-quote to the second customer. A request can be made to the terminal device 120. The information required to create a self-quotation is: information about the type of building to be constructed, information about the square footage of the building to be constructed, information about the construction year of the building to be constructed, information about the number of thermostats, information about the number of actuators, and distributor. It may include information on the number of holes, information on the presence or absence of a controller, and information on the presence or absence of a constant flow valve.

The processor 111 according to various embodiments may receive a self-quotation request request including information necessary to generate a self-quotation from the second customer terminal device 120 in operation 730. The second customer may input information necessary to create a self-quotation through the second customer terminal device 120. When the input of necessary information is completed, the second customer terminal device 120 may transmit a self-quotation request request including the input information to the electronic device 110.

The processor 111 according to an embodiment may input information about the type of building to be constructed, information about the square footage of the building to be constructed, and information about the construction year of the building to be constructed into the second correlation model. . The processor 111 may obtain information about the number of temperature controllers, information about the number of drivers, information about the number of distributors, information about the presence or absence of a controller, and information about the presence or absence of a constant flow valve from the second correlation model. The second correlation model uses, according to a machine learning algorithm, a set of information about a plurality of building types, information about the square footage of a plurality of buildings, and information about the number of years of construction of the plurality of buildings as training input data, and uses the plurality of buildings as training input data. A set of information on the number of thermostats corresponding to each building, information on the number of actuators, information on the number of distributors, information on the presence or absence of a controller, and information on the presence or absence of a constant flow valve are used as training output data, and the above training is performed. It may be an artificial intelligence model built by modeling the correlation between input data for training and the output data for training.

The processor 111 according to various embodiments may generate a self-quotation for heating pipe repair and installation based on information required to generate a self-quotation in operation 740.

According to one embodiment, in order to generate a self-quote for heating pipe repair and installation, an estimate for the thermostat is generated based on information about the number of thermostats and the unit price of the thermostat, and information about the number of actuators is generated. and based on the unit price of the actuator, generate an estimate for the actuator, generate an estimate for the distributor based on information about the number of pieces of the distributor and the distributor unit price corresponding to the number of pieces of the distributor, and determine the presence or absence of the controller. Based on the information and the unit price of the controller, a quotation for the controller is generated, and based on the information about the presence or absence of the constant flow valve and the unit price of the constant flow valve, a quotation for the constant flow valve is generated, and the temperature controller is generated. The self-quotation can be generated based on a quotation, an quotation for the actuator, an quotation for the distributor, an quotation for the controller, an quotation for the constant flow valve, a predetermined construction cost, and a predetermined price of piping accessories. .

According to one embodiment, the self-quotation request may include information about the product desired by the customer among entry-level products or premium products. According to one embodiment, the unit price of the temperature controller, the unit price of the driver, the unit price of the distributor, the unit price of the controller, and the unit price of the constant flow valve may be determined based on information about the product desired by the customer.

The processor 111 according to various embodiments may transmit a self-quotation regarding heating pipe repair and installation to the second customer terminal device 120 in operation 750.

According to this embodiment, the second customer can receive a self-quotation by entering necessary information regarding heating pipe repair and installation through the second customer terminal device 120.

According to an embodiment of the present disclosure, after the processor 111 calculates the self-quote, when receiving an image including a dispenser and at least one temperature controller through a customer terminal device, the self-quote and the dispenser and at least one An image including a temperature controller may be transmitted to the expert terminal device 130.

The expert terminal device 130 may adjust the quantity that is the subject of self-quotation calculation based on the image including the dispenser and at least one temperature controller. As an example, the expert terminal device 130 may adjust the quantity that is the subject of self-quotation calculation based on the number of pipes in the distributor.

In addition, according to an embodiment of the present disclosure, the processor can calculate self-quotes at different unit prices based on access permission information of the user terminal device. Illustratively, when self-quotation calculation is requested by the user terminal device to which the first access permission information is assigned, the processor calculates the unit price of the temperature controller, the unit price of the driver, the unit price of the distributor, the unit price of the controller, and the unit price of the constant flow valve. It can be calculated based on a pre-designated first unit price table. When self-quotation calculation is requested by a user terminal device assigned with second access permission information of a higher level than the first access permission information, the processor determines the unit price of the temperature controller, the unit price of the driver, the unit price of the distributor, the unit price of the controller, and the unit price of the controller. The unit price of the flow valve may be calculated based on a second unit price table composed of a lower amount than the unit price of the first unit price table.

Although the process steps, method steps, algorithms, etc. are described in a sequential order in the flow diagrams shown in FIGS. 6-7, such processes, methods, and algorithms may be configured to operate in any suitable order. In other words, the steps of the processes, methods and algorithms described in various embodiments of this disclosure do not need to be performed in the order described in this disclosure. Additionally, although some steps are described as being performed non-concurrently, in other embodiments, some such steps may be performed concurrently. Additionally, illustration of a process by depiction in the drawings does not mean that the illustrated process excludes other variations and modifications thereto, and that any of the illustrated process or steps thereof may be used in various embodiments of the present disclosure. It does not imply that more than one is required, nor does it imply that the illustrated process is preferred.

Although the method has been described through specific embodiments, the method can also be implemented as computer-readable code on a computer-readable recording medium. Computer-readable recording media include all types of recording devices that store data that can be read by a computer system. Examples of computer-readable recording media may include ROM, RAM, CD-ROM, magnetic tape, floppy disk, and optical data storage devices. Additionally, the computer-readable recording medium can be distributed in a computer system connected to a network, so that the computer-readable code can be stored and executed in a distributed manner. And, functional programs, codes, and code segments for implementing the above embodiments can be easily deduced by programmers in the technical field to which this disclosure pertains.

As above, exemplary embodiments have been disclosed in the drawings and specification. Although embodiments have been described in this specification using specific terms, this is only used for the purpose of explaining the technical idea of the present disclosure and is not used to limit the meaning or scope of the present disclosure as set forth in the claims. . Therefore, those skilled in the art will understand that various modifications and other equivalent embodiments are possible therefrom. Therefore, the true technical protection scope of the present disclosure should be determined by the technical spirit of the attached patent claims.

Claims (7)

A method of providing estimates for heating piping repair and installation, performed by an electronic device, comprising:
transmitting, to a first customer terminal device among a plurality of customer terminal devices, information for generating one of an expert quotation or a self-quotation regarding heating pipe repair and installation;
In response to receiving a request for generating the expert quotation from the first customer terminal device, requesting information necessary for generating the expert quotation to the first customer terminal device;
Receiving a request for an expert quotation corresponding to the request from the first customer terminal device;
Receiving an expert quotation for heating pipe repair and installation corresponding to the expert quotation request from the expert terminal device; and
Transmitting an expert quote for repair and installation of the heating pipe to the first customer terminal device based on information about the number of holes of the distributor
How to provide estimates for heating piping repair and installation, including. According to paragraph 1,
The information required to generate the expert quotation and the request for the expert quotation are:
A method of providing a quote regarding heating piping repair and installation, comprising: a photograph of a distributor and a photograph of at least one thermostat. According to paragraph 2,
Inputting a photo of the distributor into a first correlation model;
Obtaining information about the number of spheres of the divider from the first correlation model; and
Further comprising transmitting information about the number of mouths of the dispenser to the expert terminal device,
The first correlation model uses a set of photos of a plurality of distributors as input data for training, and a set of information about the number of distributors corresponding to each of the plurality of distributors as output data for training, according to a machine learning algorithm. Thus, a method of providing estimates for heating pipe repair and installation, which is an artificial intelligence model built by modeling the correlation between the training input data and the training output data. According to paragraph 2,
In response to receiving a request for generating the self-quote from a second customer terminal device among the plurality of customer terminal devices, requesting information necessary for generating the self-quote to the second customer terminal device;
Receiving, from the second customer terminal device, a self-quotation request request including information necessary for generating the self-quotation;
Generating a self-quote for heating pipe repair and installation based on the information required to generate the self-quote; and
A method of providing a quote for heating pipe repair and installation, further comprising transmitting a self-quote for heating pipe repair and installation to the second customer terminal device. According to paragraph 4,
The information required to create the above self-quote is:
Information on the type of building to be constructed, information on the square footage of the building to be constructed, information on the construction year of the building to be constructed, information on the number of temperature controllers, information on the number of actuators, information on the number of distributors, and information on the presence or absence of a controller. A method of providing estimates for heating piping repair and installation, characterized in that it includes information regarding the presence and absence of constant flow valves. According to clause 6,
The step of creating the self-quote is,
generating an estimate for a temperature controller based on information about the number of temperature controllers and a unit price of the temperature controller;
Generating an estimate for an actuator based on information about the number of actuators and a unit price of the actuator;
generating an estimate for the dispenser based on information about the number of mouths of the dispenser and a unit price of the dispenser corresponding to the number of mouths of the dispenser;
generating an estimate for the controller based on the information regarding the presence or absence of the controller and the unit price of the controller;
generating an estimate for the constant flow valve based on the information regarding the presence or absence of the constant flow valve and the unit price of the constant flow valve; and
Based on the quotation for the temperature controller, the quotation for the actuator, the quotation for the distributor, the quotation for the controller, the quotation for the constant flow valve, the predetermined construction cost, and the predetermined price of the piping accessories, the self-quotation A method of providing estimates for heating piping repair and installation, including steps for generating a. According to clause 6,
The self-quotation request includes information about the product desired by the customer of the second customer terminal device, among entry-level products or premium products,
The unit price of the temperature controller, the unit price of the driver, the unit price of the distributor, the unit price of the controller, and the unit price of the constant flow valve are determined based on information about the product desired by the customer for heating pipe repair and installation. How to provide a quote.