system

Abstract

The system according to this embodiment aims to generate design proposals based on customer wishes and needs, monitor the construction process, and provide consistent after-sales care after handover. [Solution] The system according to the embodiment comprises a reception unit, a generation unit, an estimation unit, a management unit, a monitoring unit, a handover unit, and a care unit. The reception unit receives customer requests and needs. The generation unit generates design proposals based on the information received by the reception unit. The estimation unit estimates the cost of the design proposals generated by the generation unit. The management unit procures materials based on the cost estimated by the estimation unit. The monitoring unit monitors the construction process based on the materials procured by the management unit. The handover unit performs final checks and adjustments to the construction process monitored by the monitoring unit. The care unit provides after-sales care after the handover by the handover unit.

Description

Technical Field

[0001] The technology of the present disclosure relates to a system.

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, and includes steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance that responds to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In the conventional technology, there is a problem that it is difficult to consistently perform from the generation of a design plan based on customer wishes and needs to the monitoring of the construction process and aftercare after delivery.

[0005] The system according to the embodiment aims to consistently generate a design plan based on customer wishes and needs, monitor the construction process, and perform aftercare after delivery.

Means for Solving the Problems

[0006] The system according to this embodiment comprises a reception unit, a generation unit, an estimation unit, a management unit, a monitoring unit, a handover unit, and a care unit. The reception unit receives customer requests and needs. The generation unit generates design proposals based on the information received by the reception unit. The estimation unit estimates the cost of the design proposals generated by the generation unit. The management unit procures materials based on the cost estimated by the estimation unit. The monitoring unit monitors the construction process based on the materials procured by the management unit. The handover unit performs final checks and adjustments to the construction process monitored by the monitoring unit. The care unit provides after-sales care after the handover by the handover unit. [Effects of the Invention]

[0007] The system according to this embodiment can generate design proposals based on customer wishes and needs, monitor the construction process, and provide consistent after-sales care after handover. [Brief explanation of the drawing]

[0008] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Modes for carrying out the invention]

[0009] Hereinafter, an example of an embodiment of the system relating to the technology of this disclosure will be described with reference to the attached drawings.

[0010] First, let's explain the terminology used in the following explanation.

[0011] In the following embodiments, the signed processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Furthermore, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include CPU (Central Processing Unit), GPU (Graphics Processing Unit), GPGPU (General-Purpose computing on Graphics Processing Units), APU (Accelerated Processing Unit), or TPU (Tensor Processing Unit).

[0012] In the following embodiments, signed RAM (Random Access Memory) is a memory that temporarily stores information and is used as work memory by the processor.

[0013] In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0014] In the following embodiments, the labeled communication I / F (Interface) is an interface including a communication processor, an antenna, and the like. The communication I / F controls communication between a plurality of computers. Examples of communication standards applied to the communication I / F include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0015] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B". That is, "A and / or B" means that it may be only A, only B, or a combination of A and B. Also, in this specification, when expressing three or more matters connected by "and / or", the same concept as "A and / or B" is applied.

[0016] [First Embodiment] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0017] As shown in FIG. 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0018] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. Also, the database 24 and the communication I / F 26 are connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0019] The smart device 14 comprises a computer 36, a receiving device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The receiving device 38, output device 40, and camera 42 are also connected to the bus 52.

[0020] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, and accepts user input. The touch panel 38A accepts user input via touch by detecting contact with an object (e.g., a pen or finger). The microphone 38B accepts user input via voice by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 (see Figure 2) acquires the data indicating the user input.

[0021] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user by outputting the data in a form perceptible to the user (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0022] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0023] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0024] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0025] Storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0026] In the smart device 14, specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. The specific processing program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as a control unit 46A according to the specific processing program 60 executed on the RAM 48. The smart device 14 also has a data generation model 58 and an emotion identification model 59, similar to the data generation model and emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0027] Furthermore, other devices besides the data processing device 12 may also have the data generation model 58. For example, a server device (e.g., a generation server) may have the data generation model 58. In this case, the data processing device 12 obtains processing results (such as prediction results) using the data generation model 58 by communicating with the server device having the data generation model 58. The data processing device 12 may also be a server device or a terminal device owned by a user (e.g., a mobile phone, robot, home appliance, etc.). Next, an example of processing by the data processing system 10 according to the first embodiment will be described.

[0028] (Example of form 1) The building project management system according to an embodiment of the present invention is a system that receives customer wishes and needs, generates design proposals, estimates costs, procures materials, monitors the construction process, performs final checks, handover, and provides after-sales service. The system begins with the customer communicating their wishes and needs to an AI agent. Next, the generating AI agent automatically generates multiple design proposals, which the customer selects. Subsequently, an automated estimation system makes proposals based on the budget and adjusts the design. Once construction begins, a supply chain management agent procures the necessary materials, and a progress monitoring agent monitors the construction process. After completion, a final check and adjustments are performed, and the project is handed over to the customer. Furthermore, interior design proposals and maintenance services are continuously provided. For example, when a customer communicates their wishes and needs to an AI agent, an interactive AI chatbot is introduced to collect detailed requirements and wishes through dialogue with the customer. The system gathers information about the customer's lifestyle, design preferences, budget, special requirements, etc., through questions and dialogues, and stores it in a database. Next, the generating AI agent automatically generates custom design proposals based on the collected requirements. Multiple design proposals are provided, and VR or AR technology is used to allow the customer to virtually experience and evaluate the designs. Subsequently, a cost calculation algorithm is used to automate real-time cost estimations for each design proposal. Optimization is performed based on the client's budget, proposing appropriate options while maintaining a balance between design and cost. Once construction begins, a supply chain management agent selects and procures the best suppliers of necessary materials, furniture, and equipment. A construction progress monitoring system, integrated with IoT sensors, tracks the construction process in real time, notifying the client and construction team of any anomalies or delays. After completion, final checks and adjustments are performed before handing the home over to the client. Furthermore, personalized service agents are introduced to provide interior design and furniture placement suggestions, home maintenance plans, and more. Even after the client moves in, regular follow-ups and customized lifestyle support services are provided to ensure long-term satisfaction.This allows the construction project management system to generate design proposals based on customer wishes and needs, estimate costs, procure materials, monitor the construction process, perform final checks, hand over the project, and provide after-sales service.

[0029] The building project management system according to this embodiment comprises a reception unit, a generation unit, an estimation unit, a management unit, a monitoring unit, a handover unit, and a care unit. The reception unit receives customer requests and needs. The reception unit, for example, implements an interactive AI chatbot to collect detailed requirements and requests through dialogue with customers. The generation unit generates design proposals based on the information received by the reception unit. The generation unit, for example, automatically generates custom design proposals based on the collected requirements. The generation unit provides multiple design proposals and uses VR or AR technology to allow customers to virtually experience and evaluate the designs. The estimation unit estimates the cost of the design proposals generated by the generation unit. The estimation unit, for example, automates real-time cost estimation for each design proposal using a cost calculation algorithm. The management unit procures materials based on the costs estimated by the estimation unit. The management unit, for example, selects and procures the best suppliers of necessary materials, furniture, and equipment. The monitoring unit monitors the building process based on the materials procured by the management unit. The monitoring department tracks the construction process in real time using, for example, a construction progress monitoring system linked with IoT sensors, and notifies the customer and construction team of any abnormalities or delays. The handover department performs final checks and adjustments to the construction process monitored by the monitoring department. The handover department performs final checks and adjustments and hands over the property to the customer. The care department provides after-sales care after the handover by the handover department. The care department provides, for example, interior design and furniture placement suggestions, and home maintenance plans. Thus, the construction project management system according to this embodiment can generate design proposals based on the customer's wishes and needs, and perform cost estimation, material procurement, construction process monitoring, final checks, handover, and after-sales care.

[0030] The reception department receives customer requests and needs. For example, the reception department can implement an interactive AI chatbot to collect detailed requirements and requests through dialogue with customers. Specifically, the AI ​​chatbot uses natural language processing technology to understand customer input and asks appropriate questions to collect detailed information such as the customer's desired architectural style, budget, materials to be used, and desired completion date. Furthermore, the AI ​​chatbot can generate responses in real time based on the customer's answers and ask additional questions as needed to gain a more accurate understanding of the customer's needs. For example, if a customer desires a specific design style, the AI ​​chatbot can present images and examples related to that style to help the customer further concretize their preferences. The AI ​​chatbot also stores customer requests in a database for use in subsequent processes. This allows the reception department to efficiently and accurately collect customer needs and smoothly move on to the next step.

[0031] The generation unit generates design proposals based on information received by the reception unit. For example, the generation unit automatically generates custom design proposals based on collected requirements. Specifically, the generation unit uses AI to analyze customer requirements and generate multiple design proposals. The AI ​​learns from past design data and architectural trends to propose the design proposal best suited to the customer's needs. For example, the AI ​​selects the optimal layout and materials based on the customer's desired architectural style and budget, and generates a design proposal. The generation unit also uses VR and AR technology to allow customers to virtually experience and evaluate the designs. By wearing a VR headset, customers can experience the generated design proposals in a virtual space and walk around the interior of the actual building. This allows customers to check the details of the design proposals and request revisions or changes as needed. Furthermore, the generation unit can reflect customer feedback in real time and update the design proposals. This enables the generation unit to provide the optimal design proposal that meets customer needs and improve customer satisfaction.

[0032] The Estimation Department estimates the cost of the design proposals generated by the Generation Department. The Estimation Department automates real-time cost estimation for each design proposal, for example, using a cost calculation algorithm. Specifically, the Estimation Department meticulously calculates the costs of materials, labor, and equipment included in the design proposal to estimate the total cost. The cost calculation algorithm provides accurate cost estimates based on the latest market prices and historical project data. For example, the algorithm calculates the cost of each item, taking into account the type and quantity of materials used, and the time and labor required for construction. The Estimation Department also compares costs across multiple design proposals to provide the customer with the best option. Furthermore, the Estimation Department visually displays the cost estimation results in an easy-to-understand format for the customer. This allows the Estimation Department to provide customers with highly transparent cost information and support budget management.

[0033] The management department procures materials based on costs estimated by the estimation department. For example, the management department selects and procures the most suitable suppliers of necessary materials, furniture, and equipment. Specifically, based on the estimation results, the management department creates a list of necessary materials and equipment and selects the most suitable suppliers. The management department considers supplier evaluations and past transaction history to select suppliers that meet conditions such as quality, cost, and delivery time. Furthermore, to streamline the procurement process, the management department implements an electronic procurement system, automating the process from order placement to delivery. This allows the management department to reduce procurement costs and shorten delivery times. In addition, the management department verifies the quality of procured materials and equipment, conducting inspections and tests as needed. This ensures that the management department reliably procures the necessary materials and equipment for construction projects, allowing the project to progress smoothly.

[0034] The monitoring department monitors the construction process based on materials procured by the management department. For example, the monitoring department tracks the construction process in real time using a construction progress monitoring system linked with IoT sensors, and notifies the customer and construction team of any anomalies or delays. Specifically, the monitoring department monitors the progress of construction and environmental conditions in real time through IoT sensors installed at the construction site. For example, the sensors collect data such as temperature, humidity, vibration, and location information and transmit it to a central monitoring system. The monitoring department analyzes this data to understand the progress of construction and immediately notifies relevant parties if any anomalies or delays occur. Furthermore, the monitoring department has introduced real-time chat and video conferencing systems to facilitate communication with the construction team and to resolve problems early. This allows the monitoring department to efficiently monitor the construction process and ensure the smooth progress of the project.

[0035] The Handover Department performs the final checks and adjustments to the construction process, which has been monitored by the Supervision Department. For example, the Handover Department performs the final checks and adjustments and hands over the building to the customer. Specifically, in the final stages of the construction project, the Handover Department conducts detailed inspections to confirm that the construction has been carried out according to the design. For example, they check the building's structure, interior, and the operation of equipment to ensure that quality standards are met. The Handover Department also conducts final confirmations with the customer and makes adjustments and corrections as necessary. For example, if the customer is dissatisfied with a particular part, they will correct or improve that part to increase customer satisfaction. Furthermore, the Handover Department provides explanations on how to use and maintain the building, supporting the customer so that they can use their new building with peace of mind. In this way, the Handover Department can ensure quality in the final stages of the construction project and hand over the building to the customer in a satisfactory manner.

[0036] The Care Department provides after-sales care following the handover by the Handover Department. For example, the Care Department offers interior design and furniture placement suggestions, and home maintenance plans. Specifically, the Care Department proposes interior designs tailored to the customer's lifestyle and preferences, and advises on the placement of furniture and decorations. The Care Department also creates long-term maintenance plans for the building and provides schedules for regular inspections and repairs. For example, they conduct regular checks of various parts of the building, such as roof and exterior wall inspections, and maintenance of plumbing and electrical equipment, and respond quickly if problems arise. Furthermore, the Care Department responds to customer inquiries and requests, providing after-sales service. For instance, if a customer has questions about how to use a particular piece of equipment, the Care Department provides detailed explanations and on-site support as needed. In this way, the Care Department helps customers live comfortably in their new homes and improves long-term customer satisfaction.

[0037] The reception department can implement an interactive AI chatbot to collect detailed requirements and preferences from customers through dialogue. For example, the reception department can use natural language processing technology to engage with customers and gather detailed requirements and preferences. Furthermore, the reception department can use a dialogue management system to ensure smooth interactions with customers. In addition, the reception department can also engage with customers through a user interface to collect detailed requirements and preferences. This allows for the collection of more accurate information by gathering detailed requirements and preferences through dialogue with customers.

[0038] The generation unit can automatically generate custom design proposals based on collected requirements. For example, the generation unit sets parameters based on customer requirements and generates custom design proposals using an automated generation algorithm. The generation unit can also generate custom design proposals based on customer requirements using generation AI. Furthermore, the generation unit can adjust the level of detail of the design proposals based on the collected requirements. This allows for the automatic generation of custom design proposals based on collected requirements, enabling the provision of design proposals that meet customer needs.

[0039] The generation unit can provide multiple design options and allow customers to virtually experience and evaluate the designs using VR and AR technologies. For example, the generation unit can enable customers to virtually experience the designs using a head-mounted display. It can also enable customers to virtually experience the designs using a smartphone app. Furthermore, the generation unit can enable customers to virtually experience the designs using 3D modeling software. This allows customers to more concretely understand the design options by enabling them to virtually experience and evaluate the designs using VR and AR technologies.

[0040] The estimation unit can automate real-time cost estimation for each design proposal using cost calculation algorithms. For example, the estimation unit can perform cost estimation using linear regression. It can also perform cost estimation using neural networks. Furthermore, it can perform cost estimation using heuristic methods. This enables the provision of fast and accurate estimates by automating real-time cost estimation using cost calculation algorithms.

[0041] The management department can select and procure the most suitable suppliers for necessary materials, furniture, and equipment. The management department selects the best suppliers based on criteria such as price, quality, delivery time, and reliability. They can also select the best suppliers by referring to past procurement data. Furthermore, they can select the best suppliers based on the customer's budget. This enables efficient material procurement by selecting and procuring the most suitable suppliers for necessary materials, furniture, and equipment.

[0042] The monitoring unit can track the construction process in real time using a construction progress monitoring system that integrates with IoT sensors. The monitoring unit uses a construction progress monitoring system equipped with features such as sensor type, data collection method, and real-time display. Furthermore, the monitoring unit can monitor construction progress in real time based on data from IoT sensors. In addition, the monitoring unit can notify the customer and construction team if it detects anomalies or delays. This allows for the rapid detection of anomalies and delays by tracking the construction process in real time using a construction progress monitoring system integrated with IoT sensors.

[0043] The Care Department can provide services such as interior design and furniture placement suggestions, and home maintenance plans. For example, the Care Department can offer interior design and furniture placement proposals that include design concepts, layout simulations, and proposal formats. Furthermore, the Care Department can customize maintenance plans based on the client's lifestyle and design preferences. In addition, the Care Department can provide regular follow-up and customized lifestyle support services. This ensures long-term client satisfaction by providing services such as interior design, furniture placement suggestions, and home maintenance plans.

[0044] The reception desk can analyze a customer's past project history and select the most appropriate question format. For example, it can automatically generate relevant questions based on a customer's past project history. It can also prioritize suggesting question formats (text, voice, etc.) that the customer has used in the past. Furthermore, the reception desk can predict specific needs and preferences from the customer's past project history and adjust the question format accordingly. This allows for the selection of the most suitable question format by analyzing the customer's past project history.

[0045] The reception desk can customize the content of the conversation based on the customer's lifestyle and design preferences. For example, the reception desk can automatically generate relevant questions tailored to the customer's lifestyle. It can also make specific suggestions and ask questions based on the customer's design preferences. Furthermore, the reception desk can adjust the tone and style of the conversation based on the customer's lifestyle and design preferences. This allows for more appropriate information gathering by customizing the conversation based on the customer's lifestyle and design preferences.

[0046] The reception desk can collect region-specific requirements and preferences by considering the customer's geographical location. For example, the reception desk can automatically collect region-specific requirements based on the customer's geographical location. It can also predict and collect preferences related to a specific region based on the customer's geographical location. Furthermore, the reception desk can ask region-specific questions, taking the customer's geographical location into consideration. This allows for the collection of region-specific requirements and preferences by considering the customer's geographical location.

[0047] The reception department can analyze customers' social media activity and collect relevant requirements and preferences. For example, the reception department can automatically collect relevant requirements by analyzing customers' social media activity. It can also predict and collect specific preferences based on customers' social media activity. Furthermore, the reception department can ask relevant questions based on customers' social media activity. This allows for the collection of relevant requirements and preferences by analyzing customers' social media activity.

[0048] The generation unit can adjust the level of detail of the design proposal based on the collected requirements. For example, the generation unit can generate a detailed design proposal based on customer requirements. It can also generate a concise design proposal based on customer requirements. Furthermore, the generation unit can generate a customizable design proposal based on customer requirements. This allows for the provision of design proposals that meet customer needs by adjusting the level of detail based on the collected requirements.

[0049] The generation unit can generate optimal design proposals by referring to the customer's past project history. For example, the generation unit generates relevant design proposals based on the customer's past project history. Furthermore, the generation unit can predict specific needs and desires from the customer's past project history and generate design proposals accordingly. In addition, the generation unit can generate optimal design proposals by referring to the customer's past project history. This allows for the generation of optimal design proposals by referencing the customer's past project history.

[0050] The generation unit can generate region-specific design proposals by taking into account the customer's geographical location information. For example, the generation unit generates region-specific design proposals based on the customer's geographical location information. Furthermore, the generation unit can generate design proposals related to a specific region from the customer's geographical location information. In addition, the generation unit can generate region-specific design proposals by taking into account the customer's geographical location information. This allows for the provision of region-specific design proposals by considering the customer's geographical location information.

[0051] The generation unit can analyze a customer's social media activity and generate relevant design proposals. For example, it can analyze a customer's social media activity and generate relevant design proposals. Furthermore, the generation unit can predict specific needs and desires from a customer's social media activity and generate design proposals based on those predictions. In addition, the generation unit can generate relevant design proposals based on a customer's social media activity. This allows for the provision of relevant design proposals by analyzing a customer's social media activity.

[0052] The estimation department can optimize cost estimates for each design proposal based on the customer's budget. For example, the estimation department can provide the optimal cost estimate based on the customer's budget. Furthermore, the estimation department can adjust design proposals based on the customer's budget. In addition, the estimation department can provide estimates that balance cost and quality based on the customer's budget. This allows for the provision of estimates that maintain a balance between cost and quality by optimizing based on the customer's budget.

[0053] The estimation department can improve the accuracy of estimates by referring to past project data. For example, the estimation department can improve the accuracy of estimates based on past project data. Furthermore, the estimation department can predict specific cost elements from past project data and incorporate them into estimates. In addition, the estimation department can improve the accuracy of estimates by referring to past project data. This allows for improved estimation accuracy by referring to past project data.

[0054] The estimation department can perform region-specific cost estimates by taking into account the customer's geographical location. For example, the estimation department can provide region-specific cost estimates based on the customer's geographical location. Furthermore, the estimation department can predict cost elements related to a specific region based on the customer's geographical location and incorporate them into the estimate. In addition, the estimation department can perform region-specific cost estimates by taking into account the customer's geographical location. This allows the department to provide region-specific cost estimates by considering the customer's geographical location.

[0055] The Estimation Department can analyze a customer's social media activity and provide related cost estimates. For example, the Estimation Department can analyze a customer's social media activity and provide related cost estimates. Furthermore, the Estimation Department can predict specific needs and desires from a customer's social media activity and reflect them in the cost estimates. In addition, the Estimation Department can provide related cost estimates based on a customer's social media activity. This allows the Estimation Department to provide relevant cost estimates by analyzing a customer's social media activity.

[0056] The management department can refer to past procurement data when selecting the optimal suppliers for necessary materials, furniture, and equipment. For example, the management department can select the best supplier based on past procurement data. Furthermore, the management department can predict and select suppliers for specific materials or furniture based on past procurement data. In addition, the management department can select the best supplier by referring to past procurement data. This allows for the selection of the optimal supplier by referring to past procurement data.

[0057] The management department can select the optimal procurement method based on the customer's budget during the procurement process. For example, the management department can select the optimal procurement method based on the customer's budget. Furthermore, the management department can select a procurement method that maintains a balance between cost and quality based on the customer's budget. In addition, the management department can select a method that allows for rapid procurement based on the customer's budget. This enables procurement that maintains a balance between cost and quality by selecting the optimal procurement method based on the customer's budget.

[0058] The management department can select region-specific suppliers by considering the customer's geographical location. For example, the management department can select region-specific suppliers based on the customer's geographical location. Furthermore, the management department can select suppliers associated with a specific region based on the customer's geographical location. In addition, the management department can select region-specific suppliers by considering the customer's geographical location. This allows for the selection of region-specific suppliers by considering the customer's geographical location.

[0059] The management department can analyze customers' social media activity and select relevant suppliers. For example, the management department can analyze customers' social media activity and select relevant suppliers. Furthermore, the management department can predict specific needs and desires from customers' social media activity and select suppliers accordingly. In addition, the management department can select relevant suppliers based on customers' social media activity. Thus, by analyzing customers' social media activity, relevant suppliers can be selected.

[0060] The monitoring unit can track construction progress in real time in conjunction with IoT sensors. For example, the monitoring unit uses IoT sensors to track construction progress in real time. Furthermore, the monitoring unit can monitor construction progress in real time based on data from IoT sensors. In addition, the monitoring unit can track construction progress in real time in conjunction with IoT sensors. This allows for the rapid detection of anomalies and delays by tracking construction progress in real time in conjunction with IoT sensors.

[0061] The monitoring unit can quickly notify customers and construction teams if abnormalities or delays occur. For example, the monitoring unit can quickly notify customers and construction teams if abnormalities or delays occur. Furthermore, the monitoring unit can notify customers and construction teams in real time if abnormalities or delays occur. This allows for early resolution of problems by promptly notifying customers and construction teams when abnormalities or delays occur.

[0062] The monitoring unit can apply region-specific monitoring methods, taking into account the customer's geographical location information. For example, the monitoring unit can apply region-specific monitoring methods based on the customer's geographical location information. Furthermore, the monitoring unit can apply monitoring methods relevant to a specific region based on the customer's geographical location information. In addition, the monitoring unit can apply region-specific monitoring methods, taking into account the customer's geographical location information. This allows for the provision of region-specific monitoring methods by considering the customer's geographical location information.

[0063] The monitoring department can analyze customers' social media activity and provide relevant monitoring information. For example, the monitoring department can analyze customers' social media activity and provide relevant monitoring information. Furthermore, the monitoring department can predict specific needs and desires from customers' social media activity and provide monitoring information based on that. In addition, the monitoring department can provide relevant monitoring information based on customers' social media activity. Thus, by analyzing customers' social media activity, relevant monitoring information can be provided.

[0064] The handover unit can select the optimal adjustment method by referring to past project data during the final check. For example, the handover unit can select the optimal adjustment method based on past project data. Furthermore, the handover unit can predict and select a specific adjustment method from past project data. In addition, the handover unit can select the optimal adjustment method by referring to past project data. This allows for the selection of the optimal adjustment method by referring to past project data.

[0065] The delivery department can customize the product at the time of delivery based on the customer's lifestyle and design preferences. For example, the delivery department can customize the product at the time of delivery to match the customer's lifestyle. Furthermore, the delivery department can also customize the product at the time of delivery based on the customer's design preferences. This allows for a more satisfying delivery by customizing the product based on the customer's lifestyle and design preferences.

[0066] The delivery unit can apply region-specific delivery methods, taking into account the customer's geographical location information. For example, the delivery unit can apply region-specific delivery methods based on the customer's geographical location information. Furthermore, the delivery unit can apply delivery methods relevant to specific regions based on the customer's geographical location information. In addition, the delivery unit can apply region-specific delivery methods, taking into account the customer's geographical location information. This allows for the provision of region-specific delivery methods by considering the customer's geographical location information.

[0067] The delivery department can analyze customers' social media activity and provide relevant delivery information. For example, the delivery department can analyze customers' social media activity and provide relevant delivery information. Furthermore, the delivery department can predict specific needs and desires from customers' social media activity and provide delivery information based on that. In addition, the delivery department can provide relevant delivery information based on customers' social media activity. Thus, by analyzing customers' social media activity, relevant delivery information can be provided.

[0068] The Care Department can refer to the client's past project history when proposing interior design and furniture arrangements. For example, the Care Department can propose relevant interior designs and furniture arrangements based on the client's past project history. Furthermore, the Care Department can predict specific needs and desires from the client's past project history and propose interior designs and furniture arrangements accordingly. In addition, the Care Department can propose the most suitable interior designs and furniture arrangements by referring to the client's past project history. This allows for more appropriate interior design and furniture arrangement proposals by referencing the client's past project history.

[0069] The care department can customize home maintenance plans based on the customer's lifestyle and design preferences. For example, the care department can customize home maintenance plans to suit the customer's lifestyle. Furthermore, the care department can customize home maintenance plans based on the customer's design preferences. This allows for the provision of more appropriate maintenance plans by customizing them based on the customer's lifestyle and design preferences.

[0070] The care department can apply region-specific aftercare methods, taking into account the customer's geographical location. For example, the care department can apply region-specific aftercare methods based on the customer's geographical location. Furthermore, the care department can apply aftercare methods relevant to a specific region based on the customer's geographical location. In addition, the care department can apply region-specific aftercare methods, taking into account the customer's geographical location. This allows for the provision of region-specific aftercare methods by considering the customer's geographical location.

[0071] The Care Department can analyze customers' social media activity and provide relevant aftercare information. For example, the Care Department can analyze customers' social media activity and provide relevant aftercare information. Furthermore, the Care Department can predict specific needs and desires from customers' social media activity and provide aftercare information based on that. In short, by analyzing customers' social media activity, the Care Department can provide relevant aftercare information.

[0072] The system according to the embodiment is not limited to the example described above, and various modifications are possible, for example, as follows.

[0073] The reception desk can analyze a customer's past project history and select the most appropriate question format. For example, it can automatically generate relevant questions based on the customer's past project history. The reception desk can also prioritize suggesting question formats (text, voice, etc.) that the customer has used in the past. Furthermore, the reception desk can predict specific needs and preferences from the customer's past project history and adjust the question format accordingly. This allows for the selection of the most suitable question format by analyzing the customer's past project history.

[0074] The generation unit can generate region-specific design proposals by taking into account the customer's geographical location information. For example, it can generate region-specific design proposals based on the customer's geographical location information. Furthermore, the generation unit can generate design proposals related to a specific region from the customer's geographical location information. In addition, the generation unit can generate region-specific design proposals by considering the customer's geographical location information. This allows for the provision of region-specific design proposals by taking the customer's geographical location information into account.

[0075] The estimation department can improve the accuracy of estimates by referring to past project data. For example, it can improve the accuracy of estimates based on past project data. Furthermore, the estimation department can predict specific cost elements from past project data and incorporate them into estimates. In addition, the estimation department can improve the accuracy of estimates by referring to past project data. This means that the accuracy of estimates can be improved by referring to past project data.

[0076] The management department can analyze customers' social media activity and select relevant suppliers. For example, it can analyze customers' social media activity and select relevant suppliers. Furthermore, the management department can predict specific needs and desires from customers' social media activity and select suppliers accordingly. In addition, the management department can select relevant suppliers based on customers' social media activity. Thus, by analyzing customers' social media activity, it is possible to select relevant suppliers.

[0077] The Care Department can customize the content of conversations based on the customer's lifestyle and design preferences. For example, it can automatically generate relevant questions tailored to the customer's lifestyle. The Care Department can also make specific suggestions and ask questions based on the customer's design preferences. Furthermore, the Care Department can adjust the tone and style of the conversation based on the customer's lifestyle and design preferences. This allows for more appropriate information gathering by customizing the conversation based on the customer's lifestyle and design preferences.

[0078] The following briefly describes the processing flow for example form 1.

[0079] Step 1: The reception desk receives customer requests and needs. For example, an interactive AI chatbot is implemented to collect detailed requirements and requests through dialogue with customers. Step 2: The generation unit generates design proposals based on the information received by the reception unit. For example, it automatically generates custom design proposals based on the collected requirements and provides multiple design options. Furthermore, it uses VR and AR technology to allow customers to virtually experience and evaluate the designs. Step 3: The estimation unit estimates the cost of the design proposals generated by the generation unit. For example, it automates real-time cost estimation for each design proposal using a cost calculation algorithm. Step 4: The management department procures materials based on the costs estimated by the estimation department. For example, they select and procure the best suppliers for the necessary materials, furniture, and equipment. Step 5: The monitoring department monitors the construction process based on materials procured by the management department. For example, they track the construction process in real time using a construction progress monitoring system linked with IoT sensors and notify the customer and construction team of any anomalies or delays. Step 6: The handover department performs final checks and adjustments to the construction process, which has been monitored by the supervision department. For example, they perform final checks and adjustments and hand over the building to the customer. Step 7: The Care Department provides after-sales care following the handover by the Handover Department. For example, they offer suggestions for interior design and furniture arrangement, and home maintenance plans.

[0080] (Example of form 2) The building project management system according to an embodiment of the present invention is a system that receives customer wishes and needs, generates design proposals, estimates costs, procures materials, monitors the construction process, performs final checks, handover, and provides after-sales service. The system begins with the customer communicating their wishes and needs to an AI agent. Next, the generating AI agent automatically generates multiple design proposals, which the customer selects. Subsequently, an automated estimation system makes proposals based on the budget and adjusts the design. Once construction begins, a supply chain management agent procures the necessary materials, and a progress monitoring agent monitors the construction process. After completion, a final check and adjustments are performed, and the project is handed over to the customer. Furthermore, interior design proposals and maintenance services are continuously provided. For example, when a customer communicates their wishes and needs to an AI agent, an interactive AI chatbot is introduced to collect detailed requirements and wishes through dialogue with the customer. The system gathers information about the customer's lifestyle, design preferences, budget, special requirements, etc., through questions and dialogues, and stores it in a database. Next, the generating AI agent automatically generates custom design proposals based on the collected requirements. Multiple design proposals are provided, and VR or AR technology is used to allow the customer to virtually experience and evaluate the designs. Subsequently, a cost calculation algorithm is used to automate real-time cost estimations for each design proposal. Optimization is performed based on the client's budget, proposing appropriate options while maintaining a balance between design and cost. Once construction begins, a supply chain management agent selects and procures the best suppliers of necessary materials, furniture, and equipment. A construction progress monitoring system, integrated with IoT sensors, tracks the construction process in real time, notifying the client and construction team of any anomalies or delays. After completion, final checks and adjustments are performed before handing the home over to the client. Furthermore, personalized service agents are introduced to provide interior design and furniture placement suggestions, home maintenance plans, and more. Even after the client moves in, regular follow-ups and customized lifestyle support services are provided to ensure long-term satisfaction.This allows the construction project management system to generate design proposals based on customer wishes and needs, estimate costs, procure materials, monitor the construction process, perform final checks, hand over the project, and provide after-sales service.

[0081] The building project management system according to this embodiment comprises a reception unit, a generation unit, an estimation unit, a management unit, a monitoring unit, a handover unit, and a care unit. The reception unit receives customer requests and needs. The reception unit, for example, implements an interactive AI chatbot to collect detailed requirements and requests through dialogue with customers. The generation unit generates design proposals based on the information received by the reception unit. The generation unit, for example, automatically generates custom design proposals based on the collected requirements. The generation unit provides multiple design proposals and uses VR or AR technology to allow customers to virtually experience and evaluate the designs. The estimation unit estimates the cost of the design proposals generated by the generation unit. The estimation unit, for example, automates real-time cost estimation for each design proposal using a cost calculation algorithm. The management unit procures materials based on the costs estimated by the estimation unit. The management unit, for example, selects and procures the best suppliers of necessary materials, furniture, and equipment. The monitoring unit monitors the building process based on the materials procured by the management unit. The monitoring department tracks the construction process in real time using, for example, a construction progress monitoring system linked with IoT sensors, and notifies the customer and construction team of any abnormalities or delays. The handover department performs final checks and adjustments to the construction process monitored by the monitoring department. The handover department performs final checks and adjustments and hands over the property to the customer. The care department provides after-sales care after the handover by the handover department. The care department provides, for example, interior design and furniture placement suggestions, and home maintenance plans. Thus, the construction project management system according to this embodiment can generate design proposals based on the customer's wishes and needs, and perform cost estimation, material procurement, construction process monitoring, final checks, handover, and after-sales care.

[0082] The reception department receives customer requests and needs. For example, the reception department can implement an interactive AI chatbot to collect detailed requirements and requests through dialogue with customers. Specifically, the AI ​​chatbot uses natural language processing technology to understand customer input and asks appropriate questions to collect detailed information such as the customer's desired architectural style, budget, materials to be used, and desired completion date. Furthermore, the AI ​​chatbot can generate responses in real time based on the customer's answers and ask additional questions as needed to gain a more accurate understanding of the customer's needs. For example, if a customer desires a specific design style, the AI ​​chatbot can present images and examples related to that style to help the customer further concretize their preferences. The AI ​​chatbot also stores customer requests in a database for use in subsequent processes. This allows the reception department to efficiently and accurately collect customer needs and smoothly move on to the next step.

[0083] The generation unit generates design proposals based on information received by the reception unit. For example, the generation unit automatically generates custom design proposals based on collected requirements. Specifically, the generation unit uses AI to analyze customer requirements and generate multiple design proposals. The AI ​​learns from past design data and architectural trends to propose the design proposal best suited to the customer's needs. For example, the AI ​​selects the optimal layout and materials based on the customer's desired architectural style and budget, and generates a design proposal. The generation unit also uses VR and AR technology to allow customers to virtually experience and evaluate the designs. By wearing a VR headset, customers can experience the generated design proposals in a virtual space and walk around the interior of the actual building. This allows customers to check the details of the design proposals and request revisions or changes as needed. Furthermore, the generation unit can reflect customer feedback in real time and update the design proposals. This enables the generation unit to provide the optimal design proposal that meets customer needs and improve customer satisfaction.

[0084] The Estimation Department estimates the cost of the design proposals generated by the Generation Department. The Estimation Department automates real-time cost estimation for each design proposal, for example, using a cost calculation algorithm. Specifically, the Estimation Department meticulously calculates the costs of materials, labor, and equipment included in the design proposal to estimate the total cost. The cost calculation algorithm provides accurate cost estimates based on the latest market prices and historical project data. For example, the algorithm calculates the cost of each item, taking into account the type and quantity of materials used, and the time and labor required for construction. The Estimation Department also compares costs across multiple design proposals to provide the customer with the best option. Furthermore, the Estimation Department visually displays the cost estimation results in an easy-to-understand format for the customer. This allows the Estimation Department to provide customers with highly transparent cost information and support budget management.

[0085] The management department procures materials based on costs estimated by the estimation department. For example, the management department selects and procures the most suitable suppliers of necessary materials, furniture, and equipment. Specifically, based on the estimation results, the management department creates a list of necessary materials and equipment and selects the most suitable suppliers. The management department considers supplier evaluations and past transaction history to select suppliers that meet conditions such as quality, cost, and delivery time. Furthermore, to streamline the procurement process, the management department implements an electronic procurement system, automating the process from order placement to delivery. This allows the management department to reduce procurement costs and shorten delivery times. In addition, the management department verifies the quality of procured materials and equipment, conducting inspections and tests as needed. This ensures that the management department reliably procures the necessary materials and equipment for construction projects, allowing the project to progress smoothly.

[0086] The monitoring department monitors the construction process based on materials procured by the management department. For example, the monitoring department tracks the construction process in real time using a construction progress monitoring system linked with IoT sensors, and notifies the customer and construction team of any anomalies or delays. Specifically, the monitoring department monitors the progress of construction and environmental conditions in real time through IoT sensors installed at the construction site. For example, the sensors collect data such as temperature, humidity, vibration, and location information and transmit it to a central monitoring system. The monitoring department analyzes this data to understand the progress of construction and immediately notifies relevant parties if any anomalies or delays occur. Furthermore, the monitoring department has introduced real-time chat and video conferencing systems to facilitate communication with the construction team and to resolve problems early. This allows the monitoring department to efficiently monitor the construction process and ensure the smooth progress of the project.

[0087] The Handover Department performs the final checks and adjustments to the construction process, which has been monitored by the Supervision Department. For example, the Handover Department performs the final checks and adjustments and hands over the building to the customer. Specifically, in the final stages of the construction project, the Handover Department conducts detailed inspections to confirm that the construction has been carried out according to the design. For example, they check the building's structure, interior, and the operation of equipment to ensure that quality standards are met. The Handover Department also conducts final confirmations with the customer and makes adjustments and corrections as necessary. For example, if the customer is dissatisfied with a particular part, they will correct or improve that part to increase customer satisfaction. Furthermore, the Handover Department provides explanations on how to use and maintain the building, supporting the customer so that they can use their new building with peace of mind. In this way, the Handover Department can ensure quality in the final stages of the construction project and hand over the building to the customer in a satisfactory manner.

[0088] The Care Department provides after-sales care following the handover by the Handover Department. For example, the Care Department offers interior design and furniture placement suggestions, and home maintenance plans. Specifically, the Care Department proposes interior designs tailored to the customer's lifestyle and preferences, and advises on the placement of furniture and decorations. The Care Department also creates long-term maintenance plans for the building and provides schedules for regular inspections and repairs. For example, they conduct regular checks of various parts of the building, such as roof and exterior wall inspections, and maintenance of plumbing and electrical equipment, and respond quickly if problems arise. Furthermore, the Care Department responds to customer inquiries and requests, providing after-sales service. For instance, if a customer has questions about how to use a particular piece of equipment, the Care Department provides detailed explanations and on-site support as needed. In this way, the Care Department helps customers live comfortably in their new homes and improves long-term customer satisfaction.

[0089] The reception department can implement an interactive AI chatbot to collect detailed requirements and preferences from customers through dialogue. For example, the reception department can use natural language processing technology to engage with customers and gather detailed requirements and preferences. Furthermore, the reception department can use a dialogue management system to ensure smooth interactions with customers. In addition, the reception department can also engage with customers through a user interface to collect detailed requirements and preferences. This allows for the collection of more accurate information by gathering detailed requirements and preferences through dialogue with customers.

[0090] The generation unit can automatically generate custom design proposals based on collected requirements. For example, the generation unit sets parameters based on customer requirements and generates custom design proposals using an automated generation algorithm. The generation unit can also generate custom design proposals based on customer requirements using generation AI. Furthermore, the generation unit can adjust the level of detail of the design proposals based on the collected requirements. This allows for the automatic generation of custom design proposals based on collected requirements, enabling the provision of design proposals that meet customer needs.

[0091] The generation unit can provide multiple design options and allow customers to virtually experience and evaluate the designs using VR and AR technologies. For example, the generation unit can enable customers to virtually experience the designs using a head-mounted display. It can also enable customers to virtually experience the designs using a smartphone app. Furthermore, the generation unit can enable customers to virtually experience the designs using 3D modeling software. This allows customers to more concretely understand the design options by enabling them to virtually experience and evaluate the designs using VR and AR technologies.

[0092] The estimation unit can automate real-time cost estimation for each design proposal using cost calculation algorithms. For example, the estimation unit can perform cost estimation using linear regression. It can also perform cost estimation using neural networks. Furthermore, it can perform cost estimation using heuristic methods. This enables the provision of fast and accurate estimates by automating real-time cost estimation using cost calculation algorithms.

[0093] The management department can select and procure the most suitable suppliers for necessary materials, furniture, and equipment. The management department selects the best suppliers based on criteria such as price, quality, delivery time, and reliability. They can also select the best suppliers by referring to past procurement data. Furthermore, they can select the best suppliers based on the customer's budget. This enables efficient material procurement by selecting and procuring the most suitable suppliers for necessary materials, furniture, and equipment.

[0094] The monitoring unit can track the construction process in real time using a construction progress monitoring system that integrates with IoT sensors. The monitoring unit uses a construction progress monitoring system equipped with features such as sensor type, data collection method, and real-time display. Furthermore, the monitoring unit can monitor construction progress in real time based on data from IoT sensors. In addition, the monitoring unit can notify the customer and construction team if it detects anomalies or delays. This allows for the rapid detection of anomalies and delays by tracking the construction process in real time using a construction progress monitoring system integrated with IoT sensors.

[0095] The Care Department can provide services such as interior design and furniture placement suggestions, and home maintenance plans. For example, the Care Department can offer interior design and furniture placement proposals that include design concepts, layout simulations, and proposal formats. Furthermore, the Care Department can customize maintenance plans based on the client's lifestyle and design preferences. In addition, the Care Department can provide regular follow-up and customized lifestyle support services. This ensures long-term client satisfaction by providing services such as interior design, furniture placement suggestions, and home maintenance plans.

[0096] The reception desk can estimate the customer's emotions and adjust how preferences and needs are collected based on those estimates. For example, if the customer is stressed, the reception desk can provide a simple interface and minimize the input steps. If the customer is relaxed, the reception desk can also provide detailed input options and suggest customizable input methods. Furthermore, if the customer is in a hurry, the reception desk can prioritize voice input to quickly collect preferences and needs. This allows for more appropriate information gathering by adjusting how preferences and needs are collected based on the customer's emotions. Emotion estimation is achieved using emotion estimation functions, such as emotion engines or generative AI. Generative AI includes, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI.

[0097] The reception desk can analyze a customer's past project history and select the most appropriate question format. For example, it can automatically generate relevant questions based on a customer's past project history. It can also prioritize suggesting question formats (text, voice, etc.) that the customer has used in the past. Furthermore, the reception desk can predict specific needs and preferences from the customer's past project history and adjust the question format accordingly. This allows for the selection of the most suitable question format by analyzing the customer's past project history.

[0098] The reception desk can customize the content of the conversation based on the customer's lifestyle and design preferences. For example, the reception desk can automatically generate relevant questions tailored to the customer's lifestyle. It can also make specific suggestions and ask questions based on the customer's design preferences. Furthermore, the reception desk can adjust the tone and style of the conversation based on the customer's lifestyle and design preferences. This allows for more appropriate information gathering by customizing the conversation based on the customer's lifestyle and design preferences.

[0099] The reception desk can estimate the customer's emotions and prioritize the information to collect based on those emotions. For example, if the customer is stressed, the reception desk will prioritize collecting the most important information. If the customer is relaxed, the reception desk can also collect more detailed information. Furthermore, if the customer is in a hurry, the reception desk can prioritize information that can be collected quickly. This allows for more efficient information gathering by prioritizing the information to be collected based on the customer's emotions. Emotion estimation is achieved using emotion estimation functions, such as emotion engines or generative AI. Generative AI includes, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI.

[0100] The reception desk can collect region-specific requirements and preferences by considering the customer's geographical location. For example, the reception desk can automatically collect region-specific requirements based on the customer's geographical location. It can also predict and collect preferences related to a specific region based on the customer's geographical location. Furthermore, the reception desk can ask region-specific questions, taking the customer's geographical location into consideration. This allows for the collection of region-specific requirements and preferences by considering the customer's geographical location.

[0101] The reception department can analyze customers' social media activity and collect relevant requirements and preferences. For example, the reception department can automatically collect relevant requirements by analyzing customers' social media activity. It can also predict and collect specific preferences based on customers' social media activity. Furthermore, the reception department can ask relevant questions based on customers' social media activity. This allows for the collection of relevant requirements and preferences by analyzing customers' social media activity.

[0102] The generation unit can estimate the customer's emotions and adjust the presentation of the design proposal based on those emotions. For example, if the customer is relaxed, the generation unit will generate a design proposal that proceeds at a leisurely pace. If the customer is in a hurry, the generation unit can also generate a design proposal that emphasizes the shortest route. Furthermore, if the customer is excited, the generation unit can generate a design proposal with visually stimulating effects. This allows for the provision of more appropriate design proposals by adjusting their presentation based on the customer's emotions. Emotion estimation is achieved using emotion estimation functions, such as an emotion engine or generative AI. Generative AI includes, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI.

[0103] The generation unit can adjust the level of detail of the design proposal based on the collected requirements. For example, the generation unit can generate a detailed design proposal based on customer requirements. It can also generate a concise design proposal based on customer requirements. Furthermore, the generation unit can generate a customizable design proposal based on customer requirements. This allows for the provision of design proposals that meet customer needs by adjusting the level of detail based on the collected requirements.

[0104] The generation unit can generate optimal design proposals by referring to the customer's past project history. For example, the generation unit generates relevant design proposals based on the customer's past project history. Furthermore, the generation unit can predict specific needs and desires from the customer's past project history and generate design proposals accordingly. In addition, the generation unit can generate optimal design proposals by referring to the customer's past project history. This allows for the generation of optimal design proposals by referencing the customer's past project history.

[0105] The generation unit can estimate the customer's emotions and prioritize design proposals based on those emotions. For example, if the customer is relaxed, the generation unit will prioritize detailed design proposals. If the customer is in a hurry, the generation unit can also prioritize design proposals that can be generated quickly. Furthermore, if the customer is excited, the generation unit can prioritize visually stimulating design proposals. This allows for the provision of more appropriate design proposals by prioritizing them based on the customer's emotions. Emotion estimation is achieved using emotion estimation functions, such as emotion engines or generative AI. Generative AI includes, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI.

[0106] The generation unit can generate region-specific design proposals by taking into account the customer's geographical location information. For example, the generation unit generates region-specific design proposals based on the customer's geographical location information. Furthermore, the generation unit can generate design proposals related to a specific region from the customer's geographical location information. In addition, the generation unit can generate region-specific design proposals by taking into account the customer's geographical location information. This allows for the provision of region-specific design proposals by considering the customer's geographical location information.

[0107] The generation unit can analyze a customer's social media activity and generate relevant design proposals. For example, it can analyze a customer's social media activity and generate relevant design proposals. Furthermore, the generation unit can predict specific needs and desires from a customer's social media activity and generate design proposals based on those predictions. In addition, the generation unit can generate relevant design proposals based on a customer's social media activity. This allows for the provision of relevant design proposals by analyzing a customer's social media activity.

[0108] The estimation unit can estimate the customer's emotions and adjust the way the estimate is presented based on those emotions. For example, if the customer is relaxed, the estimation unit can provide a detailed estimate. If the customer is in a hurry, it can provide a concise estimate. Furthermore, if the customer is excited, it can provide a visually stimulating estimate. This allows for the provision of more appropriate estimates by adjusting the presentation based on the customer's emotions. Emotion estimation is achieved using emotion estimation functions, such as emotion engines or generative AI. Generative AI includes, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI.

[0109] The estimation department can optimize cost estimates for each design proposal based on the customer's budget. For example, the estimation department can provide the optimal cost estimate based on the customer's budget. Furthermore, the estimation department can adjust design proposals based on the customer's budget. In addition, the estimation department can provide estimates that balance cost and quality based on the customer's budget. This allows for the provision of estimates that maintain a balance between cost and quality by optimizing based on the customer's budget.

[0110] The estimation department can improve the accuracy of estimates by referring to past project data. For example, the estimation department can improve the accuracy of estimates based on past project data. Furthermore, the estimation department can predict specific cost elements from past project data and incorporate them into estimates. In addition, the estimation department can improve the accuracy of estimates by referring to past project data. This allows for improved estimation accuracy by referring to past project data.

[0111] The estimation department can estimate the customer's emotions and prioritize estimates based on those emotions. For example, if the customer is relaxed, the estimation department might prioritize a detailed estimate. If the customer is in a hurry, it might prioritize an estimate that can be delivered quickly. Furthermore, if the customer is excited, it might prioritize a visually stimulating estimate. This allows for more appropriate estimates to be provided by prioritizing estimates based on customer emotions. Emotion estimation is achieved using emotion estimation functions, such as emotion engines or generative AI. Generative AI includes, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI.

[0112] The estimation department can perform region-specific cost estimates by taking into account the customer's geographical location. For example, the estimation department can provide region-specific cost estimates based on the customer's geographical location. Furthermore, the estimation department can predict cost elements related to a specific region based on the customer's geographical location and incorporate them into the estimate. In addition, the estimation department can perform region-specific cost estimates by taking into account the customer's geographical location. This allows the department to provide region-specific cost estimates by considering the customer's geographical location.

[0113] The Estimation Department can analyze a customer's social media activity and provide related cost estimates. For example, the Estimation Department can analyze a customer's social media activity and provide related cost estimates. Furthermore, the Estimation Department can predict specific needs and desires from a customer's social media activity and reflect them in the cost estimates. In addition, the Estimation Department can provide related cost estimates based on a customer's social media activity. This allows the Estimation Department to provide relevant cost estimates by analyzing a customer's social media activity.

[0114] The management department can estimate customer emotions and adjust material procurement methods based on those estimated emotions. For example, if a customer is relaxed, the management department can provide a detailed material procurement plan. If a customer is in a hurry, the management department can also prioritize materials that can be procured quickly. Furthermore, if a customer is excited, the management department can prioritize visually stimulating materials. This allows for more appropriate material procurement by adjusting procurement methods based on customer emotions. Emotion estimation is achieved using emotion estimation functions, such as emotion engines or generative AI. Generative AI includes, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI.

[0115] The management department can refer to past procurement data when selecting the optimal suppliers for necessary materials, furniture, and equipment. For example, the management department can select the best supplier based on past procurement data. Furthermore, the management department can predict and select suppliers for specific materials or furniture based on past procurement data. In addition, the management department can select the best supplier by referring to past procurement data. This allows for the selection of the optimal supplier by referring to past procurement data.

[0116] The management department can select the optimal procurement method based on the customer's budget during the procurement process. For example, the management department can select the optimal procurement method based on the customer's budget. Furthermore, the management department can select a procurement method that maintains a balance between cost and quality based on the customer's budget. In addition, the management department can select a method that allows for rapid procurement based on the customer's budget. This enables procurement that maintains a balance between cost and quality by selecting the optimal procurement method based on the customer's budget.

[0117] The management department can estimate customer emotions and determine procurement priorities based on those estimated emotions. For example, if a customer is relaxed, the management department might prioritize detailed procurement plans. If a customer is in a hurry, the management department might prioritize materials that can be procured quickly. Furthermore, if a customer is excited, the management department might prioritize visually stimulating materials. This allows for more appropriate material procurement by determining procurement priorities based on customer emotions. Emotion estimation is achieved using emotion estimation functions, such as emotion engines or generative AI. Generative AI includes, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI.

[0118] The management department can select region-specific suppliers by considering the customer's geographical location. For example, the management department can select region-specific suppliers based on the customer's geographical location. Furthermore, the management department can select suppliers associated with a specific region based on the customer's geographical location. In addition, the management department can select region-specific suppliers by considering the customer's geographical location. This allows for the selection of region-specific suppliers by considering the customer's geographical location.

[0119] The management department can analyze customers' social media activity and select relevant suppliers. For example, the management department can analyze customers' social media activity and select relevant suppliers. Furthermore, the management department can predict specific needs and desires from customers' social media activity and select suppliers accordingly. In addition, the management department can select relevant suppliers based on customers' social media activity. Thus, by analyzing customers' social media activity, relevant suppliers can be selected.

[0120] The monitoring unit can estimate customer emotions and adjust the monitoring method of the construction process based on the estimated customer emotions. For example, if the customer is relaxed, the monitoring unit can provide a detailed monitoring report. It can also prioritize monitoring reports that can be provided quickly if the customer is in a hurry. Furthermore, if the customer is excited, the monitoring unit can provide a visually stimulating monitoring report. This allows for more appropriate monitoring by adjusting the monitoring method of the construction process based on customer emotions. Emotion estimation is achieved using emotion estimation functions, such as emotion engines or generative AI. Generative AI includes, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI.

[0121] The monitoring unit can track construction progress in real time in conjunction with IoT sensors. For example, the monitoring unit uses IoT sensors to track construction progress in real time. Furthermore, the monitoring unit can monitor construction progress in real time based on data from IoT sensors. In addition, the monitoring unit can track construction progress in real time in conjunction with IoT sensors. This allows for the rapid detection of anomalies and delays by tracking construction progress in real time in conjunction with IoT sensors.

[0122] The monitoring unit can quickly notify customers and construction teams if abnormalities or delays occur. For example, the monitoring unit can quickly notify customers and construction teams if abnormalities or delays occur. Furthermore, the monitoring unit can notify customers and construction teams in real time if abnormalities or delays occur. This allows for early resolution of problems by promptly notifying customers and construction teams when abnormalities or delays occur.

[0123] The monitoring unit can estimate customer emotions and prioritize monitoring based on those estimated emotions. For example, if a customer is relaxed, the monitoring unit will prioritize detailed monitoring reports. If a customer is in a hurry, the monitoring unit can also prioritize monitoring reports that can be delivered quickly. Furthermore, if a customer is excited, the monitoring unit can prioritize visually stimulating monitoring reports. This allows for more appropriate monitoring by prioritizing monitoring based on customer emotions. Emotion estimation is achieved using emotion estimation functions, such as emotion engines or generative AI. Generative AI includes, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI.

[0124] The monitoring unit can apply region-specific monitoring methods, taking into account the customer's geographical location information. For example, the monitoring unit can apply region-specific monitoring methods based on the customer's geographical location information. Furthermore, the monitoring unit can apply monitoring methods relevant to a specific region based on the customer's geographical location information. In addition, the monitoring unit can apply region-specific monitoring methods, taking into account the customer's geographical location information. This allows for the provision of region-specific monitoring methods by considering the customer's geographical location information.

[0125] The monitoring department can analyze customers' social media activity and provide relevant monitoring information. For example, the monitoring department can analyze customers' social media activity and provide relevant monitoring information. Furthermore, the monitoring department can predict specific needs and desires from customers' social media activity and provide monitoring information based on that. In addition, the monitoring department can provide relevant monitoring information based on customers' social media activity. Thus, by analyzing customers' social media activity, relevant monitoring information can be provided.

[0126] The delivery unit can estimate the customer's emotions and adjust the final check and adjustment methods based on the estimated emotions. For example, if the customer is relaxed, the delivery unit can provide a detailed final check. Alternatively, if the customer is in a hurry, the delivery unit can prioritize a final check that can be provided quickly. Furthermore, if the customer is excited, the delivery unit can provide a visually stimulating final check. This allows for a more appropriate delivery by adjusting the final check and adjustment methods based on the customer's emotions. Emotion estimation is achieved using emotion estimation functions, such as an emotion engine or generative AI. Generative AI includes, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI.

[0127] The handover unit can select the optimal adjustment method by referring to past project data during the final check. For example, the handover unit can select the optimal adjustment method based on past project data. Furthermore, the handover unit can predict and select a specific adjustment method from past project data. In addition, the handover unit can select the optimal adjustment method by referring to past project data. This allows for the selection of the optimal adjustment method by referring to past project data.

[0128] The delivery department can customize the product at the time of delivery based on the customer's lifestyle and design preferences. For example, the delivery department can customize the product at the time of delivery to match the customer's lifestyle. Furthermore, the delivery department can also customize the product at the time of delivery based on the customer's design preferences. This allows for a more satisfying delivery by customizing the product based on the customer's lifestyle and design preferences.

[0129] The delivery unit can estimate the customer's emotions and determine delivery priorities based on those estimated emotions. For example, if the customer is relaxed, the delivery unit might prioritize a detailed delivery. If the customer is in a hurry, it might prioritize a delivery that can be provided quickly. Furthermore, if the customer is excited, it might prioritize a visually stimulating delivery. This allows for more appropriate deliveries by determining delivery priorities based on the customer's emotions. Emotion estimation is achieved using emotion estimation functions, such as emotion engines or generative AI. Generative AI includes, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI.

[0130] The delivery unit can apply region-specific delivery methods, taking into account the customer's geographical location information. For example, the delivery unit can apply region-specific delivery methods based on the customer's geographical location information. Furthermore, the delivery unit can apply delivery methods relevant to specific regions based on the customer's geographical location information. In addition, the delivery unit can apply region-specific delivery methods, taking into account the customer's geographical location information. This allows for the provision of region-specific delivery methods by considering the customer's geographical location information.

[0131] The delivery department can analyze customers' social media activity and provide relevant delivery information. For example, the delivery department can analyze customers' social media activity and provide relevant delivery information. Furthermore, the delivery department can predict specific needs and desires from customers' social media activity and provide delivery information based on that. In addition, the delivery department can provide relevant delivery information based on customers' social media activity. Thus, by analyzing customers' social media activity, relevant delivery information can be provided.

[0132] The care department can estimate the customer's emotions and adjust the aftercare method based on the estimated emotions. For example, if the customer is relaxed, the care department can provide detailed aftercare. Alternatively, if the customer is in a hurry, the care department can prioritize aftercare that can be provided quickly. Furthermore, if the customer is agitated, the care department can provide visually stimulating aftercare. This allows for more appropriate aftercare by adjusting the aftercare method based on the customer's emotions. Emotion estimation is achieved using emotion estimation functions, such as emotion engines or generative AI. Generative AI includes, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI.

[0133] The Care Department can refer to the client's past project history when proposing interior design and furniture arrangements. For example, the Care Department can propose relevant interior designs and furniture arrangements based on the client's past project history. Furthermore, the Care Department can predict specific needs and desires from the client's past project history and propose interior designs and furniture arrangements accordingly. In addition, the Care Department can propose the most suitable interior designs and furniture arrangements by referring to the client's past project history. This allows for more appropriate interior design and furniture arrangement proposals by referencing the client's past project history.

[0134] The care department can customize home maintenance plans based on the customer's lifestyle and design preferences. For example, the care department can customize home maintenance plans to suit the customer's lifestyle. Furthermore, the care department can customize home maintenance plans based on the customer's design preferences. This allows for the provision of more appropriate maintenance plans by customizing them based on the customer's lifestyle and design preferences.

[0135] The care department can estimate the customer's emotions and prioritize aftercare based on those emotions. For example, if the customer is relaxed, the care department might prioritize detailed aftercare. If the customer is in a hurry, the care department might prioritize aftercare that can be provided quickly. Furthermore, if the customer is agitated, the care department might prioritize visually stimulating aftercare. This allows for more appropriate aftercare by prioritizing aftercare based on the customer's emotions. Emotion estimation is achieved using emotion estimation functions, such as emotion engines or generative AI. Generative AI includes, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI.

[0136] The care department can apply region-specific aftercare methods, taking into account the customer's geographical location. For example, the care department can apply region-specific aftercare methods based on the customer's geographical location. Furthermore, the care department can apply aftercare methods relevant to a specific region based on the customer's geographical location. In addition, the care department can apply region-specific aftercare methods, taking into account the customer's geographical location. This allows for the provision of region-specific aftercare methods by considering the customer's geographical location.

[0137] The Care Department can analyze customers' social media activity and provide relevant aftercare information. For example, the Care Department can analyze customers' social media activity and provide relevant aftercare information. Furthermore, the Care Department can predict specific needs and desires from customers' social media activity and provide aftercare information based on that. In short, by analyzing customers' social media activity, the Care Department can provide relevant aftercare information.

[0138] The system according to the embodiment is not limited to the example described above, and various modifications are possible, for example, as follows.

[0139] The reception desk can estimate the customer's emotions and adjust the tone and style of interaction based on those estimates. For example, if a customer is stressed, the reception desk can use a calm tone to help the customer relax. If a customer is excited, the reception desk can use an energetic tone to maintain the customer's excitement. Furthermore, if a customer is anxious, the reception desk can use a reassuring tone to alleviate their anxiety. By adjusting the tone and style of interaction according to the customer's emotions, a better customer experience can be provided.

[0140] The generation unit can estimate the customer's emotions and adjust the order in which design proposals are presented based on those emotions. For example, if the customer is relaxed, the generation unit will first propose detailed design proposals, allowing the customer time to consider them carefully. If the customer is in a hurry, the generation unit will first propose concise design proposals, allowing for a quick selection. Furthermore, if the customer is excited, the generation unit will first propose visually appealing design proposals, helping to maintain the customer's excitement. By adjusting the order in which design proposals are presented according to the customer's emotions, more appropriate proposals can be made.

[0141] The estimation department can estimate the customer's emotions and adjust the level of detail in the estimate based on that estimation. For example, if the customer is relaxed, the estimation department can provide a detailed estimate, allowing the customer to consider it carefully. If the customer is in a hurry, the estimation department can provide a concise estimate, allowing them to make a quick decision. Furthermore, if the customer is excited, the estimation department can provide a visually appealing estimate, maintaining the customer's excitement. By adjusting the level of detail in the estimate according to the customer's emotions, a more appropriate estimate can be provided.

[0142] The management department can estimate customer emotions and adjust material procurement priorities based on those estimates. For example, if a customer is relaxed, the management department will prioritize quality-focused material procurement. If a customer is in a hurry, the management department can prioritize materials that can be procured quickly. Furthermore, if a customer is excited, the management department can prioritize visually appealing materials. By adjusting material procurement priorities according to customer emotions, more appropriate material procurement can be achieved.

[0143] The monitoring department can estimate the customer's emotions and adjust the method of reporting on construction progress based on those estimates. For example, if the customer is relaxed, the monitoring department can provide detailed progress reports to reassure the customer. If the customer is in a hurry, the monitoring department can provide concise progress reports to allow them to quickly grasp the situation. Furthermore, if the customer is excited, the monitoring department can provide visually appealing progress reports to maintain the customer's excitement. In this way, by adjusting the method of reporting on construction progress according to the customer's emotions, more appropriate reports can be provided.

[0144] The reception desk can analyze a customer's past project history and select the most appropriate question format. For example, it can automatically generate relevant questions based on the customer's past project history. The reception desk can also prioritize suggesting question formats (text, voice, etc.) that the customer has used in the past. Furthermore, the reception desk can predict specific needs and preferences from the customer's past project history and adjust the question format accordingly. This allows for the selection of the most suitable question format by analyzing the customer's past project history.

[0145] The generation unit can generate region-specific design proposals by taking into account the customer's geographical location information. For example, it can generate region-specific design proposals based on the customer's geographical location information. Furthermore, the generation unit can generate design proposals related to a specific region from the customer's geographical location information. In addition, the generation unit can generate region-specific design proposals by considering the customer's geographical location information. This allows for the provision of region-specific design proposals by taking the customer's geographical location information into account.

[0146] The estimation department can improve the accuracy of estimates by referring to past project data. For example, it can improve the accuracy of estimates based on past project data. Furthermore, the estimation department can predict specific cost elements from past project data and incorporate them into estimates. In addition, the estimation department can improve the accuracy of estimates by referring to past project data. This means that the accuracy of estimates can be improved by referring to past project data.

[0147] The management department can analyze customers' social media activity and select relevant suppliers. For example, it can analyze customers' social media activity and select relevant suppliers. Furthermore, the management department can predict specific needs and desires from customers' social media activity and select suppliers accordingly. In addition, the management department can select relevant suppliers based on customers' social media activity. Thus, by analyzing customers' social media activity, it is possible to select relevant suppliers.

[0148] The Care Department can customize the content of conversations based on the customer's lifestyle and design preferences. For example, it can automatically generate relevant questions tailored to the customer's lifestyle. The Care Department can also make specific suggestions and ask questions based on the customer's design preferences. Furthermore, the Care Department can adjust the tone and style of the conversation based on the customer's lifestyle and design preferences. This allows for more appropriate information gathering by customizing the conversation based on the customer's lifestyle and design preferences.

[0149] The following briefly describes the processing flow for example form 2.

[0150] Step 1: The reception desk receives customer requests and needs. For example, an interactive AI chatbot is implemented to collect detailed requirements and requests through dialogue with customers. Step 2: The generation unit generates design proposals based on the information received by the reception unit. For example, it automatically generates custom design proposals based on the collected requirements and provides multiple design options. Furthermore, it uses VR and AR technology to allow customers to virtually experience and evaluate the designs. Step 3: The estimation unit estimates the cost of the design proposals generated by the generation unit. For example, it automates real-time cost estimation for each design proposal using a cost calculation algorithm. Step 4: The management department procures materials based on the costs estimated by the estimation department. For example, they select and procure the best suppliers for the necessary materials, furniture, and equipment. Step 5: The monitoring department monitors the construction process based on materials procured by the management department. For example, they track the construction process in real time using a construction progress monitoring system linked with IoT sensors and notify the customer and construction team of any anomalies or delays. Step 6: The handover department performs final checks and adjustments to the construction process, which has been monitored by the supervision department. For example, they perform final checks and adjustments and hand over the building to the customer. Step 7: The Care Department provides after-sales care following the handover by the Handover Department. For example, they offer suggestions for interior design and furniture arrangement, and home maintenance plans.

[0151] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0152] Data generation model 58 is a form of so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> Examples of generative AI include text generation AI, image generation AI, and multimodal generation AI. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats from audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVMs), k-means clustering, convolutional neural networks (CNNs), recurrent neural networks (RNNs), generative adversarial networks (GANs), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each of the above parts is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example.Furthermore, processing performed by AI, including generative AI, may be replaced with rule-based processing, and rule-based processing may be replaced with processing performed by AI, including generative AI.

[0153] Furthermore, the processing performed by the data processing system 10 described above is carried out by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart device 14, but it may also be carried out by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart device 14. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart device 14 or an external device, and the smart device 14 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0154] Each of the multiple elements described above, including the reception unit, generation unit, estimation unit, management unit, monitoring unit, handover unit, and care unit, is implemented by, for example, at least one of the smart device 14 and the data processing unit 12. For example, the reception unit is implemented by the control unit 46A of the smart device 14 and receives customer requests and needs through an interactive AI chatbot. The generation unit is implemented by, for example, the identification processing unit 290 of the data processing unit 12 and automatically generates custom design proposals based on collected requirements. The estimation unit is implemented by, for example, the identification processing unit 290 of the data processing unit 12 and performs real-time cost estimation using a cost calculation algorithm. The management unit is implemented by, for example, the control unit 46A of the smart device 14 and selects and procures the optimal suppliers of necessary materials, furniture, and equipment. The monitoring unit is implemented by, for example, the control unit 46A of the smart device 14 and tracks the construction process in real time with a construction progress monitoring system linked with IoT sensors. The handover section is implemented, for example, by the control unit 46A of the smart device 14, which performs final checks and adjustments before handing over the device to the customer. The care section is implemented, for example, by the control unit 46A of the smart device 14, which provides interior design and furniture placement suggestions, home maintenance plans, etc. The correspondence between each section and the devices and control units is not limited to the examples described above, and various modifications are possible.

[0155] [Second Embodiment] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0156] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0157] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN and / or LAN.

[0158] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0159] The microphone 238 receives voice commands and other instructions from the user by receiving voice signals. The microphone 238 captures the voice signals from the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0160] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, which captures images of the area around the user (for example, an imaging range defined by a field of view equivalent to the field of vision of a typical healthy person).

[0161] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0162] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing by the processor 28. The storage 32 stores the specific processing program 56.

[0163] The processor 28 reads a specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 acting as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0164] Storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0165] In the smart glasses 214, specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 acting as a control unit 46A according to the specific processing program 60 executed on the RAM 48. The smart glasses 214 also have a data generation model 58 and an emotion identification model 59, similar to the data generation model and emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0166] Furthermore, other devices besides the data processing device 12 may also have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 obtains processing results (such as prediction results) using the data generation model 58 by communicating with the server device that has the data generation model 58. Also, the data processing device 12 may be a server device or a terminal device owned by the user (for example, a mobile phone, robot, home appliance, etc.).

[0167] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0168] The data generation model 58 is a so-called generative AI. An example of a data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats such as audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVM), k-means clustering, convolutional neural networks (CNN), recurrent neural networks (RNN), generative adversarial networks (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each part described above is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example. Also, processing performed by an AI including a generative AI may be replaced by rule-based processing, and rule-based processing may be replaced by processing performed by an AI including a generative AI.

[0169] The data processing system 210 according to the second embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 210 is performed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart glasses 214, but it may also be performed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart glasses 214. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart glasses 214 or an external device, and the smart glasses 214 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0170] Each of the multiple elements described above, including the reception unit, generation unit, estimation unit, management unit, monitoring unit, handover unit, and care unit, is implemented by, for example, at least one of the smart glasses 214 and the data processing unit 12. For example, the reception unit is implemented by the control unit 46A of the smart glasses 214, which receives customer requests and needs through an interactive AI chatbot. The generation unit is implemented by, for example, the identification processing unit 290 of the data processing unit 12, which automatically generates custom design proposals based on collected requirements. The estimation unit is implemented by, for example, the identification processing unit 290 of the data processing unit 12, which performs real-time cost estimation using a cost calculation algorithm. The management unit is implemented by, for example, the control unit 46A of the smart glasses 214, which selects and procures the best suppliers of necessary materials, furniture, and equipment. The monitoring unit is implemented by, for example, the control unit 46A of the smart glasses 214, which tracks the construction process in real time with a construction progress monitoring system linked with IoT sensors. The handover section is implemented, for example, by the control unit 46A of the smart glasses 214, which performs final checks and adjustments before handing the product over to the customer. The care section is implemented, for example, by the control unit 46A of the smart glasses 214, which provides suggestions for interior design and furniture placement, and home maintenance plans. The correspondence between each section and the device or control unit is not limited to the examples described above, and various modifications are possible.

[0171] [Third Embodiment] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0172] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0173] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN and / or LAN.

[0174] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0175] The microphone 238 receives voice commands and other instructions from the user by receiving voice signals. The microphone 238 captures the voice signals from the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0176] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, which captures images of the area around the user (for example, an imaging range defined by a field of view equivalent to the field of vision of a typical healthy person).

[0177] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0178] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0179] The processor 28 reads a specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 acting as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0180] Storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0181] In the headset terminal 314, specific processing is performed by the processor 46. The storage 50 stores a specific program 60. The processor 46 reads the specific program 60 from the storage 50 and executes the read specific program 60 on the RAM 48. The specific processing is realized by the processor 46 acting as a control unit 46A according to the specific program 60 executed on the RAM 48. The headset terminal 314 also has a data generation model 58 and an emotion identification model 59, similar to the data generation model and emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0182] Furthermore, other devices besides the data processing device 12 may also have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 obtains processing results (such as prediction results) using the data generation model 58 by communicating with the server device that has the data generation model 58. Also, the data processing device 12 may be a server device or a terminal device owned by the user (for example, a mobile phone, robot, home appliance, etc.).

[0183] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0184] The data generation model 58 is a so-called generative AI. An example of a data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats such as audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVM), k-means clustering, convolutional neural networks (CNN), recurrent neural networks (RNN), generative adversarial networks (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each part described above is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example. Also, processing performed by an AI including a generative AI may be replaced by rule-based processing, and rule-based processing may be replaced by processing performed by an AI including a generative AI.

[0185] The data processing system 310 according to the third embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 310 is performed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the headset terminal 314, but may also be performed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the headset terminal 314. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the headset terminal 314 or an external device, and the headset terminal 314 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0186] Each of the multiple elements described above, including the reception unit, generation unit, estimation unit, management unit, monitoring unit, handover unit, and care unit, is implemented by, for example, at least one of the headset terminal 314 and the data processing unit 12. For example, the reception unit is implemented by the control unit 46A of the headset terminal 314 and receives customer requests and needs through an interactive AI chatbot. The generation unit is implemented by, for example, the identification processing unit 290 of the data processing unit 12 and automatically generates custom design proposals based on collected requirements. The estimation unit is implemented by, for example, the identification processing unit 290 of the data processing unit 12 and performs real-time cost estimation using a cost calculation algorithm. The management unit is implemented by, for example, the control unit 46A of the headset terminal 314 and selects and procures the optimal suppliers of necessary materials, furniture, and equipment. The monitoring unit is implemented by, for example, the control unit 46A of the headset terminal 314 and tracks the construction process in real time with a construction progress monitoring system linked with IoT sensors. The handover section is implemented, for example, by the control unit 46A of the headset terminal 314, which performs final checks and adjustments before handing over the device to the customer. The care section is implemented, for example, by the control unit 46A of the headset terminal 314, which provides interior design and furniture placement suggestions, home maintenance plans, etc. The correspondence between each section and the device or control unit is not limited to the examples described above, and various modifications are possible.

[0187] [Fourth Embodiment] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0188] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0189] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN and / or LAN.

[0190] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0191] The microphone 238 receives voice commands and other instructions from the user by receiving voice signals. The microphone 238 captures the voice signals from the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0192] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS image sensor or CCD image sensor, which captures images of the area around the user (for example, an imaging range defined by a field of view equivalent to the field of vision of a typical healthy person).

[0193] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0194] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. The robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0195] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0196] The processor 28 reads a specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 acting as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0197] Storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0198] In robot 414, specific processing is performed by processor 46. A specific program 60 is stored in storage 50. Processor 46 reads the specific program 60 from storage 50 and executes it on RAM 48. The specific processing is achieved by processor 46 acting as a control unit 46A according to the specific program 60 executed on RAM 48. Robot 414 also has data generation model 58 and emotion identification model 59, similar to those of the robot, and can perform processing similar to that of the specific processing unit 290 using these models.

[0199] Furthermore, other devices besides the data processing device 12 may also have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 obtains processing results (such as prediction results) using the data generation model 58 by communicating with the server device that has the data generation model 58. Also, the data processing device 12 may be a server device or a terminal device owned by the user (for example, a mobile phone, robot, home appliance, etc.).

[0200] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0201] The data generation model 58 is a so-called generative AI. An example of a data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats such as audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVM), k-means clustering, convolutional neural networks (CNN), recurrent neural networks (RNN), generative adversarial networks (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each part described above is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example. Also, processing performed by an AI including a generative AI may be replaced by rule-based processing, and rule-based processing may be replaced by processing performed by an AI including a generative AI.

[0202] The data processing system 410 according to the fourth embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 410 is performed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the robot 414, but it may also be performed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the robot 414. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the robot 414 or an external device, and the robot 414 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0203] Each of the multiple elements described above, including the reception, generation, estimation, management, monitoring, handover, and care departments, is implemented by, for example, at least one of the robot 414 and the data processing device 12. For example, the reception department is implemented by the control unit 46A of the robot 414, which receives customer requests and needs through an interactive AI chatbot. The generation department is implemented by, for example, the identification processing unit 290 of the data processing device 12, which automatically generates custom design proposals based on collected requirements. The estimation department is implemented by, for example, the identification processing unit 290 of the data processing device 12, which performs real-time cost estimation using a cost calculation algorithm. The management department is implemented by, for example, the control unit 46A of the robot 414, which selects and procures the best suppliers of necessary materials, furniture, and equipment. The monitoring department is implemented by, for example, the control unit 46A of the robot 414, which tracks the construction process in real time with a construction progress monitoring system linked with IoT sensors. The handover section is implemented, for example, by the control unit 46A of the robot 414, which performs final checks and adjustments before handing over the device to the customer. The care section is implemented, for example, by the control unit 46A of the robot 414, which provides interior design and furniture placement suggestions, home maintenance plans, etc. The correspondence between each section and the device or control unit is not limited to the examples described above and can be modified in various ways.

[0204] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0205] Figure 9 shows the emotion map 400, in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0206] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0207] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0208] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, and motorcycles, emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated based, for example, on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0209] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0210] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0211] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing method for the specific process may be used, which includes computer 22 and multiple other computers.

[0212] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0213] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[0214] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0215] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0216] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0217] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0218] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0219] Furthermore, although the above-described examples were divided into four embodiments, some or all of these embodiments may be combined. Also, the smart device 14, smart glasses 214, headset terminal 314, and robot 414 are just examples, and they may be combined, or other devices may be used. Also, although the above-described examples were divided into two embodiments, Embodiment 1 and Embodiment 2, these may be combined.

[0220] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and other things that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0221] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0222] (Note 1) A reception desk that handles customer requests and needs, A generation unit that generates a design proposal based on the information received by the reception unit, An estimation unit that estimates the cost of the design proposal generated by the generation unit, A management department procures materials based on the costs estimated by the aforementioned estimation department, A monitoring unit monitors the construction process based on materials procured by the aforementioned management unit, The handover department performs the final check and adjustment of the construction process monitored by the aforementioned monitoring department, The system includes a care unit that provides aftercare following delivery by the aforementioned delivery unit. A system characterized by the following features. (Note 2) The aforementioned reception unit is We will implement an interactive AI chatbot to gather detailed requirements and preferences from customers through dialogue. The system described in Appendix 1, characterized by the features described herein. (Note 3) The generating unit is Automatically generate custom design proposals based on collected requirements. The system described in Appendix 1, characterized by the features described herein. (Note 4) The generating unit is We provide multiple design options and use VR and AR technology to allow customers to virtually experience and evaluate the designs. The system described in Appendix 1, characterized by the features described herein. (Note 5) The aforementioned estimation department, Automate real-time cost estimation for each design proposal using cost calculation algorithms. The system described in Appendix 1, characterized by the features described herein. (Note 6) The aforementioned management department, Select and procure the best suppliers for the necessary materials, furniture, and equipment. The system described in Appendix 1, characterized by the features described herein. (Note 7) The aforementioned monitoring unit, A construction progress monitoring system linked with IoT sensors tracks the construction process in real time. The system described in Appendix 1, characterized by the features described herein. (Note 8) The aforementioned care unit is We offer interior design and furniture placement suggestions, as well as home maintenance plans. The system described in Appendix 1, characterized by the features described herein. (Note 9) The aforementioned reception unit is We estimate customer emotions and adjust how we collect their wishes and needs based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 10) The aforementioned reception unit is Analyze the customer's past project history and select the most suitable question format. The system described in Appendix 1, characterized by the features described herein. (Note 11) The aforementioned reception unit is Customize the conversation based on the customer's lifestyle and design preferences. The system described in Appendix 1, characterized by the features described herein. (Note 12) The aforementioned reception unit is We estimate customer emotions and prioritize the information to collect based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 13) The aforementioned reception unit is We collect region-specific requirements and preferences, taking into account the customer's geographical location. The system described in Appendix 1, characterized by the features described herein. (Note 14) The aforementioned reception unit is Analyze customers' social media activity and gather relevant requirements and preferences. The system described in Appendix 1, characterized by the features described herein. (Note 15) The generating unit is We estimate the customer's emotions and adjust the way the design proposal is presented based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 16) The generating unit is Based on the collected requirements, adjust the level of detail in the design proposal. The system described in Appendix 1, characterized by the features described herein. (Note 17) The generating unit is We generate the optimal design proposal by referring to the customer's past project history. The system described in Appendix 1, characterized by the features described herein. (Note 18) The generating unit is We estimate customer emotions and prioritize design proposals based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 19) The generating unit is We generate region-specific design proposals, taking into account the customer's geographical location. The system described in Appendix 1, characterized by the features described herein. (Note 20) The generating unit is Analyze customer social media activity and generate relevant design proposals. The system described in Appendix 1, characterized by the features described herein. (Note 21) The aforementioned estimation department, We estimate customer emotions and adjust the way estimates are presented based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 22) The aforementioned estimation department, When estimating the cost of each design proposal, we optimize it based on the customer's budget. The system described in Appendix 1, characterized by the features described herein. (Note 23) The aforementioned estimation department, Referencing past project data improves the accuracy of estimates. The system described in Appendix 1, characterized by the features described herein. (Note 24) The aforementioned estimation department, Estimate customer sentiment and prioritize quotes based on the estimated customer sentiment. The system described in Appendix 1, characterized by the features described herein. (Note 25) The aforementioned estimation department, We take into account the customer's geographical location to provide region-specific cost estimates. The system described in Appendix 1, characterized by the features described herein. (Note 26) The aforementioned estimation department, Analyze customer social media activity and estimate related costs. The system described in Appendix 1, characterized by the features described herein. (Note 27) The aforementioned management department, We estimate customer emotions and adjust material procurement methods based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 28) The aforementioned management department, When selecting the optimal suppliers for necessary materials, furniture, and equipment, we refer to past procurement data. The system described in Appendix 1, characterized by the features described herein. (Note 29) The aforementioned management department, During procurement, we select the optimal procurement method based on the customer's budget. The system described in Appendix 1, characterized by the features described herein. (Note 30) The aforementioned management department, Estimate customer sentiment and prioritize procurement based on that estimated sentiment. The system described in Appendix 1, characterized by the features described herein. (Note 31) The aforementioned management department, We select region-specific suppliers, taking into account the customer's geographical location. The system described in Appendix 1, characterized by the features described herein. (Note 32) The aforementioned management department, Analyze customer social media activity and select relevant suppliers. The system described in Appendix 1, characterized by the features described herein. (Note 33) The aforementioned monitoring unit, Estimate customer emotions and adjust how the construction process is monitored based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 34) The aforementioned monitoring unit, It works in conjunction with IoT sensors to track construction progress in real time. The system described in Appendix 1, characterized by the features described herein. (Note 35) The aforementioned monitoring unit, In the event of any abnormalities or delays, promptly notify the customer and the construction team. The system described in Appendix 1, characterized by the features described herein. (Note 36) The aforementioned monitoring unit, Estimate customer sentiment and prioritize monitoring based on the estimated customer sentiment. The system described in Appendix 1, characterized by the features described herein. (Note 37) The aforementioned monitoring unit, We apply region-specific monitoring methods, taking into account the customer's geographical location. The system described in Appendix 1, characterized by the features described herein. (Note 38) The aforementioned monitoring unit, We analyze customers' social media activity and provide relevant monitoring information. The system described in Appendix 1, characterized by the features described herein. (Note 39) The aforementioned handover section is, We estimate customer emotions and adjust the final check and adjustment process based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 40) The aforementioned handover section is, At the final check, select the optimal adjustment method by referring to past project data The system according to Appendix 1, characterized in that it is as described above. (Appendix 41) The delivery department At the time of delivery, customize based on the customer's lifestyle and design preferences The system according to Appendix 1, characterized in that it is as described above. (Appendix 42) The delivery department Estimate the customer's emotions and determine the priority order of delivery based on the estimated customer emotions The system according to Appendix 1, characterized in that it is as described above. (Appendix 43) The delivery department Considering the customer's geographical location information, apply a region-specific delivery method The system according to Appendix 1, characterized in that it is as described above. (Appendix 44) The delivery department Analyze the customer's social media activities and provide relevant delivery information The system according to Appendix 1, characterized in that it is as described above. (Appendix 45) The care department Estimate the customer's emotions and adjust the aftercare method based on the estimated customer emotions The system according to Appendix 1, characterized in that it is as described above. (Appendix 46)<L The care department When proposing interior design and furniture arrangement, refer to the customer's past project history The system according to Appendix 1, characterized in that it is as described above. (Appendix 47) The care department When providing a home maintenance plan, customize based on the customer's lifestyle and design preferences [[ID=5】8]]The system according to Appendix 1, characterized in that it is as described above. (Appendix 48) The care department Estimate customer emotions and prioritize after-sales service based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 49) The aforementioned care unit is We will apply region-specific after-sales service methods, taking into account the customer's geographical location. The system described in Appendix 1, characterized by the features described herein. (Note 50) The aforementioned care unit is We analyze customers' social media activity and provide relevant after-sales service information. The system described in Appendix 1, characterized by the features described herein. [Explanation of Symbols]

[0223] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots

Claims

1. A reception desk that handles customer requests and needs, A generation unit that generates a design proposal based on the information received by the reception unit, An estimation unit that estimates the cost of the design proposal generated by the generation unit, A management department procures materials based on the costs estimated by the aforementioned estimation department, A monitoring unit monitors the construction process based on materials procured by the aforementioned management unit, The handover department performs the final check and adjustment of the construction process monitored by the aforementioned monitoring department, The system includes a care unit that provides aftercare following delivery by the aforementioned delivery unit. A system characterized by the following features.

2. The aforementioned reception unit is We will implement an interactive AI chatbot to collect detailed requirements and preferences from customers through dialogue. The system according to feature 1.

3. The generating unit is Automatically generate custom design proposals based on collected requirements. The system according to feature 1.

4. The generating unit is We provide multiple design options and use VR and AR technology to allow customers to virtually experience and evaluate the designs. The system according to feature 1.

5. The aforementioned estimation department, Automate real-time cost estimation for each design proposal using cost calculation algorithms. The system according to feature 1.

6. The aforementioned management department, Select and procure the best suppliers for the necessary materials, furniture, and equipment. The system according to feature 1.

7. The aforementioned monitoring unit, A construction progress monitoring system linked with IoT sensors tracks the construction process in real time. The system according to feature 1.

8. The aforementioned care unit is We offer interior design and furniture placement suggestions, as well as home maintenance plans. The system according to feature 1.

9. The aforementioned reception unit is We estimate customer emotions and adjust how we collect their wishes and needs based on those estimated emotions. The system according to feature 1.

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