system

Abstract

The system of the embodiment aims to centrally manage information on vacant houses, abandoned houses, and land with unknown owners across the country, and to efficiently buy and sell them. [Solution] The system according to the embodiment comprises a collection unit, a registration unit, a sales management unit, a fee management unit, and a use restriction management unit. The collection unit collects information on vacant or abandoned houses and land with unknown owners from all over the country. The registration unit registers the information collected by the collection unit in a database and manages it all together. The sales management unit manages sales for commercial or residential use based on the information registered by the registration unit. The fee management unit allows local governments or businesses to receive a fee when a sale is concluded by the sales management unit. The use restriction management unit manages use restrictions on land sold by the sales management unit.

Description

[Technical Field]

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

[0002] Patent document 1 discloses a persona chatbot control method performed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to a description of the chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] Conventional technology has faced the challenge of centrally managing information on vacant houses, abandoned houses, and land with unknown owners across the country, and efficiently buying and selling them.

[0005] The system of the embodiment aims to centrally manage information on vacant houses, abandoned houses, and land with unknown owners across the country, and to efficiently buy and sell them. [Means for solving the problem]

[0006] The system according to the embodiment comprises a collection unit, a registration unit, a sales management unit, a fee management unit, and a use restriction management unit. The collection unit collects information on vacant or abandoned houses and land with unknown owners nationwide. The registration unit registers the information collected by the collection unit in a database and manages it all at once. The sales management unit manages sales for commercial or residential use based on the information registered by the registration unit. The fee management unit allows local governments or businesses to receive a fee when a sale is concluded by the sales management unit. The use restriction management unit manages use restrictions on land sold by the sales management unit. [Effects of the Invention]

[0007] The system according to the embodiment centrally manages information on vacant houses, abandoned houses, and land with unknown owners across the country, enabling efficient buying and selling. [Brief explanation of the drawings]

[0008] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9]1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. DETAILED DESCRIPTION OF THE INVENTION

[0009] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0010] First, the terms used in the following description will be explained.

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

[0012] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

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

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

[0015] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

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

[0017] 1, a 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, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also 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 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0020] The reception device 38 includes a touch panel 38A and a microphone 38B, and receives user input. The touch panel 38A detects contact with a pointer (for example, a pen or a finger) to receive user input by the touch of the pointer. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 (see FIG. 2) acquires the data indicating the user input.

[0021] Output device 40 includes a display 40A and a speaker 40B, and presents data to a user by outputting the data in a form of expression that the user can perceive (e.g., audio and / or text). Display 40A displays visible information such as text and images in accordance with instructions from processor 46. Speaker 40B outputs audio in accordance with instructions from processor 46. Camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0022] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

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

[0024] 2, in the data processing device 12, a specific process 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" according to the technology of the present 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 process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0025] The storage 32 stores a data generation model 58 and an 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 a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0026] In the smart device 14, the specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. The specific processing program 60 is used together 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 the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the smart device 14 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

[0027] Note that a device other than the data processing device 12 may 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 a processing result (prediction result, etc.) using the data generation model 58 by communicating with the server device having the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device owned by a user (e.g., a mobile phone, a robot, a home appliance, etc.). Next, an example of processing by the data processing system 10 according to the first embodiment will be described.

[0028] (Example 1) A land management system according to an embodiment of the present invention compiles a nationwide list of vacant houses, abandoned houses, and land with unknown owners and manages it as a database. This land management system manages vacant houses and vacant land nationwide without requiring any procedures from local governments. The listed data is bought and sold for commercial or residential use, and the local government managing the land and businesses participating in the transaction receive a commission. Contractors can freely use the purchased land, but resale to overseas markets and resale itself is prohibited. For example, information on vacant houses, abandoned houses, and land with unknown owners nationwide is collected. This information is based on data provided by local governments and real estate agents. For example, detailed information on vacant houses, such as their location, area, and current condition, is collected. The collected information is then registered in a database and managed in a centralized manner. This database centrally manages information on vacant houses and vacant land nationwide, without requiring any procedures from local governments. For example, information on vacant houses, such as their location, area, and current condition, is registered in the database. The registered information is bought and sold for commercial or residential use. For example, vacant land available for commercial use and vacant houses available for residential use are listed and provided to potential buyers. Potential buyers select land based on the listed information and complete the purchase process. The local government managing the land and the businesses participating in the transaction receive a commission. For example, when a land transaction is completed, the local government or business receives a commission. This increases the profits of the local government and business. Contractors can freely use the purchased land. For example, they can use the purchased land for residential or commercial purposes. However, resale to overseas markets and resale itself are prohibited. This promotes appropriate land use. This system centrally manages vacant houses, abandoned houses, and land with unknown owners nationwide, enabling efficient sales and purchases. It also increases the profits of local governments and businesses and promotes appropriate land use. This allows the land management system to centrally manage vacant houses, abandoned houses, and land with unknown owners nationwide, enabling efficient sales and appropriate use.

[0029] A land management system according to an embodiment includes a collection unit, a registration unit, a sales management unit, a fee management unit, and a use restriction management unit. The collection unit collects information on vacant or abandoned houses and land with unknown owners nationwide. The collection unit collects information based on data provided by, for example, local governments and real estate agents. For example, the collection unit can collect detailed information on vacant houses, such as their location, area, and current status. The collection unit can also collect information via the Internet or through field surveys. For example, information can be collected from public databases on the Internet or real estate agent websites. Field surveys can involve visiting the site and collecting information directly. The registration unit registers the information collected by the collection unit in a database and manages it in a centralized manner. For example, the registration unit registers the collected data in a database and centrally manages information on vacant houses and vacant land nationwide. The database structure includes information on the location, area, and current status of vacant houses. The registration unit can implement security measures, such as data encryption and access control, to ensure the security of the database. The sales management unit manages sales and purchases for commercial or residential use based on the information registered by the registration unit. The sales management unit, for example, lists vacant land available for commercial use or vacant houses available for residential use and provides the listing to potential buyers. Potential buyers can select land based on the listed information and complete the purchase procedure. The sales management unit can also conduct sales and purchases taking into account the attribute information of the potential buyer. For example, the optimal sales and purchase method is selected based on the attribute information of the potential buyer, such as the age, occupation, and interests of the potential buyer. The fee management unit manages a system by which a local government or business receives a fee when a sale is concluded by the sales management unit. The fee management unit manages a system by which a local government or business receives a fee when a land sale is concluded, for example. The fee calculation method and criteria include, for example, the fee rate and the timing of calculation. The fee management unit can also select the optimal fee calculation method by referring to past fee data. The use restriction management unit manages use restrictions on land sold and purchased by the sales management unit. For example, the use restriction management unit manages use restrictions on the contract holder and prevents resale overseas or resale altogether. The specific content and criteria of the use restrictions include, for example, the available uses and the scope of restrictions.The usage restriction management unit can also impose usage restrictions taking into account the contractor's attribute information. For example, the optimal usage restriction method is selected based on the contractor's attribute information, such as age, occupation, and interests. As a result, the land management system according to the embodiment can collectively manage vacant houses, abandoned houses, and land with unknown owners across the country, enabling efficient buying and selling and appropriate use.

[0030] The collection unit can receive data provided by local governments and real estate agents. For example, the collection unit collects information based on data provided by local governments and real estate agents. For example, it can collect detailed information such as the location, area, and current status of vacant houses. The collection unit can also collect information via the Internet or field surveys. For example, it collects information from public databases on the Internet and real estate agent websites. In field surveys, it is possible to go to the site and collect information directly. In this way, by receiving data provided by local governments and real estate agents, the reliability of the collected data is improved.

[0031] The registration unit can register the collected data in a database and manage it all at once. The registration unit, for example, registers the collected data in a database and centrally manages information on vacant houses and vacant lots across the country. The database structure includes, for example, information such as the location, area, and current status of vacant houses. The registration unit can implement security measures such as data encryption and access control to ensure the security of the database. As a result, by registering the data in a database and managing it all at once, data management becomes more efficient.

[0032] The sales management unit can create a list of vacant land that can be used for commercial purposes or vacant houses that can be used for residential purposes, and provide it to potential buyers. The sales management unit can, for example, create a list of vacant land that can be used for commercial purposes or vacant houses that can be used for residential purposes, and provide it to potential buyers. Potential buyers can select land and carry out the purchase procedure based on the listed information. The sales management unit can also conduct sales taking into account the attribute information of the potential buyer. For example, the optimal sales method can be selected based on attribute information such as the age, occupation, and interests of the potential buyer. This makes it easier for potential buyers to select appropriate land based on the listed information.

[0033] The fee management unit can manage a system whereby local governments and businesses receive fees when a land sale is concluded. The fee management unit manages a system whereby local governments and businesses receive fees when a land sale is concluded, for example. Fee calculation methods and standards include, for example, the fee rate and the timing of calculation. The fee management unit can also select the optimal fee calculation method by referring to past fee data. This makes fee management more efficient and improves the profits of local governments and businesses.

[0034] The usage restriction management unit manages the usage restrictions of the contract holder and can prevent resale overseas or resale altogether. The usage restriction management unit, for example, manages the usage restrictions of the contract holder and prevents resale overseas or resale altogether. The specific content and standards of the usage restrictions include, for example, the available uses and the scope of restrictions. The usage restriction management unit can also impose usage restrictions taking into account the contract holder's attribute information. For example, the optimal usage restriction method is selected based on the contract holder's attribute information such as age, occupation, and interests. This promotes appropriate use of land.

[0035] The collection unit may include an update confirmation unit that updates and checks data. The collection unit may include, for example, an update confirmation unit that updates and checks data. The update confirmation unit, for example, checks the currency of the collected data and updates the data as necessary. The update frequency and confirmation method may be, for example, periodic checks or an automated system. This makes data updating and checking more efficient, and the latest information is always maintained.

[0036] The registration unit may include a security management unit that ensures the security of the database. The registration unit may include, for example, a security management unit that ensures the security of the database. The security management unit implements security measures such as data encryption and access control. This ensures the security of the database and strengthens the protection of data.

[0037] The collection unit can analyze past data collection history and select the optimal collection method. The collection unit, for example, analyzes past data collection history and selects the optimal collection method. For example, the collection unit identifies and applies the most efficient collection method from the past data collection history. The collection unit can also analyze past data collection history and optimize the timing and frequency of collection. Furthermore, the collection target priority can be determined based on the past data collection history. As a result, the collection efficiency is improved by selecting the optimal collection method based on the past data collection history.

[0038] The collection unit can perform filtering based on the characteristics and demand of the region when collecting data. For example, the collection unit performs filtering based on the characteristics and demand of the region when collecting data. For example, the collection unit selects the type of data to collect based on the characteristics of the region. It can also determine the priority of the data to be collected according to the demand of the region. Furthermore, it can adjust the range of data to be collected taking into account the characteristics and demand of the region. This makes it possible to collect data according to the characteristics and demand of the region.

[0039] The collection unit can prioritize collecting highly relevant data by taking geographical location information into consideration when collecting data. For example, the collection unit prioritizes collecting highly relevant data by taking geographical location information into consideration when collecting data. For example, the collection unit prioritizes collecting highly relevant data based on the geographical location information. The range of data to be collected can also be adjusted by taking geographical location information into consideration. Furthermore, the priority of data to be collected can also be determined based on the geographical location information. As a result, by preferentially collecting highly relevant data based on the geographical location information, collection efficiency is improved.

[0040] The collection unit can analyze social media activity and collect related data when collecting data. For example, the collection unit analyzes social media activity and collects related data when collecting data. For example, the collection unit analyzes social media activity and collects related data. The collection unit can also determine the priority of data to be collected based on social media trends. Furthermore, the range of data to be collected can be adjusted taking into account the amount of social media activity. This improves the accuracy of collection by collecting related data based on social media activity.

[0041] The registration unit can adjust the level of detail of the registration based on the importance of the data when registering the data. For example, the registration unit adjusts the level of detail of the registration based on the importance of the data when registering the data. For example, data with high importance is registered in detail, and data with low importance is registered in a simplified manner. The level of detail of the registration can also be adjusted according to the importance of the data. Furthermore, data with high importance can be registered in detail with priority. This makes it possible to register data in detail according to the importance of the data.

[0042] The registration unit can apply different registration algorithms depending on the category of data when registering data. For example, the registration unit applies different registration algorithms depending on the category of data when registering data. For example, different registration algorithms are applied to commercial data and residential data. The registration unit can also select the optimal registration algorithm depending on the category of data. Furthermore, different registration algorithms can be applied for each category of data. This makes it possible to perform optimal registration depending on the category of data.

[0043] The registration unit can determine the priority of registration based on the time of data collection when registering data. For example, the registration unit determines the priority of registration based on the time of data collection when registering data. For example, the most recent data is registered preferentially. The priority of registration can also be determined based on the time of data collection. Furthermore, older data can be postponed and the most recent data can be registered preferentially. This makes it possible to prioritize registration based on the time of data collection.

[0044] The registration unit can adjust the order of registration based on the relevance of the data when registering the data. For example, the registration unit adjusts the order of registration based on the relevance of the data when registering the data. For example, highly relevant data is registered preferentially. The registration order can also be adjusted based on the relevance of the data. Furthermore, data with low relevance can be postponed and highly relevant data can be registered preferentially. This enables efficient registration based on the relevance of the data.

[0045] The trading management unit can improve the accuracy of trading by taking into account the interrelationships of data during trading management. The trading management unit, for example, improves the accuracy of trading by taking into account the interrelationships of data during trading management. For example, the trading management unit analyzes the interrelationships of data and selects the optimal trading method. The accuracy of trading can also be improved by taking into account the interrelationships of data. Furthermore, the priority of trading can also be determined based on the interrelationships of data. In this way, the accuracy of trading is improved by taking into account the interrelationships of data.

[0046] The buying and selling management unit can conduct buying and selling taking into consideration the attribute information of the prospective purchaser when managing buying and selling. The buying and selling management unit, for example, conducts buying and selling taking into consideration the attribute information of the prospective purchaser when managing buying and selling. For example, the optimal buying and selling method is selected based on the attribute information of the prospective purchaser. The accuracy of buying and selling can also be improved by taking into consideration the attribute information of the prospective purchaser. Furthermore, the priority of buying and selling can also be determined based on the attribute information of the prospective purchaser. In this way, the accuracy of buying and selling can be improved by taking into consideration the attribute information of the prospective purchaser.

[0047] The trading management unit can take geographical distribution into consideration when managing trading. The trading management unit, for example, takes geographical distribution into consideration when managing trading. For example, the trading management unit selects the optimal trading method based on the geographical distribution. The accuracy of trading can also be improved by taking geographical distribution into consideration. Furthermore, the priority of trading can also be determined based on the geographical distribution. In this way, the accuracy of trading can be improved by taking geographical distribution into consideration.

[0048] The trading management unit can improve the accuracy of trading by referring to related literature during trading management. The trading management unit, for example, improves the accuracy of trading by referring to related literature during trading management. For example, the optimal trading method is selected based on the related literature. The accuracy of trading can also be improved by referring to related literature. Furthermore, trading priorities can also be determined based on the related literature. In this way, the accuracy of trading is improved by referring to related literature.

[0049] The fee management unit can select the optimal fee calculation method by referring to past fee data when managing fees. The fee management unit, for example, selects the optimal fee calculation method by referring to past fee data when managing fees. For example, the optimal fee calculation method is selected based on past fee data. The accuracy of fee calculation can also be improved by referring to past fee data. Furthermore, the priority of fee calculation can also be determined based on past fee data. In this way, calculation accuracy is improved by selecting the optimal fee calculation method based on past fee data.

[0050] The fee management unit can adjust the level of detail of fees according to the scale of trading when managing fees. The fee management unit, for example, adjusts the level of detail of fees according to the scale of trading when managing fees. For example, if the scale of trading is large, a detailed fee calculation method is provided. The level of detail of fees can also be adjusted according to the scale of trading. Furthermore, if the scale of trading is small, a simplified fee calculation method can also be provided. This makes it possible to adjust the level of detail of fee calculation according to the scale of trading.

[0051] The fee management unit can calculate fees taking into account geographical location information when managing fees. For example, the fee management unit calculates fees taking into account geographical location information when managing fees. For example, the fee management unit calculates fees for each region based on the geographical location information. The fee calculation method can also be adjusted taking into account the geographical location information. Furthermore, the priority of fees can also be determined based on the geographical location information. As a result, calculating fees based on geographical location information improves calculation accuracy.

[0052] The fee management unit can improve the accuracy of fees by referring to related literature when managing fees. The fee management unit, for example, improves the accuracy of fees by referring to related literature when managing fees. For example, the optimal fee calculation method is selected based on the related literature. The accuracy of fee calculation can also be improved by referring to related literature. Furthermore, the priority of fee calculation can also be determined based on the related literature. In this way, the accuracy of fee calculation is improved by referring to related literature.

[0053] The usage restriction management unit can select the optimal usage restriction method by referring to past usage restriction data when managing usage restrictions. The usage restriction management unit, for example, selects the optimal usage restriction method by referring to past usage restriction data when managing usage restrictions. For example, the optimal usage restriction method is selected based on past usage restriction data. The accuracy of usage restrictions can also be improved by referring to past usage restriction data. Furthermore, the priority of usage restrictions can also be determined based on past usage restriction data. In this way, the accuracy of restrictions is improved by selecting the optimal usage restriction method based on past usage restriction data.

[0054] The usage restriction management unit can impose usage restrictions by taking into account the attribute information of the subscriber when managing usage restrictions. The usage restriction management unit, for example, imposes usage restrictions by taking into account the attribute information of the subscriber when managing usage restrictions. For example, the unit selects the optimal usage restriction method based on the attribute information of the subscriber. The accuracy of usage restrictions can also be improved by taking into account the attribute information of the subscriber. Furthermore, the priority of usage restrictions can also be determined based on the attribute information of the subscriber. In this way, the accuracy of usage restrictions can be improved by taking into account the attribute information of the subscriber.

[0055] The usage restriction management unit can impose usage restrictions taking into account geographical location information when managing usage restrictions. The usage restriction management unit, for example, imposes usage restrictions taking into account geographical location information when managing usage restrictions. For example, the usage restriction management unit applies usage restrictions for each region based on the geographical location information. The usage restriction method can also be adjusted taking into account the geographical location information. Furthermore, the priority of usage restrictions can also be determined based on the geographical location information. As a result, by imposing usage restrictions based on geographical location information, the accuracy of restrictions is improved.

[0056] The usage restriction management unit can improve the accuracy of usage restrictions by referring to related literature when managing usage restrictions. The usage restriction management unit, for example, improves the accuracy of usage restrictions by referring to related literature when managing usage restrictions. For example, the optimal usage restriction method is selected based on the related literature. The accuracy of usage restrictions can also be improved by referring to related literature. Furthermore, the priority of usage restrictions can also be determined based on the related literature. In this way, the accuracy of usage restrictions is improved by referring to related literature.

[0057] The update confirmation unit can select the optimal update method by referring to past update data when checking for an update. For example, the update confirmation unit selects the optimal update method by referring to past update data when checking for an update. For example, the optimal update method is selected based on past update data. Also, by referring to past update data, the accuracy of updates can be improved. Furthermore, the priority of updates can be determined based on past update data. In this way, the accuracy of updates can be improved by selecting the optimal update method based on past update data.

[0058] The update checking unit can check update data taking geographical location information into consideration when checking for updates. For example, the update checking unit checks update data taking geographical location information into consideration when checking for updates. For example, update data for each region is checked based on the geographical location information. The method for checking update data can also be adjusted taking geographical location information into consideration. Furthermore, the priority of update data can also be determined based on the geographical location information. As a result, checking update data based on geographical location information improves checking accuracy.

[0059] The security management unit can select optimal security measures by referring to past security data during security management. For example, the security management unit selects optimal security measures by referring to past security data during security management. For example, optimal security measures are selected based on past security data. The accuracy of security measures can also be improved by referring to past security data. Furthermore, the priority of security measures can also be determined based on past security data. In this way, the accuracy of measures is improved by selecting optimal security measures based on past security data.

[0060] The security management unit can take security measures into consideration of geographical location information during security management. The security management unit, for example, takes security measures into consideration of geographical location information during security management. For example, the security measures for each region are applied based on the geographical location information. The security measures can also be adjusted by taking the geographical location information into consideration. Furthermore, the priority of security measures can also be determined based on the geographical location information. As a result, by taking security measures based on the geographical location information, the accuracy of the measures is improved.

[0061] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0062] The land management system can further include a regional characteristics analysis unit. The regional characteristics analysis unit analyzes the characteristics of each region and evaluates the availability and demand for land. For example, it can propose optimal land use methods taking into account the region's demographic trends, economic situation, and infrastructure development status. The regional characteristics analysis unit can also adjust land prices based on the region's characteristics. This makes it possible to manage and buy and sell land while taking into account the characteristics of each region.

[0063] The land management system may further include an environmental impact assessment unit. The environmental impact assessment unit assesses the impact of land use on the environment. For example, it can consider the impact of land development on the ecosystem and propose appropriate land use methods from the perspective of environmental protection. The environmental impact assessment unit can also assess environmental risks associated with land use and propose risk mitigation measures. This promotes environmentally friendly land use.

[0064] The land management system can also have a community liaison department. This department strengthens ties with local residents and businesses and collects their opinions and requests regarding land use. For example, it can formulate land use plans that reflect the opinions of local residents. It can also revitalize the local economy through cooperation with local businesses. This strengthens ties with the local community and promotes appropriate land use.

[0065] The land management system may also include a historical and cultural protection department, which evaluates the historical and cultural value of land and takes measures to protect it. For example, it may support the preservation and restoration of historical buildings and cultural properties. It may also propose land use methods that take into account the land's historical background. This promotes land use that respects its historical and cultural value.

[0066] The land management system can further include a disaster risk assessment unit. The disaster risk assessment unit assesses the disaster risk of the land and proposes risk mitigation measures. For example, it can assess the risk of natural disasters such as earthquakes and floods and take appropriate disaster prevention measures. It can also propose restrictions on land use in areas with high disaster risk and infrastructure development to reduce the risk. This promotes safe land use that takes disaster risk into consideration.

[0067] The processing flow of the first embodiment will be briefly explained below.

[0068] Step 1: The collection department collects information on vacant or abandoned houses and land with unknown owners across the country. The collection department collects information based on data provided by local governments and real estate agents. For example, detailed information such as the location, area, and current condition of vacant houses can be collected. Information can also be collected through the Internet or field surveys. For example, information can be collected from public databases on the Internet or real estate agent websites. Field surveys allow information to be collected directly on-site. Step 2: The registration unit registers the information collected by the collection unit in a database and manages it all together. The registration unit registers the collected data in a database and centrally manages information on vacant houses and vacant lots across the country. The database structure includes information such as the location, area, and current status of vacant houses. The registration unit can implement security measures such as data encryption and access control to ensure the security of the database. Step 3: The sales management department manages sales for commercial or residential use based on the information registered by the registration department. The sales management department creates a list of vacant land available for commercial use and vacant houses available for residential use, and provides this to potential buyers. Potential buyers can select land based on the listed information and carry out the purchase procedure. The sales management department can also consider the attribute information of potential buyers when conducting sales. For example, it selects the most appropriate sales method based on attribute information such as the age, occupation, and interests of the potential buyer. Step 4: The fee management unit manages the system by which the local government or business receives a fee when a sale is concluded by the sales management unit. The fee management unit manages the system by which the local government or business receives a fee when a land sale is concluded. The fee calculation method and standards include the fee rate and the timing of calculation. The fee management unit can also refer to past fee data to select the optimal fee calculation method. Step 5: The Use Restriction Management Department manages the use restrictions of the land purchased and sold by the Purchase and Sale Management Department. The Use Restriction Management Department manages the use restrictions of the contract holder and prevents resale overseas or resale altogether. The specific content and standards of the use restrictions include the available uses and the scope of restrictions. The Use Restriction Management Department can also impose use restrictions taking into account the contract holder's attribute information. For example, it selects the optimal use restriction method based on the contract holder's attribute information such as age, occupation, and interests.

[0069] (Example 2) A land management system according to an embodiment of the present invention compiles a nationwide list of vacant houses, abandoned houses, and land with unknown owners and manages it as a database. This land management system manages vacant houses and vacant land nationwide without requiring any procedures from local governments. The listed data is bought and sold for commercial or residential use, and the local government managing the land and businesses participating in the transaction receive a commission. Contractors can freely use the purchased land, but resale to overseas markets and resale itself is prohibited. For example, information on vacant houses, abandoned houses, and land with unknown owners nationwide is collected. This information is based on data provided by local governments and real estate agents. For example, detailed information on vacant houses, such as their location, area, and current condition, is collected. The collected information is then registered in a database and managed in a centralized manner. This database centrally manages information on vacant houses and vacant land nationwide, without requiring any procedures from local governments. For example, information on vacant houses, such as their location, area, and current condition, is registered in the database. The registered information is bought and sold for commercial or residential use. For example, vacant land available for commercial use and vacant houses available for residential use are listed and provided to potential buyers. Potential buyers select land based on the listed information and complete the purchase process. The local government managing the land and the businesses participating in the transaction receive a commission. For example, when a land transaction is completed, the local government or business receives a commission. This increases the profits of the local government and business. Contractors can freely use the purchased land. For example, they can use the purchased land for residential or commercial purposes. However, resale to overseas markets and resale itself are prohibited. This promotes appropriate land use. This system centrally manages vacant houses, abandoned houses, and land with unknown owners nationwide, enabling efficient sales and purchases. It also increases the profits of local governments and businesses and promotes appropriate land use. This allows the land management system to centrally manage vacant houses, abandoned houses, and land with unknown owners nationwide, enabling efficient sales and appropriate use.

[0070] A land management system according to an embodiment includes a collection unit, a registration unit, a sales management unit, a fee management unit, and a use restriction management unit. The collection unit collects information on vacant or abandoned houses and land with unknown owners nationwide. The collection unit collects information based on data provided by, for example, local governments and real estate agents. For example, the collection unit can collect detailed information on vacant houses, such as their location, area, and current status. The collection unit can also collect information via the Internet or through field surveys. For example, information can be collected from public databases on the Internet or real estate agent websites. Field surveys can involve visiting the site and collecting information directly. The registration unit registers the information collected by the collection unit in a database and manages it in a centralized manner. For example, the registration unit registers the collected data in a database and centrally manages information on vacant houses and vacant land nationwide. The database structure includes information on the location, area, and current status of vacant houses. The registration unit can implement security measures, such as data encryption and access control, to ensure the security of the database. The sales management unit manages sales and purchases for commercial or residential use based on the information registered by the registration unit. The sales management unit, for example, lists vacant land available for commercial use or vacant houses available for residential use and provides the listing to potential buyers. Potential buyers can select land based on the listed information and complete the purchase procedure. The sales management unit can also conduct sales and purchases taking into account the attribute information of the potential buyer. For example, the optimal sales and purchase method is selected based on the attribute information of the potential buyer, such as the age, occupation, and interests of the potential buyer. The fee management unit manages a system by which a local government or business receives a fee when a sale is concluded by the sales management unit. The fee management unit manages a system by which a local government or business receives a fee when a land sale is concluded, for example. The fee calculation method and criteria include, for example, the fee rate and the timing of calculation. The fee management unit can also select the optimal fee calculation method by referring to past fee data. The use restriction management unit manages use restrictions on land sold and purchased by the sales management unit. For example, the use restriction management unit manages use restrictions on the contract holder and prevents resale overseas or resale altogether. The specific content and criteria of the use restrictions include, for example, the available uses and the scope of restrictions.The usage restriction management unit can also impose usage restrictions taking into account the contractor's attribute information. For example, the optimal usage restriction method is selected based on the contractor's attribute information, such as age, occupation, and interests. As a result, the land management system according to the embodiment can collectively manage vacant houses, abandoned houses, and land with unknown owners across the country, enabling efficient buying and selling and appropriate use.

[0071] The collection unit can receive data provided by local governments and real estate agents. For example, the collection unit collects information based on data provided by local governments and real estate agents. For example, it can collect detailed information such as the location, area, and current status of vacant houses. The collection unit can also collect information via the Internet or field surveys. For example, it collects information from public databases on the Internet and real estate agent websites. In field surveys, it is possible to go to the site and collect information directly. In this way, by receiving data provided by local governments and real estate agents, the reliability of the collected data is improved.

[0072] The registration unit can register the collected data in a database and manage it all at once. The registration unit, for example, registers the collected data in a database and centrally manages information on vacant houses and vacant lots across the country. The database structure includes, for example, information such as the location, area, and current status of vacant houses. The registration unit can implement security measures such as data encryption and access control to ensure the security of the database. As a result, by registering the data in a database and managing it all at once, data management becomes more efficient.

[0073] The sales management unit can create a list of vacant land that can be used for commercial purposes or vacant houses that can be used for residential purposes, and provide it to potential buyers. The sales management unit can, for example, create a list of vacant land that can be used for commercial purposes or vacant houses that can be used for residential purposes, and provide it to potential buyers. Potential buyers can select land and carry out the purchase procedure based on the listed information. The sales management unit can also conduct sales taking into account the attribute information of the potential buyer. For example, the optimal sales method can be selected based on attribute information such as the age, occupation, and interests of the potential buyer. This makes it easier for potential buyers to select appropriate land based on the listed information.

[0074] The fee management unit can manage a system whereby local governments and businesses receive fees when a land sale is concluded. The fee management unit manages a system whereby local governments and businesses receive fees when a land sale is concluded, for example. Fee calculation methods and standards include, for example, the fee rate and the timing of calculation. The fee management unit can also select the optimal fee calculation method by referring to past fee data. This makes fee management more efficient and improves the profits of local governments and businesses.

[0075] The usage restriction management unit manages the usage restrictions of the contract holder and can prevent resale overseas or resale altogether. The usage restriction management unit, for example, manages the usage restrictions of the contract holder and prevents resale overseas or resale altogether. The specific content and standards of the usage restrictions include, for example, the available uses and the scope of restrictions. The usage restriction management unit can also impose usage restrictions taking into account the contract holder's attribute information. For example, the optimal usage restriction method is selected based on the contract holder's attribute information such as age, occupation, and interests. This promotes appropriate use of land.

[0076] The collection unit may include an update confirmation unit that updates and checks data. The collection unit may include, for example, an update confirmation unit that updates and checks data. The update confirmation unit, for example, checks the currency of the collected data and updates the data as necessary. The update frequency and confirmation method may be, for example, periodic checks or an automated system. This makes data updating and checking more efficient, and the latest information is always maintained.

[0077] The registration unit may include a security management unit that ensures the security of the database. The registration unit may include, for example, a security management unit that ensures the security of the database. The security management unit implements security measures such as data encryption and access control. This ensures the security of the database and strengthens the protection of data.

[0078] The collection unit can estimate the user's emotions and adjust the timing of data collection based on the estimated user emotions. The collection unit, for example, estimates the user's emotions and adjusts the timing of data collection based on the estimated user emotions. For example, if the user is feeling stressed, the frequency of data collection can be reduced to reduce the burden. Also, if the user is relaxed, the frequency of data collection can be increased to collect more detailed information. Furthermore, if the user is in a hurry, the timing of data collection can be adjusted to collect information quickly. In this way, the burden on the user can be reduced by adjusting the timing of data collection according to the user's emotions.

[0079] The collection unit can analyze past data collection history and select the optimal collection method. The collection unit, for example, analyzes past data collection history and selects the optimal collection method. For example, the collection unit identifies and applies the most efficient collection method from the past data collection history. The collection unit can also analyze past data collection history and optimize the timing and frequency of collection. Furthermore, the collection target priority can be determined based on the past data collection history. As a result, the collection efficiency is improved by selecting the optimal collection method based on the past data collection history.

[0080] The collection unit can perform filtering based on the characteristics and demand of the region when collecting data. For example, the collection unit performs filtering based on the characteristics and demand of the region when collecting data. For example, the collection unit selects the type of data to collect based on the characteristics of the region. It can also determine the priority of the data to be collected according to the demand of the region. Furthermore, it can adjust the range of data to be collected taking into account the characteristics and demand of the region. This makes it possible to collect data according to the characteristics and demand of the region.

[0081] The collection unit can estimate the user's emotions and determine the priority of data to be collected based on the estimated user's emotions. The collection unit, for example, estimates the user's emotions and determines the priority of data to be collected based on the estimated user's emotions. For example, if the user is feeling stressed, data of high importance can be collected with priority. Also, if the user is relaxed, detailed data can be collected with priority. Furthermore, if the user is in a hurry, data that can be collected quickly can be collected with priority. In this way, by determining the priority of data to be collected according to the user's emotions, important data can be collected with priority.

[0082] The collection unit can prioritize collecting highly relevant data by taking geographical location information into consideration when collecting data. For example, the collection unit prioritizes collecting highly relevant data by taking geographical location information into consideration when collecting data. For example, the collection unit prioritizes collecting highly relevant data based on the geographical location information. The range of data to be collected can also be adjusted by taking geographical location information into consideration. Furthermore, the priority of data to be collected can also be determined based on the geographical location information. As a result, by preferentially collecting highly relevant data based on the geographical location information, collection efficiency is improved.

[0083] The collection unit can analyze social media activity and collect related data when collecting data. For example, the collection unit analyzes social media activity and collects related data when collecting data. For example, the collection unit analyzes social media activity and collects related data. The collection unit can also determine the priority of data to be collected based on social media trends. Furthermore, the range of data to be collected can be adjusted taking into account the amount of social media activity. This improves the accuracy of collection by collecting related data based on social media activity.

[0084] The registration unit can estimate the user's emotion and adjust the expression method for data registration based on the estimated user's emotion. The registration unit, for example, estimates the user's emotion and adjusts the expression method for data registration based on the estimated user's emotion. For example, if the user is feeling stressed, data can be registered using a simple expression method. Also, if the user is relaxed, data can be registered using a detailed expression method. Furthermore, if the user is in a hurry, an expression method that can be registered quickly can be selected. In this way, the burden on the user is reduced by adjusting the expression method for data registration according to the user's emotion.

[0085] The registration unit can adjust the level of detail of the registration based on the importance of the data when registering the data. For example, the registration unit adjusts the level of detail of the registration based on the importance of the data when registering the data. For example, data with high importance is registered in detail, and data with low importance is registered in a simplified manner. The level of detail of the registration can also be adjusted according to the importance of the data. Furthermore, data with high importance can be registered in detail with priority. This makes it possible to register data in detail according to the importance of the data.

[0086] The registration unit can apply different registration algorithms depending on the category of data when registering data. For example, the registration unit applies different registration algorithms depending on the category of data when registering data. For example, different registration algorithms are applied to commercial data and residential data. The registration unit can also select the optimal registration algorithm depending on the category of data. Furthermore, different registration algorithms can be applied for each category of data. This makes it possible to perform optimal registration depending on the category of data.

[0087] The registration unit can estimate the user's emotion and adjust the length of the registered data based on the estimated user's emotion. The registration unit, for example, estimates the user's emotion and adjusts the length of the registered data based on the estimated user's emotion. For example, if the user is feeling stressed, short data can be registered. Also, if the user is relaxed, detailed data can be registered. Furthermore, if the user is in a hurry, short data that can be registered quickly can be selected. In this way, adjusting the length of the registered data according to the user's emotion reduces the burden on the user.

[0088] The registration unit can determine the priority of registration based on the time of data collection when registering data. For example, the registration unit determines the priority of registration based on the time of data collection when registering data. For example, the most recent data is registered preferentially. The priority of registration can also be determined based on the time of data collection. Furthermore, older data can be postponed and the most recent data can be registered preferentially. This makes it possible to prioritize registration based on the time of data collection.

[0089] The registration unit can adjust the order of registration based on the relevance of the data when registering the data. For example, the registration unit adjusts the order of registration based on the relevance of the data when registering the data. For example, highly relevant data is registered preferentially. The registration order can also be adjusted based on the relevance of the data. Furthermore, data with low relevance can be postponed and highly relevant data can be registered preferentially. This enables efficient registration based on the relevance of the data.

[0090] The trading management unit can estimate the user's emotions and adjust the trading criteria based on the estimated user emotions. The trading management unit, for example, estimates the user's emotions and adjusts the trading criteria based on the estimated user emotions. For example, if the user is feeling stressed, simple trading criteria can be provided. Also, if the user is relaxed, detailed trading criteria can be provided. Furthermore, if the user is in a hurry, criteria that allow for quick trading can be selected. This makes it possible to adjust the trading criteria according to the user's emotions.

[0091] The trading management unit can improve the accuracy of trading by taking into account the interrelationships of data during trading management. The trading management unit, for example, improves the accuracy of trading by taking into account the interrelationships of data during trading management. For example, the trading management unit analyzes the interrelationships of data and selects the optimal trading method. The accuracy of trading can also be improved by taking into account the interrelationships of data. Furthermore, the priority of trading can also be determined based on the interrelationships of data. In this way, the accuracy of trading is improved by taking into account the interrelationships of data.

[0092] The buying and selling management unit can conduct buying and selling taking into consideration the attribute information of the prospective purchaser when managing buying and selling. The buying and selling management unit, for example, conducts buying and selling taking into consideration the attribute information of the prospective purchaser when managing buying and selling. For example, the optimal buying and selling method is selected based on the attribute information of the prospective purchaser. The accuracy of buying and selling can also be improved by taking into consideration the attribute information of the prospective purchaser. Furthermore, the priority of buying and selling can also be determined based on the attribute information of the prospective purchaser. In this way, the accuracy of buying and selling can be improved by taking into consideration the attribute information of the prospective purchaser.

[0093] The trading management unit can estimate the user's emotions and adjust the order in which trading results are displayed based on the estimated user emotions. The trading management unit, for example, estimates the user's emotions and adjusts the order in which trading results are displayed based on the estimated user emotions. For example, if the user is feeling stressed, important results can be displayed preferentially. Also, if the user is relaxed, detailed results can be displayed preferentially. Furthermore, if the user is in a hurry, results that can be checked quickly can be displayed preferentially. This makes it possible to adjust the display order of trading results according to the user's emotions.

[0094] The trading management unit can take geographical distribution into consideration when managing trading. The trading management unit, for example, takes geographical distribution into consideration when managing trading. For example, the trading management unit selects the optimal trading method based on the geographical distribution. The accuracy of trading can also be improved by taking geographical distribution into consideration. Furthermore, the priority of trading can also be determined based on the geographical distribution. In this way, the accuracy of trading can be improved by taking geographical distribution into consideration.

[0095] The trading management unit can improve the accuracy of trading by referring to related literature during trading management. The trading management unit, for example, improves the accuracy of trading by referring to related literature during trading management. For example, the optimal trading method is selected based on the related literature. The accuracy of trading can also be improved by referring to related literature. Furthermore, trading priorities can also be determined based on the related literature. In this way, the accuracy of trading is improved by referring to related literature.

[0096] The fee management unit can estimate the user's emotions and adjust the fee calculation method based on the estimated user emotions. The fee management unit, for example, estimates the user's emotions and adjusts the fee calculation method based on the estimated user emotions. For example, if the user is feeling stressed, a simple fee calculation method can be provided. Also, if the user is relaxed, a detailed fee calculation method can be provided. Furthermore, if the user is in a hurry, a fee calculation method that allows for quick calculation can be selected. This makes it possible to adjust the fee calculation method according to the user's emotions.

[0097] The fee management unit can select the optimal fee calculation method by referring to past fee data when managing fees. The fee management unit, for example, selects the optimal fee calculation method by referring to past fee data when managing fees. For example, the optimal fee calculation method is selected based on past fee data. The accuracy of fee calculation can also be improved by referring to past fee data. Furthermore, the priority of fee calculation can also be determined based on past fee data. In this way, calculation accuracy is improved by selecting the optimal fee calculation method based on past fee data.

[0098] The fee management unit can adjust the level of detail of fees according to the scale of trading when managing fees. The fee management unit, for example, adjusts the level of detail of fees according to the scale of trading when managing fees. For example, if the scale of trading is large, a detailed fee calculation method is provided. The level of detail of fees can also be adjusted according to the scale of trading. Furthermore, if the scale of trading is small, a simplified fee calculation method can also be provided. This makes it possible to adjust the level of detail of fee calculation according to the scale of trading.

[0099] The fee management unit can estimate the user's emotions and determine the priority of fees based on the estimated user's emotions. The fee management unit, for example, estimates the user's emotions and determines the priority of fees based on the estimated user's emotions. For example, if the user is feeling stressed, important fees can be calculated with priority. Also, if the user is relaxed, detailed fees can be calculated with priority. Furthermore, if the user is in a hurry, fees that can be calculated quickly can be calculated with priority. This makes it possible to determine the priority of fees according to the user's emotions.

[0100] The fee management unit can calculate fees taking into account geographical location information when managing fees. For example, the fee management unit calculates fees taking into account geographical location information when managing fees. For example, the fee management unit calculates fees for each region based on the geographical location information. The fee calculation method can also be adjusted taking into account the geographical location information. Furthermore, the priority of fees can also be determined based on the geographical location information. As a result, calculating fees based on geographical location information improves calculation accuracy.

[0101] The fee management unit can improve the accuracy of fees by referring to related literature when managing fees. The fee management unit, for example, improves the accuracy of fees by referring to related literature when managing fees. For example, the optimal fee calculation method is selected based on the related literature. The accuracy of fee calculation can also be improved by referring to related literature. Furthermore, the priority of fee calculation can also be determined based on the related literature. In this way, the accuracy of fee calculation is improved by referring to related literature.

[0102] The usage restriction management unit can estimate the user's emotions and adjust the usage restriction method based on the estimated user's emotions. The usage restriction management unit, for example, estimates the user's emotions and adjusts the usage restriction method based on the estimated user's emotions. For example, if the user is feeling stressed, a simple usage restriction method can be provided. Also, if the user is relaxed, a detailed usage restriction method can be provided. Furthermore, if the user is in a hurry, a usage restriction method that can be applied quickly can be selected. This makes it possible to adjust the usage restriction method according to the user's emotions.

[0103] The usage restriction management unit can select the optimal usage restriction method by referring to past usage restriction data when managing usage restrictions. The usage restriction management unit, for example, selects the optimal usage restriction method by referring to past usage restriction data when managing usage restrictions. For example, the optimal usage restriction method is selected based on past usage restriction data. The accuracy of usage restrictions can also be improved by referring to past usage restriction data. Furthermore, the priority of usage restrictions can also be determined based on past usage restriction data. In this way, the accuracy of restrictions is improved by selecting the optimal usage restriction method based on past usage restriction data.

[0104] The usage restriction management unit can impose usage restrictions by taking into account the attribute information of the subscriber when managing usage restrictions. The usage restriction management unit, for example, imposes usage restrictions by taking into account the attribute information of the subscriber when managing usage restrictions. For example, the unit selects the optimal usage restriction method based on the attribute information of the subscriber. The accuracy of usage restrictions can also be improved by taking into account the attribute information of the subscriber. Furthermore, the priority of usage restrictions can also be determined based on the attribute information of the subscriber. In this way, the accuracy of usage restrictions can be improved by taking into account the attribute information of the subscriber.

[0105] The usage restriction management unit can estimate the user's emotions and determine the priority of usage restrictions based on the estimated user's emotions. The usage restriction management unit, for example, estimates the user's emotions and determines the priority of usage restrictions based on the estimated user's emotions. For example, if the user is feeling stressed, important usage restrictions can be applied with priority. Also, if the user is relaxed, detailed usage restrictions can be applied with priority. Furthermore, if the user is in a hurry, usage restrictions that can be applied quickly can be applied with priority. This makes it possible to determine the priority of usage restrictions according to the user's emotions.

[0106] The usage restriction management unit can impose usage restrictions taking into account geographical location information when managing usage restrictions. The usage restriction management unit, for example, imposes usage restrictions taking into account geographical location information when managing usage restrictions. For example, the usage restriction management unit applies usage restrictions for each region based on the geographical location information. The usage restriction method can also be adjusted taking into account the geographical location information. Furthermore, the priority of usage restrictions can also be determined based on the geographical location information. As a result, by imposing usage restrictions based on geographical location information, the accuracy of restrictions is improved.

[0107] The usage restriction management unit can improve the accuracy of usage restrictions by referring to related literature when managing usage restrictions. The usage restriction management unit, for example, improves the accuracy of usage restrictions by referring to related literature when managing usage restrictions. For example, the optimal usage restriction method is selected based on the related literature. The accuracy of usage restrictions can also be improved by referring to related literature. Furthermore, the priority of usage restrictions can also be determined based on the related literature. In this way, the accuracy of usage restrictions is improved by referring to related literature.

[0108] The update confirmation unit can estimate the user's emotions and adjust the timing of data updates based on the estimated user emotions. The update confirmation unit, for example, estimates the user's emotions and adjusts the timing of data updates based on the estimated user emotions. For example, if the user is feeling stressed, the frequency of data updates can be reduced to reduce the burden. Also, if the user is relaxed, the frequency of data updates can be increased to provide more detailed information. Furthermore, if the user is in a hurry, the timing of data updates can be adjusted to provide information quickly. This makes it possible to adjust the timing of data updates according to the user's emotions.

[0109] The update confirmation unit can select the optimal update method by referring to past update data when checking for an update. For example, the update confirmation unit selects the optimal update method by referring to past update data when checking for an update. For example, the optimal update method is selected based on past update data. Also, by referring to past update data, the accuracy of updates can be improved. Furthermore, the priority of updates can be determined based on past update data. In this way, the accuracy of updates can be improved by selecting the optimal update method based on past update data.

[0110] The update confirmation unit can estimate the user's emotions and determine the priority of update data based on the estimated user's emotions. The update confirmation unit, for example, estimates the user's emotions and determines the priority of update data based on the estimated user's emotions. For example, if the user is feeling stressed, important update data can be checked with priority. Also, if the user is relaxed, detailed update data can be checked with priority. Furthermore, if the user is in a hurry, update data that can be checked quickly can be checked with priority. This makes it possible to determine the priority of update data according to the user's emotions.

[0111] The update checking unit can check update data taking geographical location information into consideration when checking for updates. For example, the update checking unit checks update data taking geographical location information into consideration when checking for updates. For example, update data for each region is checked based on the geographical location information. The method for checking update data can also be adjusted taking geographical location information into consideration. Furthermore, the priority of update data can also be determined based on the geographical location information. As a result, checking update data based on geographical location information improves checking accuracy.

[0112] The security management unit can estimate the user's emotions and adjust security measures based on the estimated user's emotions. The security management unit, for example, estimates the user's emotions and adjusts security measures based on the estimated user's emotions. For example, if the user is feeling stressed, simple security measures can be provided. Also, if the user is relaxed, detailed security measures can be provided. Furthermore, if the user is in a hurry, security measures that can be quickly applied can be selected. This makes it possible to adjust security measures according to the user's emotions.

[0113] The security management unit can select optimal security measures by referring to past security data during security management. For example, the security management unit selects optimal security measures by referring to past security data during security management. For example, optimal security measures are selected based on past security data. The accuracy of security measures can also be improved by referring to past security data. Furthermore, the priority of security measures can also be determined based on past security data. In this way, the accuracy of measures is improved by selecting optimal security measures based on past security data.

[0114] The security management unit can estimate the user's emotions and determine the priority of security measures based on the estimated user's emotions. The security management unit, for example, estimates the user's emotions and determines the priority of security measures based on the estimated user's emotions. For example, if the user is feeling stressed, important security measures can be applied with priority. Also, if the user is relaxed, detailed security measures can be applied with priority. Furthermore, if the user is in a hurry, security measures that can be applied quickly can be applied with priority. This makes it possible to determine the priority of security measures according to the user's emotions.

[0115] The security management unit can take security measures into consideration of geographical location information during security management. The security management unit, for example, takes security measures into consideration of geographical location information during security management. For example, the security measures for each region are applied based on the geographical location information. The security measures can also be adjusted by taking the geographical location information into consideration. Furthermore, the priority of security measures can also be determined based on the geographical location information. As a result, by taking security measures based on the geographical location information, the accuracy of the measures is improved. === Hard Collateral 1-1 === Each of the multiple elements, including the collection unit, registration unit, trade management unit, fee management unit, and usage restriction management unit, described above, is realized, for example, by at least one of the smart device 14 and the data processing device 12. For example, the collection unit collects information using the camera 42 and communication I / F 44 of the smart device 14, and processes the collected data by the specific processing unit 290 of the data processing device 12. The registration unit, realized, for example, by the specific processing unit 290 of the data processing device 12, registers the collected information in the database 24. The trade management unit, realized, for example, by the control unit 46A of the smart device 14, manages trades based on the registered information. The fee management unit, realized, for example, by the specific processing unit 290 of the data processing device 12, calculates and manages fees when a trade is concluded. The usage restriction management unit, realized, for example, by the control unit 46A of the smart device 14, manages usage restrictions of the subscriber. === Hard Collateral 1-2 === Each of the multiple elements, including the collection unit, registration unit, trade management unit, fee management unit, and usage restriction management unit, described above, is realized, for example, by at least one of the smart glasses 214 and the data processing device 12. For example, the collection unit collects information using the camera 42 and communication I / F 44 of the smart glasses 214 and processes the collected data by the specific processing unit 290 of the data processing device 12. The registration unit is realized, for example, by the specific processing unit 290 of the data processing device 12 and registers the collected information in the database 24. The trade management unit is realized, for example, by the control unit 46A of the smart glasses 214 and manages trades based on the registered information. The fee management unit is realized, for example, by the specific processing unit 290 of the data processing device 12 and calculates and manages fees when a trade is concluded. The usage restriction management unit is realized, for example, by the control unit 46A of the smart glasses 214 and manages usage restrictions for the subscriber. === Hard Collateral 1-3 === Each of the multiple elements, including the collection unit, registration unit, trade management unit, fee management unit, and usage restriction management unit, described above, is realized, for example, by at least one of the headset terminal 314 and the data processing device 12. For example, the collection unit collects information using the camera 42 and communication I / F 44 of the headset terminal 314, and processes the collected data by the specific processing unit 290 of the data processing device 12. The registration unit is realized, for example, by the specific processing unit 290 of the data processing device 12, and registers the collected information in the database 24. The trade management unit is realized, for example, by the control unit 46A of the headset terminal 314, and manages trades based on the registered information. The fee management unit is realized, for example, by the specific processing unit 290 of the data processing device 12, and calculates and manages fees when a trade is concluded. The usage restriction management unit is realized, for example, by the control unit 46A of the headset terminal 314, and manages usage restrictions for the subscriber. === Hard Collateral 1-4 === Each of the multiple elements including the collection unit, registration unit, trade management unit, fee management unit, and usage restriction management unit described above is realized, for example, by at least one of the robot 414 and the data processing device 12. For example, the collection unit collects information using the camera 42 and communication I / F 44 of the robot 414, and processes the collected data by the specific processing unit 290 of the data processing device 12. The registration unit is realized, for example, by the specific processing unit 290 of the data processing device 12, and registers the collected information in the database 24. The trade management unit is realized, for example, by the control unit 46A of the robot 414, and manages trades based on the registered information. The fee management unit is realized, for example, by the specific processing unit 290 of the data processing device 12, and calculates and manages fees when a trade is concluded. The usage restriction management unit is realized, for example, by the control unit 46A of the robot 414, and manages usage restrictions for the contractor.

[0116] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0117] The land management system can further include a regional characteristics analysis unit. The regional characteristics analysis unit analyzes the characteristics of each region and evaluates the availability and demand for land. For example, it can propose optimal land use methods taking into account the region's demographic trends, economic situation, and infrastructure development status. The regional characteristics analysis unit can also adjust land prices based on the region's characteristics. This makes it possible to manage and buy and sell land while taking into account the characteristics of each region.

[0118] The land management system may further include an environmental impact assessment unit. The environmental impact assessment unit assesses the impact of land use on the environment. For example, it can consider the impact of land development on the ecosystem and propose appropriate land use methods from the perspective of environmental protection. The environmental impact assessment unit can also assess environmental risks associated with land use and propose risk mitigation measures. This promotes environmentally friendly land use.

[0119] The land management system can also have a community liaison department. This department strengthens ties with local residents and businesses and collects their opinions and requests regarding land use. For example, it can formulate land use plans that reflect the opinions of local residents. It can also revitalize the local economy through cooperation with local businesses. This strengthens ties with the local community and promotes appropriate land use.

[0120] The land management system may also include a historical and cultural protection department, which evaluates the historical and cultural value of land and takes measures to protect it. For example, it may support the preservation and restoration of historical buildings and cultural properties. It may also propose land use methods that take into account the land's historical background. This promotes land use that respects its historical and cultural value.

[0121] The land management system can further include a disaster risk assessment unit. The disaster risk assessment unit assesses the disaster risk of the land and proposes risk mitigation measures. For example, it can assess the risk of natural disasters such as earthquakes and floods and take appropriate disaster prevention measures. It can also propose restrictions on land use in areas with high disaster risk and infrastructure development to reduce the risk. This promotes safe land use that takes disaster risk into consideration.

[0122] The collection unit can estimate the user's emotions and adjust the data collection method based on the estimated user emotions. For example, if the user is feeling stressed, data can be collected in the form of simple questions. Alternatively, if the user is relaxed, data can be collected in the form of a detailed questionnaire. Furthermore, if the user is in a hurry, a data collection method that can be completed in a short time can be selected. This enables flexible data collection according to the user's emotions.

[0123] The trading management unit can estimate the user's emotions and adjust the trading process based on the estimated user emotions. For example, if the user is feeling stressed, a simple trading process can be provided. If the user is relaxed, a trading process with detailed explanations can be provided. Furthermore, if the user is in a hurry, a process that allows the trading process to be completed quickly can be selected. This makes it possible to adjust the trading process according to the user's emotions.

[0124] The fee management unit can estimate the user's emotions and adjust the method of explaining fees based on the estimated user emotions. For example, if the user is stressed, a concise explanation can be provided. If the user is relaxed, a detailed explanation can be provided. Furthermore, if the user is in a hurry, a method of explanation that can be quickly understood can be selected. This makes it possible to adjust the method of explaining fees according to the user's emotions.

[0125] The usage restriction management unit can estimate the user's emotions and adjust the notification method for usage restrictions based on the estimated user emotions. For example, if the user is feeling stressed, a brief notification can be provided. If the user is relaxed, a detailed notification can be provided. Furthermore, if the user is in a hurry, a notification method that can be quickly understood can be selected. This makes it possible to adjust the notification method for usage restrictions according to the user's emotions.

[0126] The update confirmation unit can estimate the user's emotions and adjust the update confirmation method based on the estimated user's emotions. For example, if the user is stressed, a simple confirmation method can be provided. If the user is relaxed, a detailed confirmation method can be provided. Furthermore, if the user is in a hurry, a method that allows for quick confirmation can be selected. This makes it possible to adjust the update confirmation method according to the user's emotions.

[0127] The processing flow of the second embodiment will be briefly explained below.

[0128] Step 1: The collection department collects information on vacant or abandoned houses and land with unknown owners across the country. The collection department collects information based on data provided by local governments and real estate agents. For example, detailed information such as the location, area, and current condition of vacant houses can be collected. Information can also be collected through the Internet or field surveys. For example, information can be collected from public databases on the Internet or real estate agent websites. Field surveys allow information to be collected directly on-site. Step 2: The registration unit registers the information collected by the collection unit in a database and manages it all together. The registration unit registers the collected data in a database and centrally manages information on vacant houses and vacant lots across the country. The database structure includes information such as the location, area, and current status of vacant houses. The registration unit can implement security measures such as data encryption and access control to ensure the security of the database. Step 3: The sales management department manages sales for commercial or residential use based on the information registered by the registration department. The sales management department creates a list of vacant land available for commercial use and vacant houses available for residential use, and provides this to potential buyers. Potential buyers can select land based on the listed information and carry out the purchase procedure. The sales management department can also consider the attribute information of potential buyers when conducting sales. For example, it selects the most appropriate sales method based on attribute information such as the age, occupation, and interests of the potential buyer. Step 4: The fee management unit manages the system by which the local government or business receives a fee when a sale is concluded by the sales management unit. The fee management unit manages the system by which the local government or business receives a fee when a land sale is concluded. The fee calculation method and standards include the fee rate and the timing of calculation. The fee management unit can also refer to past fee data to select the optimal fee calculation method. Step 5: The Use Restriction Management Department manages the use restrictions of the land purchased and sold by the Purchase and Sale Management Department. The Use Restriction Management Department manages the use restrictions of the contract holder and prevents resale overseas or resale altogether. The specific content and standards of the use restrictions include the available uses and the scope of restrictions. The Use Restriction Management Department can also impose use restrictions taking into account the contract holder's attribute information. For example, it selects the optimal use restriction method based on the contract holder's attribute information such as age, occupation, and interests.

[0129] 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 a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the 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.

[0130] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> Examples of the generative AI include a neural network (NN) and a neural network (NN). The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image (e.g., still image data or video data). The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in one or more data formats of voice data, text data, image data, etc. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specification processing unit 290 performs the above-mentioned specification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and may perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processing of each of the above-mentioned parts is performed by an AI, the processing may be performed in part or entirely by the AI, but is not limited to these examples. The processing performed by an AI including the generative AI may be replaced with rule-based processing, and rule-based processing may be replaced with processing performed by an AI including the generative AI.

[0131] Furthermore, the processing by the data processing system 10 described above is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart device 14, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart device 14. Furthermore, 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.

[0132] The correspondence between each part and the device or control part is not limited to the example described above, and various modifications are possible.

[0133] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0134] 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.

[0135] 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, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0136] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0137] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0138] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0139] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0140] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0141] 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 in accordance with the specific processing program 56 executed on the RAM 30.

[0142] The storage 32 stores a data generation model 58 and an 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 a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0143] In the smart glasses 214, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. 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 the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. The smart glasses 214 also have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0144] Note that a device other than the data processing device 12 may 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 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0145] 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 a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0146] The data generation model 58 is a so-called generative AI. An example of the 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 receives a prompt including an instruction, as well as inference data such as audio data indicating speech, text data indicating text, and image data indicating an image (e.g., still image data or video data). The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in one or more data formats, such as audio data, text data, and image data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation models 58 include AIs other than the generation AI. Examples of AIs other than the generation AI include, but are not limited to, 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), and naive Bayes. These AIs can perform various types of processing, but are not limited to these examples. The AI ​​may also be an AI agent. When the processing of each of the above-described parts is performed by an AI, the processing may be performed in part or entirely by the AI, but is not limited to these examples. Processing performed by an AI, including the generation AI, may be replaced with rule-based processing, and rule-based processing may be replaced with processing performed by an AI, including the generation AI.

[0147] 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 executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart glasses 214, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart glasses 214. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the smart glasses 214 or an external device, etc., and the smart glasses 214 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0148] The correspondence between each part and the device or control part is not limited to the example described above, and various modifications are possible.

[0149] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0150] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0151] 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, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0152] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0153] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0154] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0155] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0156] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0157] 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 in accordance with the specific processing program 56 executed on the RAM 30.

[0158] The storage 32 stores a data generation model 58 and an 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 a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0159] In the headset type terminal 314, the identification process is performed by the processor 46. A identification program 60 is stored in the storage 50. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as a control unit 46A in accordance with the identification program 60 executed on the RAM 48. Note that the headset type terminal 314 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the identification processing unit 290 using these models.

[0160] Note that a device other than the data processing device 12 may 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 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0161] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0162] The data generation model 58 is a so-called generative AI. An example of the 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 receives a prompt including an instruction, as well as inference data such as audio data indicating speech, text data indicating text, and image data indicating an image (e.g., still image data or video data). The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in one or more data formats, such as audio data, text data, and image data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation models 58 include AIs other than the generation AI. Examples of AIs other than the generation AI include, but are not limited to, 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), and naive Bayes. These AIs can perform various types of processing, but are not limited to these examples. The AI ​​may also be an AI agent. When the processing of each of the above-described parts is performed by an AI, the processing may be performed in part or entirely by the AI, but is not limited to these examples. Processing performed by an AI, including the generation AI, may be replaced with rule-based processing, and rule-based processing may be replaced with processing performed by an AI, including the generation AI.

[0163] 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 executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the headset type terminal 314, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the headset type terminal 314. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the headset type terminal 314 or an external device, etc., and the headset type terminal 314 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0164] The correspondence between each part and the device or control part is not limited to the example described above, and various modifications are possible.

[0165] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0166] 7, a 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.

[0167] 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, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0168] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[0169] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0170] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS image sensor or a CCD image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0171] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0172] The control 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 emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[0173] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0174] 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 in accordance with the specific processing program 56 executed on the RAM 30.

[0175] The storage 32 stores a data generation model 58 and an 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 a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0176] In the robot 414, the processor 46 performs the identification process. The storage 50 stores the identification program 60. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as the control unit 46A in accordance with the identification program 60 executed on the RAM 48. The robot 414 also has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can perform the same process as the identification processing unit 290 using these models.

[0177] Note that a device other than the data processing device 12 may 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 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0178] 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 control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[0179] The data generation model 58 is a so-called generative AI. An example of the 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 receives a prompt including an instruction, as well as inference data such as audio data indicating speech, text data indicating text, and image data indicating an image (e.g., still image data or video data). The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in one or more data formats, such as audio data, text data, and image data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation models 58 include AIs other than the generation AI. Examples of AIs other than the generation AI include, but are not limited to, 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), and naive Bayes. These AIs can perform various types of processing, but are not limited to these examples. The AI ​​may also be an AI agent. When the processing of each of the above-described parts is performed by an AI, the processing may be performed in part or entirely by the AI, but is not limited to these examples. Processing performed by an AI, including the generation AI, may be replaced with rule-based processing, and rule-based processing may be replaced with processing performed by an AI, including the generation AI.

[0180] 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 executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the robot 414, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the robot 414. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the robot 414 or an external device, etc., and the robot 414 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0181] The correspondence between each part and the device or control part is not limited to the example described above, and various modifications are possible.

[0182] The emotion identification model 59 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 an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0183] FIG. 9 illustrates an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and behaviors arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion encompasses both emotions and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[0184] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[0185] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[0186] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. Emotions can also be created for robots, cars, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on speech emotion recognition and brain physiological signal analysis systems for emotions, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the area called "reaction," where sensation is dominant. The right half of the emotion map lists emotions belonging to the area called "situation," where situational awareness is dominant.

[0187] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs 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 a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[0188] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[0189] In the above embodiment, an example was given in which a specific process is performed by one computer 22, but the technology disclosed herein is not limited to this, and distributed processing of the specific process may be performed by multiple computers including computer 22.

[0190] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[0191] 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.

[0192] It is not necessary to store all 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 all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[0193] The hardware resource for executing a specific process can be any of the following types of processors: A processor, for example, is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. A processor also includes a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[0194] The hardware resource that executes the specific process may be configured with one of these various processors, or may be configured with 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). Also, the hardware resource that executes the specific process may be a single processor.

[0195] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[0196] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[0197] In the above example, the first to fourth embodiments have been described separately, but some or all of these embodiments may be combined. The smart device 14, smart glasses 214, headset terminal 314, and robot 414 are merely examples, and they may be combined, or other devices may be used. In the above example, the first and second embodiments have been described separately, but they may be combined.

[0198] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[0199] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[0200] [Explanation of symbols]

[0201] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot

Claims

1. A collection department that collects information on vacant or abandoned houses and land with unknown owners across the country; a registration unit that registers the information collected by the collection unit in a database and manages it collectively; a sales management unit that manages sales for commercial or residential use based on the information registered by the registration unit; a fee management unit that receives a fee from a local government or a business operator when a transaction is concluded by the transaction management unit; a use restriction management unit that manages use restrictions on the land purchased and sold by the purchase and sale management unit; Equipped with A system characterized by:

2. The collecting unit Receive data provided by local governments and real estate agents 2. The system of claim 1.

3. The registration unit Collected data is registered in a database and managed centrally.

2. The system of claim 1.

4. The trading management unit Listing vacant land available for commercial use or vacant houses available for residential use and making them available to potential buyers 2. The system of claim 1.

5. The fee management unit Manages the system by which local governments and businesses receive fees when land sales are concluded 2. The system of claim 1.

6. The usage restriction management unit Manage subscriber usage restrictions and prevent resale overseas or resale altogether 2. The system of claim 1.

7. The collecting unit Equipped with an update confirmation unit that updates and confirms data 2. The system of claim 1.

8. The registration unit Equipped with a security management department to ensure database security 2. The system of claim 1.

9. The collecting unit Inferring user emotions and adjusting the timing of data collection based on the estimated user emotions 2. The system of claim 1.

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