system

Abstract

The system according to this embodiment aims to grasp the care needs of postpartum mothers and newborns in real time and provide individualized care plans. [Solution] The system according to the embodiment comprises a monitoring unit, a proposal unit, and a coordination unit. The monitoring unit monitors the mother's health condition and the newborn's care needs. The proposal unit proposes an individualized care plan based on the data collected by the monitoring unit. The coordination unit provides services in cooperation with hotel staff based on the care plan proposed by the proposal unit.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In the conventional technology, there is a problem that it is difficult to grasp the care needs of postpartum mothers and newborns in real time and provide individual care plans.

[0005] The system according to the embodiment aims to grasp the care needs of postpartum mothers and newborns in real time and provide individual care plans.

Means for Solving the Problems

[0006] The system according to this embodiment comprises a monitoring unit, a proposal unit, and a coordination unit. The monitoring unit monitors the mother's health status and the newborn's care needs. The proposal unit proposes an individualized care plan based on the data collected by the monitoring unit. The coordination unit provides services in cooperation with hotel staff based on the care plan proposed by the proposal unit. [Effects of the Invention]

[0007] The system according to this embodiment can grasp the care needs of postpartum mothers and newborns in real time and provide individualized care plans. [Brief explanation of the drawing]

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

[0028] (Example of form 1) The care support system according to an embodiment of the present invention is a system that supports hotels providing care for postpartum mothers and newborns. This care support system monitors the mother's health status and the newborn's care needs in real time and proposes an individualized care plan. Furthermore, the care support system works in cooperation with hotel staff to provide optimal services and support the mother's relaxation and recovery. For example, the care support system collects health data such as the mother's body temperature, blood pressure, and heart rate, as well as care needs such as the newborn's weight, sleep patterns, and breastfeeding status. For example, if the mother's body temperature rises, the care support system can detect the abnormality and propose an appropriate response. Next, the care support system proposes an individualized care plan based on the monitoring results. For example, it can propose an appropriate relaxation plan and nutritional management plan according to the mother's physical condition. It can also propose breastfeeding schedules and measures to improve the sleep environment according to the newborn's care needs. This allows for optimal management of the health of both the mother and the newborn. Furthermore, the care support system works in cooperation with hotel staff to provide optimal services. For example, based on the care plan proposed by the care support system, hotel staff can provide massages and aromatherapy to support the mother's relaxation. Furthermore, hotel staff can provide support for newborn care, including breastfeeding and diaper changes. This reduces the burden on mothers and supports relaxation and recovery. Thus, the care support system provides a safe and secure environment for postpartum mothers and newborns, supporting both the mother's recovery and the newborn's health. For example, a mother's ability to relax reduces stress and promotes recovery. Also, proper newborn care can lead to healthy growth. This encourages the use of postpartum care hotels, creating a society where more mothers and newborns can receive appropriate care. In short, the care support system provides a safe and secure environment for postpartum mothers and newborns, supporting both the mother's recovery and the newborn's health.

[0029] The care support system according to the embodiment comprises a monitoring unit, a suggestion unit, and a coordination unit. The monitoring unit monitors the mother's health status and the newborn's care needs. The monitoring unit collects health data such as the mother's body temperature, blood pressure, and heart rate. For example, if the mother's body temperature rises, the monitoring unit can detect an abnormality and suggest an appropriate response. The monitoring unit collects care needs such as the newborn's weight, sleep patterns, and feeding status. For example, if the newborn's weight decreases, the monitoring unit can detect an abnormality and suggest an appropriate response. The suggestion unit proposes an individualized care plan based on the data collected by the monitoring unit. For example, the suggestion unit proposes an appropriate relaxation plan and nutritional management plan according to the mother's physical condition. For example, if the mother's physical condition deteriorates, the suggestion unit can propose an appropriate relaxation plan. For example, if the suggestion unit proposes a feeding schedule and measures to improve the sleep environment according to the newborn's care needs. For example, if the newborn's sleep pattern is disrupted, the suggestion unit can propose appropriate measures to improve the sleep environment. The Collaboration Department provides services in cooperation with hotel staff based on the care plan proposed by the Proposal Department. For example, the Collaboration Department can provide massages and aromatherapy to support the mother's relaxation, provided by hotel staff. For example, the Collaboration Department can propose an appropriate relaxation plan according to the mother's physical condition. For example, the Collaboration Department can also provide support for newborn care, such as breastfeeding and diaper changing, provided by hotel staff. For example, the Collaboration Department can propose an appropriate breastfeeding schedule according to the newborn's care needs. As a result, the care support system according to the embodiment can monitor the mother's health condition and the newborn's care needs in real time, propose an individualized care plan, and provide optimal services in cooperation with hotel staff.

[0030] The monitoring unit monitors the mother's health and the newborn's care needs. Specifically, it utilizes wearable devices and smartphone apps to collect health data such as the mother's body temperature, blood pressure, and heart rate. These devices are worn on the mother's body, collecting data 24 hours a day and transmitting it to a cloud server. For example, if the mother's body temperature rises, the system detects the abnormality and issues an alert. Furthermore, fluctuations in blood pressure and heart rate are monitored in real time, and if an abnormality is detected, countermeasures are immediately suggested. Similarly, data on the newborn's care needs, such as weight, sleep patterns, and feeding status, are collected. The newborn's weight is measured regularly using a dedicated baby scale, and this data is automatically transmitted to the system. Sleep patterns are monitored using a baby monitor or smart bed, and feeding status is recorded by the mother entering it into a smartphone app. This allows the monitoring unit to comprehensively understand the health status of both the mother and the newborn and respond quickly if an abnormality occurs. In addition, the monitoring unit can analyze the collected data to understand long-term health trends. For example, by analyzing the fluctuation patterns of a mother's body temperature and blood pressure, it is possible to assess the influence of seasons and lifestyle habits and propose preventive care. Similarly, a newborn's weight and sleep patterns can be used as basic data to understand their growth progress and changes in their daily rhythms, and to provide appropriate care.

[0031] The proposal department proposes individualized care plans based on data collected by the monitoring department. Specifically, it proposes appropriate relaxation and nutritional management plans according to the mother's physical condition. For example, if the mother's body temperature is elevated and her stress levels are high, the proposal department may suggest yoga, meditation, or aromatherapy as a relaxation plan. It can also recommend a balanced diet and supplement intake as part of a nutritional management plan. Depending on the newborn's care needs, it can also propose improvements to the breastfeeding schedule and sleep environment. For example, if the newborn is losing weight, the proposal department may suggest increasing the frequency of breastfeeding or providing dietary guidance to improve breast milk quality. If the sleep pattern is disrupted, it may suggest creating an appropriate sleep environment and methods for getting the baby to sleep. The proposal department uses AI to analyze collected data and generate the optimal care plan. Based on analysis of past data and similar cases, the AI ​​can provide the most suitable suggestions for the individual situation. For example, if the mother's health deteriorates, it can refer to past data to suggest relaxation plans that have been effective for other mothers with similar symptoms. Furthermore, regarding the care needs of newborns, we can propose the most effective feeding schedules and measures to improve the sleep environment based on past data. This allows the proposal department to provide optimal care plans tailored to individual needs, supporting the health of both mother and newborn.

[0032] The Liaison Department will work with hotel staff to provide services based on the care plan proposed by the Proposal Department. Specifically, hotel staff will provide massages and aromatherapy to support the mother's relaxation. For example, depending on the mother's physical condition, massage sessions in the relaxation room or relaxation programs using aromatherapy oils can be implemented. This will allow the mother to relax and reduce stress. Hotel staff can also provide support for newborn care, such as breastfeeding and diaper changes. For example, they can inform mothers of feeding times and provide support based on the newborn's feeding schedule. Regarding diaper changes, they can change diapers at the appropriate time to maintain a clean environment. The Liaison Department will work closely with hotel staff to coordinate the implementation of the proposed care plan. For example, they will adjust the resources and schedules necessary for implementing the relaxation plan so that the mother can receive relaxation at the optimal time. Regarding newborn care, they will also share feeding and diaper change timings with hotel staff to ensure smooth care. Furthermore, the Liaison Department can collect feedback from mothers and newborns to continuously improve the quality of service. For example, the effectiveness of relaxation plans and satisfaction with breastfeeding support are evaluated, and plans are reviewed and improved as needed. This allows the liaison department to provide optimal care for mothers and newborns and strengthen collaboration with hotel staff.

[0033] The monitoring unit can collect health data such as the mother's body temperature, blood pressure, and heart rate. For example, the monitoring unit can measure the mother's body temperature and collect the data. The monitoring unit can also measure the mother's blood pressure and collect the data. The monitoring unit can also measure the mother's heart rate and collect the data. This allows for detailed monitoring of the mother's health status. Health data includes, but is not limited to, body temperature, blood pressure, and heart rate. Some or all of the above-described processes in the monitoring unit may be performed using, for example, AI, or without AI. For example, the monitoring unit can input the mother's body temperature data into a generating AI and have the generating AI perform a process to detect abnormalities in body temperature.

[0034] The monitoring unit can collect care needs such as the newborn's weight, sleep patterns, and feeding status. For example, the monitoring unit can measure the newborn's weight and collect data. The monitoring unit can also record the newborn's sleep patterns and collect data. The monitoring unit can also record the newborn's feeding status and collect data. This allows for detailed monitoring of the newborn's care needs. Care needs include, but are not limited to, weight, sleep patterns, and feeding status. Some or all of the above processing in the monitoring unit may be performed using, for example, AI, or not using AI. For example, the monitoring unit can input newborn weight data into a generating AI and cause the generating AI to perform a process to detect abnormalities in weight.

[0035] The suggestion unit can propose a relaxation plan according to the mother's physical condition. For example, if the mother is in good health, the suggestion unit may suggest a massage as a relaxation plan. For example, if the mother is in poor health, the suggestion unit may suggest yoga as a relaxation plan. For example, if the mother's health is deteriorating, the suggestion unit may suggest aromatherapy as a relaxation plan. This allows the system to provide a relaxation plan tailored to the mother's physical condition. Relaxation plans include, but are not limited to, massage, yoga, and aromatherapy. Some or all of the processing described above in the suggestion unit may be performed using, for example, AI, or not using AI. For example, the suggestion unit can input the mother's physical condition data into a generating AI and have the generating AI propose a relaxation plan.

[0036] The suggestion unit can propose a feeding schedule according to the newborn's care needs. For example, if the newborn has high feeding needs, the suggestion unit can propose frequent feedings as a feeding schedule. If the newborn has low feeding needs, the suggestion unit can also propose spaced-out feedings as a feeding schedule. If the newborn's feeding needs fluctuate, the suggestion unit can also propose flexible feedings as a feeding schedule. This allows for the provision of a feeding schedule that meets the newborn's care needs. The feeding schedule includes, but is not limited to, the frequency and timing of feedings. Some or all of the processing described above in the suggestion unit may be performed using AI, for example, or without AI. For example, the suggestion unit can input newborn feeding data into a generating AI and have the generating AI propose a feeding schedule.

[0037] The collaboration unit can provide services to support the mother's relaxation, such as hotel staff offering massages to support the mother's relaxation. The collaboration unit can also provide yoga to support the mother's relaxation, such as hotel staff offering aromatherapy. This allows the collaboration unit to provide services that support the mother's relaxation. Relaxation support services include, but are not limited to, massages, yoga, and aromatherapy. Some or all of the above processing in the collaboration unit may be performed using AI, for example, or without AI. For example, the collaboration unit can input the mother's relaxation data into a generating AI and have the generating AI perform the provision of relaxation services.

[0038] The collaboration unit can provide services to support hotel staff in caring for newborns. For example, the collaboration unit can provide breastfeeding support to support hotel staff in caring for newborns. The collaboration unit can also provide diaper changing support to support hotel staff in caring for newborns. The collaboration unit can also provide sleep support to support hotel staff in caring for newborns. This allows the collaboration unit to provide services to support newborn care. Services to support newborn care include, but are not limited to, breastfeeding support and sleep support. Some or all of the above processing in the collaboration unit may be performed using, for example, AI, or not using AI. For example, the collaboration unit can input newborn care data into a generating AI and have the generating AI perform the provision of care services.

[0039] The monitoring unit can analyze the mother's past health data and select the optimal monitoring method. For example, the monitoring unit can analyze from the mother's past health data whether abnormalities are likely to occur during certain time periods and focus monitoring during those times. For example, based on the mother's past health data, the monitoring unit can also focus monitoring on specific health indicators if abnormalities are found in those indicators. For example, the monitoring unit can analyze the mother's past health data and select the optimal monitoring equipment. This allows for more effective monitoring by selecting the optimal monitoring method based on the mother's past health data. The optimal monitoring method includes, but is not limited to, data type and collection frequency. Some or all of the above processing in the monitoring unit may be performed using AI, for example, or without AI. For example, the monitoring unit can input the mother's past health data into a generating AI and have the generating AI select the optimal monitoring method.

[0040] The monitoring unit can collect data based on the mother's lifestyle and stress level during monitoring. For example, the monitoring unit can collect health data in accordance with the timing of meals and exercise, taking into account the mother's lifestyle. The monitoring unit can also estimate the mother's stress level and collect data intensively during periods of high stress. The monitoring unit can also consider the mother's sleep patterns and collect data during sleep. This allows for more accurate monitoring by collecting data based on the mother's lifestyle and stress level. Lifestyle includes, but is not limited to, diet, exercise, and sleep. Stress level includes, but is not limited to, questionnaires and biofeedback. Some or all of the above processing in the monitoring unit may be performed using, for example, AI, or not using AI. For example, the monitoring unit can input the mother's lifestyle data into a generating AI and have the generating AI execute the timing of data collection.

[0041] The monitoring unit can prioritize the collection of highly relevant data while considering the mother's geographical location information during monitoring. For example, if the mother is out, the monitoring unit can prioritize the collection of health data related to the environment of her destination. For example, if the mother is at home, the monitoring unit can also prioritize the collection of health data related to the environment of her home. For example, if the mother is at a specific facility, the monitoring unit can also prioritize the collection of health data related to the environment of that facility. This enables more appropriate monitoring by prioritizing the collection of highly relevant data while considering the mother's geographical location information. Geographical location information includes, but is not limited to, GPS data and location information services. Some or all of the above processing in the monitoring unit may be performed using, for example, AI, or without AI. For example, the monitoring unit can input the mother's geographical location data into a generating AI and have the generating AI collect highly relevant data.

[0042] The monitoring unit can analyze the mother's social media activity and collect relevant health data during monitoring. For example, the monitoring unit can estimate stress and emotional changes from the mother's social media activity and collect relevant health data. The monitoring unit can also estimate changes in lifestyle from the mother's social media activity and collect relevant health data. The monitoring unit can also estimate health concerns from the mother's social media activity and collect relevant health data. This allows for more accurate monitoring by analyzing the mother's social media activity and collecting relevant health data. Social media activity includes, but is not limited to, posts and activity frequency. Some or all of the above processing in the monitoring unit may be performed using AI, for example, or without AI. For example, the monitoring unit can input the mother's social media data into a generating AI and have the generating AI collect health data.

[0043] The proposal unit can adjust the level of detail in the care plan based on the mother's health condition when making a proposal. For example, if the mother's health is good, the proposal unit will propose a detailed care plan. If the mother's health is unstable, the proposal unit may also propose a simple and easy-to-implement care plan. If the mother's health is deteriorating, the proposal unit may also propose a care plan that includes emergency response. By adjusting the level of detail in the care plan based on the mother's health condition, a more appropriate care plan can be provided. Level of detail includes, but is not limited to, the depth of information and the specificity of explanations. Some or all of the above processing in the proposal unit may be performed using AI, for example, or not using AI. For example, the proposal unit can input the mother's health data into a generating AI and have the generating AI adjust the level of detail in the care plan.

[0044] The proposal unit can apply different care plan algorithms depending on the mother's lifestyle when making a proposal. For example, if the mother's lifestyle is regular, the proposal unit will propose a care plan that is suited to that regular lifestyle. For example, if the mother's lifestyle is irregular, the proposal unit can also propose a care plan that is suited to that irregular lifestyle. For example, if the mother's lifestyle is changing, the proposal unit can also propose a care plan that is suited to that change. In this way, by applying different care plan algorithms depending on the mother's lifestyle, a more appropriate care plan can be provided. Lifestyle includes, but is not limited to, diet, exercise, and sleep. Care plan algorithms include, but are not limited to, rule-based and machine learning-based algorithms. Some or all of the above processing in the proposal unit may be performed using, for example, AI, or not using AI. For example, the proposal unit can input the mother's lifestyle data into a generating AI and have the generating AI execute the application of the care plan algorithm.

[0045] The proposal unit can determine the priority of care plans based on when the mother's health data was collected. For example, if the mother's health data has been recently collected, the proposal unit will propose an up-to-date care plan based on that data. For example, if the mother's health data is outdated, the proposal unit can prompt for data updates and then propose a care plan. For example, if the mother's health data is incomplete, the proposal unit can supplement the missing data and then propose a care plan. This allows for the provision of more appropriate care plans by determining the priority of care plans based on when the mother's health data was collected. Collection timing includes, but is not limited to, periodic collection and event-based collection. Prioritization includes, but is not limited to, data importance and urgency. Some or all of the above processing in the proposal unit may be performed using, for example, AI, or not using AI. For example, the proposal unit can input the mother's health data into a generating AI and have the generating AI determine the priority of care plans.

[0046] The proposal unit can adjust the order of care plans based on the relevance of the mother's health data when making a proposal. For example, if the mother's health data is highly relevant, the proposal unit will determine the order of care plans based on that data. For example, if the mother's health data is not highly relevant, the proposal unit can re-evaluate the relevance of the data and then determine the order of care plans. For example, if there is multiple data on the mother's health, the proposal unit can prioritize the most relevant data when determining the order of care plans. This allows for the provision of more appropriate care plans by adjusting the order of care plans based on the relevance of the mother's health data. Relevance includes, but is not limited to, data correlation and causal relationships. Order includes, but is not limited to, order by importance or chronological order. Some or all of the above processing in the proposal unit may be performed using, for example, AI, or not using AI. For example, the proposal unit can input the mother's health data into a generating AI and have the generating AI perform the adjustment of the care plan order.

[0047] The integration unit can analyze the mother's past service usage history and select the most suitable service when providing a service. For example, the integration unit can prioritize providing the mother's preferred services based on her past service usage history. The integration unit can also select the most suitable service based on the mother's past service usage history. For example, the integration unit can analyze the mother's past service usage history and suggest areas for service improvement. This allows for the provision of more appropriate services by analyzing the mother's past service usage history. Service usage history includes, but is not limited to, past usage frequency and content. The optimal service includes, but is not limited to, user satisfaction and effectiveness. Some or all of the above processing in the integration unit may be performed using, for example, AI, or not using AI. For example, the integration unit can input the mother's service usage history data into a generating AI and have the generating AI select the most suitable service.

[0048] The collaboration unit can customize the means of service based on the mother's current living situation when providing services. For example, the collaboration unit can consider the mother's current living situation and propose the most suitable means of service. The collaboration unit can also customize the method of service delivery based on the mother's current living situation. The collaboration unit can also analyze the mother's current living situation and propose areas for improvement in the service. This allows for the provision of more appropriate services by customizing the means of service based on the mother's current living situation. Living situation includes, but is not limited to, the home environment and work situation. Means of service include, but is not limited to, face-to-face services and online services. Some or all of the above processing in the collaboration unit may be performed using, for example, AI, or not using AI. For example, the collaboration unit can input the mother's living situation data into a generating AI and have the generating AI perform the customization of the means of service.

[0049] The collaboration unit can select the most suitable service when providing a service, taking into account the mother's geographical location information. For example, if the mother is out, the collaboration unit will provide a service that can be used while she is out. For example, if the mother is at home, the collaboration unit can also provide a service that can be used at home. For example, if the mother is at a specific facility, the collaboration unit can also provide a service that can be used at that facility. By selecting the most suitable service, taking into account the mother's geographical location information, a more appropriate service can be provided. Geographical location information includes, but is not limited to, GPS data and location information services. The optimal service includes, but is not limited to, user satisfaction and effectiveness. Some or all of the above processing in the collaboration unit may be performed using, for example, AI, or not using AI. For example, the collaboration unit can input the mother's geographical location data into a generating AI and have the generating AI select the most suitable service.

[0050] The collaboration unit can analyze the mother's social media activity and propose service options when providing a service. For example, the collaboration unit can estimate and propose preferred services based on the mother's social media activity. The collaboration unit can also estimate changes in lifestyle habits based on the mother's social media activity and propose services. The collaboration unit can also estimate health-related concerns based on the mother's social media activity and propose services. By analyzing the mother's social media activity and proposing service options, more appropriate services can be provided. Social media activity includes, but is not limited to, posts and activity frequency. Service options include, but are not limited to, in-person services and online services. Some or all of the above processing in the collaboration unit may be performed using, for example, AI, or not using AI. For example, the collaboration unit can input the mother's social media data into a generating AI and have the generating AI propose service options.

[0051] The system according to the embodiment is not limited to the example described above, and various modifications are possible, for example, as follows.

[0052] The care support system not only monitors the mother's health and the newborn's care needs, but also manages the mother's nutritional status. For example, the monitoring unit can record the mother's meals and analyze their nutritional balance. The suggestion unit can propose appropriate meal plans based on the mother's nutritional status. For instance, if the mother is iron deficient, the system can suggest a meal plan using iron-rich foods. Furthermore, the liaison unit can collaborate with hotel chefs to provide special menus tailored to the mother's nutritional needs. In this way, the care support system can optimally manage the mother's nutritional status and support her health.

[0053] The care support system not only monitors the care needs of newborns but also tracks their developmental progress. For example, the monitoring department can regularly record the newborn's height and weight gain and track their developmental progress. The proposal department can propose appropriate care plans based on the newborn's developmental status. For instance, if a newborn is not gaining weight, the proposal department can suggest reviewing feeding methods or introducing nutritional supplements. The liaison department can also suggest that hotel staff receive training to support newborn development and provide appropriate care. In this way, the care support system can support the healthy growth of newborns.

[0054] The care support system can not only monitor the mother's health and the newborn's care needs, but also provide support to improve the mother's sleep quality. For example, the monitoring unit can record the mother's sleep patterns and analyze the quality of her sleep. The suggestion unit can propose relaxation plans to improve the mother's sleep quality. For instance, if the mother is not getting enough sleep, it can suggest relaxation methods before bed and create a comfortable sleep environment. The liaison unit can also suggest that hotel staff receive training to support the mother's sleep and provide an environment where the mother can sleep comfortably. In this way, the care support system can improve the mother's sleep quality and support her health.

[0055] The care support system not only monitors the mother's health and the newborn's care needs, but can also support the mother's exercise habits. For example, the monitoring unit can record the mother's exercise volume and activity level and analyze her exercise habits. The suggestion unit can propose an appropriate exercise plan according to the mother's exercise habits. For example, if the mother is not getting enough exercise, it can suggest light stretching or walking. In addition, the coordination unit can suggest that hotel staff receive training to support the mother's exercise, providing an environment where the mother can continue exercising without strain. In this way, the care support system can support the mother's exercise habits and maintain her health.

[0056] The care support system can not only monitor the care needs of newborns but also provide stimulation tailored to their developmental stage. For example, the monitoring unit can record the newborn's developmental stage and collect data to provide appropriate stimulation. The suggestion unit can suggest appropriate play and learning activities according to the newborn's developmental stage. For example, if a newborn is in the stage of visual development, colorful toys and picture books can be suggested. The liaison unit can also suggest that hotel staff receive training to support newborn development and provide an environment where newborns can receive appropriate stimulation. In this way, the care support system can support the development of newborns and promote healthy growth.

[0057] The care support system can not only monitor the care needs of newborns but also provide support to improve their immunity. For example, the monitoring department can record the newborn's health status and collect data to improve their immunity. The proposal department can propose care plans to improve the newborn's immunity. For example, if a newborn is prone to catching colds, a meal plan using foods rich in vitamin C can be proposed. In addition, the liaison department can propose that hotel staff receive training to improve the newborn's immunity, providing an environment in which newborns can grow up healthy. In this way, the care support system can improve the newborn's immunity and support their health.

[0058] The following briefly describes the processing flow for example form 1.

[0059] Step 1: The monitoring unit monitors the mother's health and the newborn's care needs. For example, it collects health data such as the mother's body temperature, blood pressure, and heart rate, detects abnormalities, and suggests appropriate actions. It also collects care needs such as the newborn's weight, sleep patterns, and feeding status, detects abnormalities, and suggests appropriate actions. Step 2: The proposal department proposes individualized care plans based on the data collected by the monitoring department. For example, it proposes appropriate relaxation and nutritional management plans according to the mother's physical condition, and proposes an appropriate relaxation plan if the mother's condition deteriorates. It also proposes feeding schedules and measures to improve the sleep environment according to the newborn's care needs, and proposes appropriate measures to improve the sleep environment if the newborn's sleep pattern is disrupted. Step 3: The Liaison Department will work with hotel staff to provide services based on the care plan proposed by the Proposal Department. For example, hotel staff will offer massages and aromatherapy to support the mother's relaxation and propose an appropriate relaxation plan according to the mother's physical condition. Regarding newborn care, hotel staff will provide support with breastfeeding and diaper changes and propose an appropriate breastfeeding schedule according to the newborn's care needs.

[0060] (Example of form 2) The care support system according to an embodiment of the present invention is a system that supports hotels providing care for postpartum mothers and newborns. This care support system monitors the mother's health status and the newborn's care needs in real time and proposes an individualized care plan. Furthermore, the care support system works in cooperation with hotel staff to provide optimal services and support the mother's relaxation and recovery. For example, the care support system collects health data such as the mother's body temperature, blood pressure, and heart rate, as well as care needs such as the newborn's weight, sleep patterns, and breastfeeding status. For example, if the mother's body temperature rises, the care support system can detect the abnormality and propose an appropriate response. Next, the care support system proposes an individualized care plan based on the monitoring results. For example, it can propose an appropriate relaxation plan and nutritional management plan according to the mother's physical condition. It can also propose breastfeeding schedules and measures to improve the sleep environment according to the newborn's care needs. This allows for optimal management of the health of both the mother and the newborn. Furthermore, the care support system works in cooperation with hotel staff to provide optimal services. For example, based on the care plan proposed by the care support system, hotel staff can provide massages and aromatherapy to support the mother's relaxation. Furthermore, hotel staff can provide support for newborn care, including breastfeeding and diaper changes. This reduces the burden on mothers and supports relaxation and recovery. Thus, the care support system provides a safe and secure environment for postpartum mothers and newborns, supporting both the mother's recovery and the newborn's health. For example, a mother's ability to relax reduces stress and promotes recovery. Also, proper newborn care can lead to healthy growth. This encourages the use of postpartum care hotels, creating a society where more mothers and newborns can receive appropriate care. In short, the care support system provides a safe and secure environment for postpartum mothers and newborns, supporting both the mother's recovery and the newborn's health.

[0061] The care support system according to the embodiment comprises a monitoring unit, a suggestion unit, and a coordination unit. The monitoring unit monitors the mother's health status and the newborn's care needs. The monitoring unit collects health data such as the mother's body temperature, blood pressure, and heart rate. For example, if the mother's body temperature rises, the monitoring unit can detect an abnormality and suggest an appropriate response. The monitoring unit collects care needs such as the newborn's weight, sleep patterns, and feeding status. For example, if the newborn's weight decreases, the monitoring unit can detect an abnormality and suggest an appropriate response. The suggestion unit proposes an individualized care plan based on the data collected by the monitoring unit. For example, the suggestion unit proposes an appropriate relaxation plan and nutritional management plan according to the mother's physical condition. For example, if the mother's physical condition deteriorates, the suggestion unit can propose an appropriate relaxation plan. For example, if the suggestion unit proposes a feeding schedule and measures to improve the sleep environment according to the newborn's care needs. For example, if the newborn's sleep pattern is disrupted, the suggestion unit can propose appropriate measures to improve the sleep environment. The Collaboration Department provides services in cooperation with hotel staff based on the care plan proposed by the Proposal Department. For example, the Collaboration Department can provide massages and aromatherapy to support the mother's relaxation, provided by hotel staff. For example, the Collaboration Department can propose an appropriate relaxation plan according to the mother's physical condition. For example, the Collaboration Department can also provide support for newborn care, such as breastfeeding and diaper changing, provided by hotel staff. For example, the Collaboration Department can propose an appropriate breastfeeding schedule according to the newborn's care needs. As a result, the care support system according to the embodiment can monitor the mother's health condition and the newborn's care needs in real time, propose an individualized care plan, and provide optimal services in cooperation with hotel staff.

[0062] The monitoring unit monitors the mother's health and the newborn's care needs. Specifically, it utilizes wearable devices and smartphone apps to collect health data such as the mother's body temperature, blood pressure, and heart rate. These devices are worn on the mother's body, collecting data 24 hours a day and transmitting it to a cloud server. For example, if the mother's body temperature rises, the system detects the abnormality and issues an alert. Furthermore, fluctuations in blood pressure and heart rate are monitored in real time, and if an abnormality is detected, countermeasures are immediately suggested. Similarly, data on the newborn's care needs, such as weight, sleep patterns, and feeding status, are collected. The newborn's weight is measured regularly using a dedicated baby scale, and this data is automatically transmitted to the system. Sleep patterns are monitored using a baby monitor or smart bed, and feeding status is recorded by the mother entering it into a smartphone app. This allows the monitoring unit to comprehensively understand the health status of both the mother and the newborn and respond quickly if an abnormality occurs. In addition, the monitoring unit can analyze the collected data to understand long-term health trends. For example, by analyzing the fluctuation patterns of a mother's body temperature and blood pressure, it is possible to assess the influence of seasons and lifestyle habits and propose preventive care. Similarly, a newborn's weight and sleep patterns can be used as basic data to understand their growth progress and changes in their daily rhythms, and to provide appropriate care.

[0063] The proposal department proposes individualized care plans based on data collected by the monitoring department. Specifically, it proposes appropriate relaxation and nutritional management plans according to the mother's physical condition. For example, if the mother's body temperature is elevated and her stress levels are high, the proposal department may suggest yoga, meditation, or aromatherapy as a relaxation plan. It can also recommend a balanced diet and supplement intake as part of a nutritional management plan. Depending on the newborn's care needs, it can also propose improvements to the breastfeeding schedule and sleep environment. For example, if the newborn is losing weight, the proposal department may suggest increasing the frequency of breastfeeding or providing dietary guidance to improve breast milk quality. If the sleep pattern is disrupted, it may suggest creating an appropriate sleep environment and methods for getting the baby to sleep. The proposal department uses AI to analyze collected data and generate the optimal care plan. Based on analysis of past data and similar cases, the AI ​​can provide the most suitable suggestions for the individual situation. For example, if the mother's health deteriorates, it can refer to past data to suggest relaxation plans that have been effective for other mothers with similar symptoms. Furthermore, regarding the care needs of newborns, we can propose the most effective feeding schedules and measures to improve the sleep environment based on past data. This allows the proposal department to provide optimal care plans tailored to individual needs, supporting the health of both mother and newborn.

[0064] The Liaison Department will work with hotel staff to provide services based on the care plan proposed by the Proposal Department. Specifically, hotel staff will provide massages and aromatherapy to support the mother's relaxation. For example, depending on the mother's physical condition, massage sessions in the relaxation room or relaxation programs using aromatherapy oils can be implemented. This will allow the mother to relax and reduce stress. Hotel staff can also provide support for newborn care, such as breastfeeding and diaper changes. For example, they can inform mothers of feeding times and provide support based on the newborn's feeding schedule. Regarding diaper changes, they can change diapers at the appropriate time to maintain a clean environment. The Liaison Department will work closely with hotel staff to coordinate the implementation of the proposed care plan. For example, they will adjust the resources and schedules necessary for implementing the relaxation plan so that the mother can receive relaxation at the optimal time. Regarding newborn care, they will also share feeding and diaper change timings with hotel staff to ensure smooth care. Furthermore, the Liaison Department can collect feedback from mothers and newborns to continuously improve the quality of service. For example, the effectiveness of relaxation plans and satisfaction with breastfeeding support are evaluated, and plans are reviewed and improved as needed. This allows the liaison department to provide optimal care for mothers and newborns and strengthen collaboration with hotel staff.

[0065] The monitoring unit can collect health data such as the mother's body temperature, blood pressure, and heart rate. For example, the monitoring unit can measure the mother's body temperature and collect the data. The monitoring unit can also measure the mother's blood pressure and collect the data. The monitoring unit can also measure the mother's heart rate and collect the data. This allows for detailed monitoring of the mother's health status. Health data includes, but is not limited to, body temperature, blood pressure, and heart rate. Some or all of the above-described processes in the monitoring unit may be performed using, for example, AI, or without AI. For example, the monitoring unit can input the mother's body temperature data into a generating AI and have the generating AI perform a process to detect abnormalities in body temperature.

[0066] The monitoring unit can collect care needs such as the newborn's weight, sleep patterns, and feeding status. For example, the monitoring unit can measure the newborn's weight and collect data. The monitoring unit can also record the newborn's sleep patterns and collect data. The monitoring unit can also record the newborn's feeding status and collect data. This allows for detailed monitoring of the newborn's care needs. Care needs include, but are not limited to, weight, sleep patterns, and feeding status. Some or all of the above processing in the monitoring unit may be performed using, for example, AI, or not using AI. For example, the monitoring unit can input newborn weight data into a generating AI and cause the generating AI to perform a process to detect abnormalities in weight.

[0067] The suggestion unit can propose a relaxation plan according to the mother's physical condition. For example, if the mother is in good health, the suggestion unit may suggest a massage as a relaxation plan. For example, if the mother is in poor health, the suggestion unit may suggest yoga as a relaxation plan. For example, if the mother's health is deteriorating, the suggestion unit may suggest aromatherapy as a relaxation plan. This allows the system to provide a relaxation plan tailored to the mother's physical condition. Relaxation plans include, but are not limited to, massage, yoga, and aromatherapy. Some or all of the processing described above in the suggestion unit may be performed using, for example, AI, or not using AI. For example, the suggestion unit can input the mother's physical condition data into a generating AI and have the generating AI propose a relaxation plan.

[0068] The suggestion unit can propose a feeding schedule according to the newborn's care needs. For example, if the newborn has high feeding needs, the suggestion unit can propose frequent feedings as a feeding schedule. If the newborn has low feeding needs, the suggestion unit can also propose spaced-out feedings as a feeding schedule. If the newborn's feeding needs fluctuate, the suggestion unit can also propose flexible feedings as a feeding schedule. This allows for the provision of a feeding schedule that meets the newborn's care needs. The feeding schedule includes, but is not limited to, the frequency and timing of feedings. Some or all of the processing described above in the suggestion unit may be performed using AI, for example, or without AI. For example, the suggestion unit can input newborn feeding data into a generating AI and have the generating AI propose a feeding schedule.

[0069] The collaboration unit can provide services to support the mother's relaxation, such as hotel staff offering massages to support the mother's relaxation. The collaboration unit can also provide yoga to support the mother's relaxation, such as hotel staff offering aromatherapy. This allows the collaboration unit to provide services that support the mother's relaxation. Relaxation support services include, but are not limited to, massages, yoga, and aromatherapy. Some or all of the above processing in the collaboration unit may be performed using AI, for example, or without AI. For example, the collaboration unit can input the mother's relaxation data into a generating AI and have the generating AI perform the provision of relaxation services.

[0070] The collaboration unit can provide services to support hotel staff in caring for newborns. For example, the collaboration unit can provide breastfeeding support to support hotel staff in caring for newborns. The collaboration unit can also provide diaper changing support to support hotel staff in caring for newborns. The collaboration unit can also provide sleep support to support hotel staff in caring for newborns. This allows the collaboration unit to provide services to support newborn care. Services to support newborn care include, but are not limited to, breastfeeding support and sleep support. Some or all of the above processing in the collaboration unit may be performed using, for example, AI, or not using AI. For example, the collaboration unit can input newborn care data into a generating AI and have the generating AI perform the provision of care services.

[0071] The monitoring unit can estimate the mother's emotions and adjust the frequency of health data collection based on the estimated emotions. For example, if the mother is stressed, the monitoring unit can increase the frequency of health data collection to detect abnormalities early. For example, if the mother is relaxed, the monitoring unit can also reduce the frequency of health data collection to respect her privacy. For example, if the mother is tired, the monitoring unit can adjust the collection frequency to reduce her burden. This allows for more appropriate monitoring by adjusting the frequency of health data collection according to the mother's emotions. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or generative AI. Generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the monitoring unit may be performed using AI, for example, or without AI. For example, the monitoring unit can input the mother's emotion data into a generative AI and have the generative AI perform emotion estimation.

[0072] The monitoring unit can analyze the mother's past health data and select the optimal monitoring method. For example, the monitoring unit can analyze from the mother's past health data whether abnormalities are likely to occur during certain time periods and focus monitoring during those times. For example, based on the mother's past health data, the monitoring unit can also focus monitoring on specific health indicators if abnormalities are found in those indicators. For example, the monitoring unit can analyze the mother's past health data and select the optimal monitoring equipment. This allows for more effective monitoring by selecting the optimal monitoring method based on the mother's past health data. The optimal monitoring method includes, but is not limited to, data type and collection frequency. Some or all of the above processing in the monitoring unit may be performed using AI, for example, or without AI. For example, the monitoring unit can input the mother's past health data into a generating AI and have the generating AI select the optimal monitoring method.

[0073] The monitoring unit can collect data based on the mother's lifestyle and stress level during monitoring. For example, the monitoring unit can collect health data in accordance with the timing of meals and exercise, taking into account the mother's lifestyle. The monitoring unit can also estimate the mother's stress level and collect data intensively during periods of high stress. The monitoring unit can also consider the mother's sleep patterns and collect data during sleep. This allows for more accurate monitoring by collecting data based on the mother's lifestyle and stress level. Lifestyle includes, but is not limited to, diet, exercise, and sleep. Stress level includes, but is not limited to, questionnaires and biofeedback. Some or all of the above processing in the monitoring unit may be performed using, for example, AI, or not using AI. For example, the monitoring unit can input the mother's lifestyle data into a generating AI and have the generating AI execute the timing of data collection.

[0074] The monitoring unit can estimate the mother's emotions and determine the priority of health data to collect based on the estimated emotions. For example, if the mother is stressed, the monitoring unit will prioritize collecting stress-related health data. For example, if the mother is relaxed, the monitoring unit may also prioritize collecting general health data. For example, if the mother is tired, the monitoring unit may also prioritize collecting fatigue-related health data. This allows for the priority collection of more important data by determining the priority of health data to collect according to the mother's emotions. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or generative AI. Generative AI may be, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the monitoring unit may be performed using AI, for example, or not using AI. For example, the monitoring unit can input the mother's emotion data into a generative AI and have the generative AI determine the priority of health data.

[0075] The monitoring unit can prioritize the collection of highly relevant data while considering the mother's geographical location information during monitoring. For example, if the mother is out, the monitoring unit can prioritize the collection of health data related to the environment of her destination. For example, if the mother is at home, the monitoring unit can also prioritize the collection of health data related to the environment of her home. For example, if the mother is at a specific facility, the monitoring unit can also prioritize the collection of health data related to the environment of that facility. This enables more appropriate monitoring by prioritizing the collection of highly relevant data while considering the mother's geographical location information. Geographical location information includes, but is not limited to, GPS data and location information services. Some or all of the above processing in the monitoring unit may be performed using, for example, AI, or without AI. For example, the monitoring unit can input the mother's geographical location data into a generating AI and have the generating AI collect highly relevant data.

[0076] The monitoring unit can analyze the mother's social media activity and collect relevant health data during monitoring. For example, the monitoring unit can estimate stress and emotional changes from the mother's social media activity and collect relevant health data. The monitoring unit can also estimate changes in lifestyle from the mother's social media activity and collect relevant health data. The monitoring unit can also estimate health concerns from the mother's social media activity and collect relevant health data. This allows for more accurate monitoring by analyzing the mother's social media activity and collecting relevant health data. Social media activity includes, but is not limited to, posts and activity frequency. Some or all of the above processing in the monitoring unit may be performed using AI, for example, or without AI. For example, the monitoring unit can input the mother's social media data into a generating AI and have the generating AI collect health data.

[0077] The suggestion unit can estimate the mother's emotions and adjust the way the care plan is presented based on the estimated emotions. For example, if the mother is stressed, the suggestion unit will propose a simple and easy-to-understand care plan. If the mother is relaxed, the suggestion unit may also propose a detailed care plan. If the mother is tired, the suggestion unit may also propose a less burdensome care plan. By adjusting the way the care plan is presented according to the mother's emotions, a more appropriate care plan can be provided. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or generative AI. Generative AI may be, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the suggestion unit may be performed using AI or not. For example, the suggestion unit can input the mother's emotion data into the generative AI and have the generative AI adjust the way the care plan is presented.

[0078] The proposal unit can adjust the level of detail in the care plan based on the mother's health condition when making a proposal. For example, if the mother's health is good, the proposal unit will propose a detailed care plan. If the mother's health is unstable, the proposal unit may also propose a simple and easy-to-implement care plan. If the mother's health is deteriorating, the proposal unit may also propose a care plan that includes emergency response. By adjusting the level of detail in the care plan based on the mother's health condition, a more appropriate care plan can be provided. Level of detail includes, but is not limited to, the depth of information and the specificity of explanations. Some or all of the above processing in the proposal unit may be performed using AI, for example, or not using AI. For example, the proposal unit can input the mother's health data into a generating AI and have the generating AI adjust the level of detail in the care plan.

[0079] The proposal unit can apply different care plan algorithms depending on the mother's lifestyle when making a proposal. For example, if the mother's lifestyle is regular, the proposal unit will propose a care plan that is suited to that regular lifestyle. For example, if the mother's lifestyle is irregular, the proposal unit can also propose a care plan that is suited to that irregular lifestyle. For example, if the mother's lifestyle is changing, the proposal unit can also propose a care plan that is suited to that change. In this way, by applying different care plan algorithms depending on the mother's lifestyle, a more appropriate care plan can be provided. Lifestyle includes, but is not limited to, diet, exercise, and sleep. Care plan algorithms include, but are not limited to, rule-based and machine learning-based algorithms. Some or all of the above processing in the proposal unit may be performed using, for example, AI, or not using AI. For example, the proposal unit can input the mother's lifestyle data into a generating AI and have the generating AI execute the application of the care plan algorithm.

[0080] The suggestion unit can estimate the mother's emotions and adjust the length of the care plan based on the estimated emotions. For example, if the mother is stressed, the suggestion unit can suggest a short, concise care plan. If the mother is relaxed, the suggestion unit can suggest a longer care plan with more detailed explanations. If the mother is tired, the suggestion unit can suggest a shorter, less burdensome care plan. By adjusting the length of the care plan according to the mother's emotions, a more appropriate care plan can be provided. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or generative AI. Generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the processing described above in the suggestion unit may be performed using AI or not. For example, the suggestion unit can input the mother's emotion data into a generative AI and have the generative AI adjust the length of the care plan.

[0081] The proposal unit can determine the priority of care plans based on when the mother's health data was collected. For example, if the mother's health data has been recently collected, the proposal unit will propose an up-to-date care plan based on that data. For example, if the mother's health data is outdated, the proposal unit can prompt for data updates and then propose a care plan. For example, if the mother's health data is incomplete, the proposal unit can supplement the missing data and then propose a care plan. This allows for the provision of more appropriate care plans by determining the priority of care plans based on when the mother's health data was collected. Collection timing includes, but is not limited to, periodic collection and event-based collection. Prioritization includes, but is not limited to, data importance and urgency. Some or all of the above processing in the proposal unit may be performed using, for example, AI, or not using AI. For example, the proposal unit can input the mother's health data into a generating AI and have the generating AI determine the priority of care plans.

[0082] The proposal unit can adjust the order of care plans based on the relevance of the mother's health data when making a proposal. For example, if the mother's health data is highly relevant, the proposal unit will determine the order of care plans based on that data. For example, if the mother's health data is not highly relevant, the proposal unit can re-evaluate the relevance of the data and then determine the order of care plans. For example, if there is multiple data on the mother's health, the proposal unit can prioritize the most relevant data when determining the order of care plans. This allows for the provision of more appropriate care plans by adjusting the order of care plans based on the relevance of the mother's health data. Relevance includes, but is not limited to, data correlation and causal relationships. Order includes, but is not limited to, order by importance or chronological order. Some or all of the above processing in the proposal unit may be performed using, for example, AI, or not using AI. For example, the proposal unit can input the mother's health data into a generating AI and have the generating AI perform the adjustment of the care plan order.

[0083] The collaboration unit can estimate the mother's emotions and adjust the service delivery method based on the estimated emotions. For example, if the mother is stressed, the collaboration unit can prioritize providing relaxing services. If the mother is relaxed, the collaboration unit can also provide more detailed services. If the mother is tired, the collaboration unit can also provide less burdensome services. In this way, by adjusting the service delivery method according to the mother's emotions, more appropriate services can be provided. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or generative AI. The generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the collaboration unit may be performed using AI, for example, or not using AI. For example, the collaboration unit can input the mother's emotion data into the generative AI and have the generative AI adjust the service delivery method.

[0084] The integration unit can analyze the mother's past service usage history and select the most suitable service when providing a service. For example, the integration unit can prioritize providing the mother's preferred services based on her past service usage history. The integration unit can also select the most suitable service based on the mother's past service usage history. For example, the integration unit can analyze the mother's past service usage history and suggest areas for service improvement. This allows for the provision of more appropriate services by analyzing the mother's past service usage history. Service usage history includes, but is not limited to, past usage frequency and content. The optimal service includes, but is not limited to, user satisfaction and effectiveness. Some or all of the above processing in the integration unit may be performed using, for example, AI, or not using AI. For example, the integration unit can input the mother's service usage history data into a generating AI and have the generating AI select the most suitable service.

[0085] The collaboration unit can customize the means of service based on the mother's current living situation when providing services. For example, the collaboration unit can consider the mother's current living situation and propose the most suitable means of service. The collaboration unit can also customize the method of service delivery based on the mother's current living situation. The collaboration unit can also analyze the mother's current living situation and propose areas for improvement in the service. This allows for the provision of more appropriate services by customizing the means of service based on the mother's current living situation. Living situation includes, but is not limited to, the home environment and work situation. Means of service include, but is not limited to, face-to-face services and online services. Some or all of the above processing in the collaboration unit may be performed using, for example, AI, or not using AI. For example, the collaboration unit can input the mother's living situation data into a generating AI and have the generating AI perform the customization of the means of service.

[0086] The collaboration unit can estimate the mother's emotions and determine the priority of service provision based on the estimated emotions. For example, if the mother is stressed, the collaboration unit will prioritize providing relaxing services. For example, if the mother is relaxed, the collaboration unit can also provide more detailed services. For example, if the mother is tired, the collaboration unit can also provide less burdensome services. In this way, by determining the priority of service provision according to the mother's emotions, more appropriate services can be provided. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or generative AI. Generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the collaboration unit may be performed using AI, for example, or not using AI. For example, the collaboration unit can input the mother's emotion data into the generative AI and have the generative AI perform the determination of service provision priorities.

[0087] The collaboration unit can select the most suitable service when providing a service, taking into account the mother's geographical location information. For example, if the mother is out, the collaboration unit will provide a service that can be used while she is out. For example, if the mother is at home, the collaboration unit can also provide a service that can be used at home. For example, if the mother is at a specific facility, the collaboration unit can also provide a service that can be used at that facility. By selecting the most suitable service, taking into account the mother's geographical location information, a more appropriate service can be provided. Geographical location information includes, but is not limited to, GPS data and location information services. The optimal service includes, but is not limited to, user satisfaction and effectiveness. Some or all of the above processing in the collaboration unit may be performed using, for example, AI, or not using AI. For example, the collaboration unit can input the mother's geographical location data into a generating AI and have the generating AI select the most suitable service.

[0088] The collaboration unit can analyze the mother's social media activity and propose service options when providing a service. For example, the collaboration unit can estimate and propose preferred services based on the mother's social media activity. The collaboration unit can also estimate changes in lifestyle habits based on the mother's social media activity and propose services. The collaboration unit can also estimate health-related concerns based on the mother's social media activity and propose services. By analyzing the mother's social media activity and proposing service options, more appropriate services can be provided. Social media activity includes, but is not limited to, posts and activity frequency. Service options include, but are not limited to, in-person services and online services. Some or all of the above processing in the collaboration unit may be performed using, for example, AI, or not using AI. For example, the collaboration unit can input the mother's social media data into a generating AI and have the generating AI propose service options.

[0089] The system according to the embodiment is not limited to the example described above, and various modifications are possible, for example, as follows.

[0090] The care support system can not only monitor the mother's health and the newborn's care needs, but also provide psychological support. For example, the monitoring department can measure the mother's stress level and, if stress levels are high, can provide relaxation music or meditation guidance. The suggestion department can also suggest counseling sessions or participation in support groups, depending on the mother's psychological state. Furthermore, the liaison department can suggest that hotel staff receive training to provide psychological support to mothers, creating an environment where mothers can feel at ease. In this way, the care support system can support not only the mother's physical health but also her psychological health.

[0091] The care support system not only monitors the mother's health and the newborn's care needs, but also manages the mother's nutritional status. For example, the monitoring unit can record the mother's meals and analyze their nutritional balance. The suggestion unit can propose appropriate meal plans based on the mother's nutritional status. For instance, if the mother is iron deficient, the system can suggest a meal plan using iron-rich foods. Furthermore, the liaison unit can collaborate with hotel chefs to provide special menus tailored to the mother's nutritional needs. In this way, the care support system can optimally manage the mother's nutritional status and support her health.

[0092] The care support system not only monitors the care needs of newborns but also tracks their developmental progress. For example, the monitoring department can regularly record the newborn's height and weight gain and track their developmental progress. The proposal department can propose appropriate care plans based on the newborn's developmental status. For instance, if a newborn is not gaining weight, the proposal department can suggest reviewing feeding methods or introducing nutritional supplements. The liaison department can also suggest that hotel staff receive training to support newborn development and provide appropriate care. In this way, the care support system can support the healthy growth of newborns.

[0093] The care support system can not only monitor the mother's health and the newborn's care needs, but also provide support to improve the mother's sleep quality. For example, the monitoring unit can record the mother's sleep patterns and analyze the quality of her sleep. The suggestion unit can propose relaxation plans to improve the mother's sleep quality. For instance, if the mother is not getting enough sleep, it can suggest relaxation methods before bed and create a comfortable sleep environment. The liaison unit can also suggest that hotel staff receive training to support the mother's sleep and provide an environment where the mother can sleep comfortably. In this way, the care support system can improve the mother's sleep quality and support her health.

[0094] The care support system not only monitors the care needs of newborns but also estimates their emotional state and provides appropriate care. For example, the monitoring unit can analyze the newborn's cries and facial expressions to estimate their emotional state. The proposal unit can propose an appropriate care plan based on the newborn's emotional state. For example, if the newborn is feeling anxious, the proposal unit can suggest holding or using a pacifier to provide reassurance. The coordination unit can also suggest that hotel staff receive training to understand the newborn's emotional state and provide appropriate care, thereby creating an environment where the newborn can feel safe and secure. In this way, the care support system can provide care that takes the newborn's emotional state into consideration and support their healthy growth.

[0095] The care support system not only monitors the mother's health and the newborn's care needs, but can also support the mother's exercise habits. For example, the monitoring unit can record the mother's exercise volume and activity level and analyze her exercise habits. The suggestion unit can propose an appropriate exercise plan according to the mother's exercise habits. For example, if the mother is not getting enough exercise, it can suggest light stretching or walking. In addition, the coordination unit can suggest that hotel staff receive training to support the mother's exercise, providing an environment where the mother can continue exercising without strain. In this way, the care support system can support the mother's exercise habits and maintain her health.

[0096] The care support system can not only monitor the care needs of newborns but also provide stimulation tailored to their developmental stage. For example, the monitoring unit can record the newborn's developmental stage and collect data to provide appropriate stimulation. The suggestion unit can suggest appropriate play and learning activities according to the newborn's developmental stage. For example, if a newborn is in the stage of visual development, colorful toys and picture books can be suggested. The liaison unit can also suggest that hotel staff receive training to support newborn development and provide an environment where newborns can receive appropriate stimulation. In this way, the care support system can support the development of newborns and promote healthy growth.

[0097] The care support system can not only monitor the mother's health and the newborn's care needs, but also provide social support for the mother. For example, the monitoring department can record the mother's social connections and offer support if she feels isolated. The suggestion department can suggest participation in local support groups or online communities according to the mother's social support needs. The liaison department can also suggest that hotel staff receive training to provide social support to mothers, creating a safe and secure environment for them. In this way, the care support system can provide social support for mothers and reduce feelings of isolation.

[0098] The care support system can not only monitor the care needs of newborns but also provide support to improve their immunity. For example, the monitoring department can record the newborn's health status and collect data to improve their immunity. The proposal department can propose care plans to improve the newborn's immunity. For example, if a newborn is prone to catching colds, a meal plan using foods rich in vitamin C can be proposed. In addition, the liaison department can propose that hotel staff receive training to improve the newborn's immunity, providing an environment in which newborns can grow up healthy. In this way, the care support system can improve the newborn's immunity and support their health.

[0099] The care support system not only monitors the mother's health and the newborn's care needs, but can also estimate the mother's emotional state and provide emotion-based care. For example, the monitoring unit can analyze the mother's facial expressions and tone of voice to estimate her emotional state. The proposal unit can propose an appropriate care plan according to the mother's emotional state. For example, if the mother is feeling anxious, aromatherapy or counseling for relaxation can be suggested. The liaison unit can also suggest that hotel staff receive training to understand the mother's emotional state and provide appropriate care, thereby creating an environment where the mother can feel at ease. In this way, the care support system can provide care that takes the mother's emotional state into consideration and support her psychological well-being.

[0100] The following briefly describes the processing flow for example form 2.

[0101] Step 1: The monitoring unit monitors the mother's health and the newborn's care needs. For example, it collects health data such as the mother's body temperature, blood pressure, and heart rate, detects abnormalities, and suggests appropriate actions. It also collects care needs such as the newborn's weight, sleep patterns, and feeding status, detects abnormalities, and suggests appropriate actions. Step 2: The proposal department proposes individualized care plans based on the data collected by the monitoring department. For example, it proposes appropriate relaxation and nutritional management plans according to the mother's physical condition, and proposes an appropriate relaxation plan if the mother's condition deteriorates. It also proposes feeding schedules and measures to improve the sleep environment according to the newborn's care needs, and proposes appropriate measures to improve the sleep environment if the newborn's sleep pattern is disrupted. Step 3: The Liaison Department will work with hotel staff to provide services based on the care plan proposed by the Proposal Department. For example, hotel staff will offer massages and aromatherapy to support the mother's relaxation and propose an appropriate relaxation plan according to the mother's physical condition. Regarding newborn care, hotel staff will provide support with breastfeeding and diaper changes and propose an appropriate breastfeeding schedule according to the newborn's care needs.

[0102] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0103] Data generation model 58 is a form of so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> Examples of generative AI include text generation AI, image generation AI, and multimodal generation AI. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats from audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVMs), k-means clustering, convolutional neural networks (CNNs), recurrent neural networks (RNNs), generative adversarial networks (GANs), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each of the above parts is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example.Furthermore, processing performed by AI, including generative AI, may be replaced with rule-based processing, and rule-based processing may be replaced with processing performed by AI, including generative AI.

[0104] Furthermore, the processing performed by the data processing system 10 described above is carried out by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart device 14, but it may also be carried out by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart device 14. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart device 14 or an external device, and the smart device 14 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0105] Each of the multiple elements described above, including the monitoring unit, proposal unit, and collaboration unit, is implemented, for example, by at least one of the smart device 14 and the data processing unit 12. For example, the monitoring unit uses the camera 42 and microphone 38B of the smart device 14 to collect information on the mother's health status and the newborn's care needs, and the control unit 46A detects any abnormalities. The proposal unit is implemented by the identification processing unit 290 of the data processing unit 12 and generates an individualized care plan based on the collected data. The collaboration unit is implemented by the control unit 46A of the smart device 14 and provides services in cooperation with hotel staff based on the proposed care plan. The correspondence between each unit and the device or control unit is not limited to the example described above and can be modified in various ways.

[0106] [Second Embodiment] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0107] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0108] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN and / or LAN.

[0109] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0110] The microphone 238 receives voice signals from the user and accepts instructions from the user. The microphone 238 captures the voice signals from the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0111] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, which captures images of the area around the user (for example, an imaging range defined by a field of view equivalent to the field of vision of a typical healthy person).

[0112] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0113] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing by the processor 28. The storage 32 stores the specific processing program 56.

[0114] The processor 28 reads a specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 acting as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0115] Storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0116] In the smart glasses 214, specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 acting as a control unit 46A according to the specific processing program 60 executed on the RAM 48. The smart glasses 214 also have a data generation model 58 and an emotion identification model 59, similar to the data generation model and emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0117] Furthermore, other devices besides the data processing device 12 may also have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 obtains processing results (such as prediction results) using the data generation model 58 by communicating with the server device that has the data generation model 58. Also, the data processing device 12 may be a server device or a terminal device owned by the user (for example, a mobile phone, robot, home appliance, etc.).

[0118] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0119] The data generation model 58 is a so-called generative AI. An example of a data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats such as audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVM), k-means clustering, convolutional neural networks (CNN), recurrent neural networks (RNN), generative adversarial networks (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each part described above is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example. Also, processing performed by an AI including a generative AI may be replaced by rule-based processing, and rule-based processing may be replaced by processing performed by an AI including a generative AI.

[0120] The data processing system 210 according to the second embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 210 is performed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart glasses 214, but it may also be performed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart glasses 214. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart glasses 214 or an external device, and the smart glasses 214 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0121] Each of the multiple elements described above, including the monitoring unit, proposal unit, and collaboration unit, is implemented in at least one of the smart glasses 214 and the data processing unit 12. For example, the monitoring unit uses the camera 42 and microphone 238 of the smart glasses 214 to collect information on the mother's health status and the newborn's care needs, and the control unit 46A detects any abnormalities. The proposal unit is implemented by the identification processing unit 290 of the data processing unit 12 and generates an individualized care plan based on the collected data. The collaboration unit is implemented by the control unit 46A of the smart glasses 214 and provides services in cooperation with hotel staff based on the proposed care plan. The correspondence between each unit and the devices and control units is not limited to the example described above and can be modified in various ways.

[0122] [Third Embodiment] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0123] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0124] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN and / or LAN.

[0125] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0126] The microphone 238 receives voice signals from the user and accepts instructions from the user. The microphone 238 captures the voice signals from the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0127] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, which captures images of the area around the user (for example, an imaging range defined by a field of view equivalent to the field of vision of a typical healthy person).

[0128] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0129] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0130] The processor 28 reads a specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 acting as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0131] Storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0132] In the headset terminal 314, specific processing is performed by the processor 46. The storage 50 stores a specific program 60. The processor 46 reads the specific program 60 from the storage 50 and executes the read specific program 60 on the RAM 48. The specific processing is realized by the processor 46 acting as a control unit 46A according to the specific program 60 executed on the RAM 48. The headset terminal 314 also has a data generation model 58 and an emotion identification model 59, similar to the data generation model and emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0133] Furthermore, other devices besides the data processing device 12 may also have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 obtains processing results (such as prediction results) using the data generation model 58 by communicating with the server device that has the data generation model 58. Also, the data processing device 12 may be a server device or a terminal device owned by the user (for example, a mobile phone, robot, home appliance, etc.).

[0134] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0135] The data generation model 58 is a so-called generative AI. An example of a data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats such as audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVM), k-means clustering, convolutional neural networks (CNN), recurrent neural networks (RNN), generative adversarial networks (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each part described above is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example. Also, processing performed by an AI including a generative AI may be replaced by rule-based processing, and rule-based processing may be replaced by processing performed by an AI including a generative AI.

[0136] The data processing system 310 according to the third embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 310 is performed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the headset terminal 314, but may also be performed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the headset terminal 314. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the headset terminal 314 or an external device, and the headset terminal 314 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0137] Each of the multiple elements described above, including the monitoring unit, proposal unit, and collaboration unit, is implemented in at least one of the headset terminal 314 and the data processing unit 12. For example, the monitoring unit uses the camera 42 and microphone 238 of the headset terminal 314 to collect information on the mother's health status and the newborn's care needs, and the control unit 46A detects any abnormalities. The proposal unit is implemented by the specific processing unit 290 of the data processing unit 12 and generates an individualized care plan based on the collected data. The collaboration unit is implemented by the control unit 46A of the headset terminal 314 and provides services in cooperation with hotel staff based on the proposed care plan. The correspondence between each unit and the devices and control units is not limited to the example described above and can be modified in various ways.

[0138] [Fourth Embodiment] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0139] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0140] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN and / or LAN.

[0141] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0142] The microphone 238 receives voice signals from the user and accepts instructions from the user. The microphone 238 captures the voice signals from the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0143] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS image sensor or CCD image sensor, which captures images of the area around the user (for example, an imaging range defined by a field of view equivalent to the field of vision of a typical healthy person).

[0144] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0145] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. The robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0146] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0147] The processor 28 reads a specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 acting as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0148] Storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0149] In robot 414, specific processing is performed by processor 46. A specific program 60 is stored in storage 50. Processor 46 reads the specific program 60 from storage 50 and executes it on RAM 48. The specific processing is achieved by processor 46 acting as a control unit 46A according to the specific program 60 executed on RAM 48. Robot 414 also has data generation model 58 and emotion identification model 59, similar to those of the robot, and can perform processing similar to that of the specific processing unit 290 using these models.

[0150] Furthermore, other devices besides the data processing device 12 may also have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 obtains processing results (such as prediction results) using the data generation model 58 by communicating with the server device that has the data generation model 58. Also, the data processing device 12 may be a server device or a terminal device owned by the user (for example, a mobile phone, robot, home appliance, etc.).

[0151] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

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

[0153] The data processing system 410 according to the fourth embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 410 is performed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the robot 414, but it may also be performed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the robot 414. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the robot 414 or an external device, and the robot 414 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0154] Each of the multiple elements described above, including the monitoring unit, proposal unit, and collaboration unit, is implemented in at least one of the following: the robot 414 and the data processing unit 12. For example, the monitoring unit uses the camera 42 and microphone 238 of the robot 414 to collect information on the mother's health status and the newborn's care needs, and the control unit 46A detects any abnormalities. The proposal unit is implemented by the identification processing unit 290 of the data processing unit 12 and generates an individualized care plan based on the collected data. The collaboration unit is implemented by the control unit 46A of the robot 414 and provides services in cooperation with hotel staff based on the proposed care plan. The correspondence between each unit and the devices and control units is not limited to the example described above and can be modified in various ways.

[0155] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0156] Figure 9 shows the emotion map 400, in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0157] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0158] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0159] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, and motorcycles, emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated based, for example, on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0160] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0161] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0162] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing method for the specific process may be used, which includes computer 22 and multiple other computers.

[0163] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0164] 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.

[0165] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0166] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0167] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0168] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0169] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0170] Furthermore, although the above-described examples were divided into four embodiments, some or all of these embodiments may be combined. Also, the smart device 14, smart glasses 214, headset terminal 314, and robot 414 are just examples, and they may be combined, or other devices may be used. Also, although the above-described examples were divided into two embodiments, Embodiment 1 and Embodiment 2, these may be combined.

[0171] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and other things that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0172] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0173] (Note 1) The monitoring department monitors the mother's health status and the newborn's care needs, A proposal unit proposes individual care plans based on the data collected by the monitoring unit, The system includes a coordination unit that provides services in cooperation with hotel staff based on the care plan proposed by the aforementioned proposal unit. A system characterized by the following features. (Note 2) The monitoring unit, Collect health data such as the mother's body temperature, blood pressure, and heart rate. The system described in Appendix 1, characterized by the features described herein. (Note 3) The monitoring unit, Collect care needs such as the newborn's weight, sleep patterns, and feeding status. The system described in Appendix 1, characterized by the features described herein. (Note 4) The aforementioned proposal section is, We propose a relaxation plan tailored to the mother's physical condition. The system described in Appendix 1, characterized by the features described herein. (Note 5) The aforementioned proposal section is, We propose a feeding schedule tailored to the newborn's care needs. The system described in Appendix 1, characterized by the features described herein. (Note 6) The aforementioned linkage unit is, Hotel staff provide a service to support the mother's relaxation. The system described in Appendix 1, characterized by the features described herein. (Note 7) The aforementioned linkage unit is, Hotel staff provide support services for newborn care. The system described in Appendix 1, characterized by the features described herein. (Note 8) The monitoring unit, The system estimates the mother's emotions and adjusts the frequency of health data collection based on the estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 9) The monitoring unit, Analyze the mother's past health data to select the optimal monitoring method. The system described in Appendix 1, characterized by the features described herein. (Note 10) The monitoring unit, During monitoring, data is collected based on the mother's lifestyle and stress levels. The system described in Appendix 1, characterized by the features described herein. (Note 11) The monitoring unit, The system estimates the mother's emotions and prioritizes the health data to collect based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 12) The monitoring unit, During monitoring, the system prioritizes collecting highly relevant data, taking into account the mother's geographical location. The system described in Appendix 1, characterized by the features described herein. (Note 13) The monitoring unit, During monitoring, the mother's social media activity is analyzed and relevant health data is collected. The system described in Appendix 1, characterized by the features described herein. (Note 14) The aforementioned proposal section is, We estimate the mother's emotions and adjust the way the care plan is expressed based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 15) The aforementioned proposal section is, When making a proposal, adjust the level of detail in the care plan based on the mother's health condition. The system described in Appendix 1, characterized by the features described herein. (Note 16) The aforementioned proposal section is, When making a proposal, different care plan algorithms are applied depending on the mother's lifestyle. The system described in Appendix 1, characterized by the features described herein. (Note 17) The aforementioned proposal section is, Estimate the mother's emotions and adjust the length of the care plan based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 18) The aforementioned proposal section is, When making a proposal, prioritize the care plan based on when the mother's health data was collected. The system described in Appendix 1, characterized by the features described herein. (Note 19) The aforementioned proposal section is, When making a proposal, adjust the order of care plans based on the relevance of the mother's health data. The system described in Appendix 1, characterized by the features described herein. (Note 20) The aforementioned linkage unit is, We estimate the mother's emotions and adjust the service delivery method based on the estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 21) The aforementioned linkage unit is, When providing services, the mother's past service usage history is analyzed to select the most suitable service. The system described in Appendix 1, characterized by the features described herein. (Note 22) The aforementioned linkage unit is, When providing services, the means of service will be customized based on the mother's current living situation. The system described in Appendix 1, characterized by the features described herein. (Note 23) The aforementioned linkage unit is, The system estimates the mother's emotions and determines the priority of service provision based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 24) The aforementioned linkage unit is, When providing services, the most suitable service will be selected considering the mother's geographical location. The system described in Appendix 1, characterized by the features described herein. (Note 25) The aforementioned linkage unit is, When providing the service, we analyze the mother's social media activity and suggest appropriate service methods. The system described in Appendix 1, characterized by the features described herein. [Explanation of Symbols]

[0174] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots

Claims

1. The monitoring department monitors the mother's health status and the newborn's care needs, A proposal unit proposes individual care plans based on the data collected by the monitoring unit, The system includes a coordination unit that provides services in cooperation with hotel staff based on the care plan proposed by the aforementioned proposal unit. A system characterized by the following features.

2. The monitoring unit, Collect health data such as the mother's body temperature, blood pressure, and heart rate. The system according to feature 1.

3. The monitoring unit, Collect care needs such as the newborn's weight, sleep patterns, and feeding status. The system according to feature 1.

4. The aforementioned proposal section is, We propose a relaxation plan tailored to the mother's physical condition. The system according to feature 1.

5. The aforementioned proposal section is, We propose a feeding schedule tailored to the newborn's care needs. The system according to feature 1.

6. The aforementioned linkage unit is, Hotel staff provide a service to support the mother's relaxation. The system according to feature 1.

7. The aforementioned linkage unit is, Hotel staff provide support services for newborn care. The system according to feature 1.

8. The monitoring unit, The system estimates the mother's emotions and adjusts the frequency of health data collection based on the estimated emotions. The system according to feature 1.

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