System

Abstract

An object of the system according to the embodiment is to constantly monitor the health condition of an elderly or weak pet and detect an abnormality at an early stage.SOLUTION: A system according to an embodiment includes a watching camera, a recording unit, a detection unit, and a notification unit. The watching camera constantly observes the state of the pet. The recorder records a state of sleep and excretion of the pet observed by the watching camera. The detector detects an abnormality of the pet based on the data recorded by the recorder. The notifier notifies the owner, the Pet hotel, and the veterinary hospital staff of the abnormality detected by the detector.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Conventional technology has the problem that it is difficult to constantly monitor the health of elderly or frail pets and detect abnormalities early.

[0005] The system according to the embodiment aims to constantly monitor the health of elderly or frail pets and detect any abnormalities at an early stage. [Means for solving the problem]

[0006] The system according to the embodiment includes a monitoring camera, a recording unit, a detection unit, and a notification unit. The monitoring camera constantly monitors the behavior of the pet. The recording unit records the pet's sleep and excretion observed by the monitoring camera. The detection unit detects abnormalities in the pet based on the data recorded by the recording unit. The notification unit notifies the owner, pet hotel, or veterinary clinic staff of any abnormalities detected by the detection unit. [Effects of the Invention]

[0007] The system according to the embodiment can constantly monitor the health of elderly or frail pets and detect abnormalities at an early stage. [Brief explanation of the drawings]

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

[0028] (Example 1) The surveillance camera system according to the embodiment of the present invention is a system that constantly monitors the state of a pet, and the AI ​​that generates it detects and notifies the user of any abnormalities. This allows the surveillance camera system to constantly monitor the health of a pet and quickly notify the user if an abnormality occurs.

[0029] A surveillance camera system according to an embodiment includes a surveillance camera, a recording unit, a detection unit, and a notification unit. The surveillance camera constantly monitors the behavior of a pet. For example, the surveillance camera can clearly capture the pet's movements and facial expressions with high resolution. The surveillance camera can also monitor the pet's behavior 24 hours a day. The recording unit records the pet's sleep and excretion behavior observed by the surveillance camera. For example, the recording unit accumulates data such as how long the pet sleeps and the frequency and amount of excretion. The recording unit can also analyze the sleep time and excretion data to check the pet's health. The detection unit detects abnormalities in the pet based on the data recorded by the recording unit. For example, the detection unit detects abnormal behavior, such as when the pet suddenly collapses or makes abnormal movements. The detection unit can also detect signs that indicate a possible problem with the pet's health. The notification unit notifies the owner, pet hotel staff, or veterinary clinic staff of any abnormalities detected by the detection unit. For example, the notification unit sends a notification including details of the time and circumstances when the abnormality occurred. The notification unit also works in conjunction with a dedicated smartphone app, allowing the user to check the pet's condition in real time. This allows the surveillance camera system according to the embodiment to constantly monitor the pet's health and quickly notify the owner if an abnormality occurs. For example, even when the owner is out, the owner can check the pet's condition via smartphone and quickly take any necessary action. Staff at pet hotels and veterinary clinics can also constantly monitor the pet's condition and take any necessary action.

[0030] The surveillance camera is equipped with a generative AI that learns your pet's behavioral patterns and predicts abnormal behavior. The surveillance camera is equipped with a generative AI that learns your pet's behavioral patterns. For example, the surveillance camera records what time of day your pet is usually active and how it moves, and predicts abnormal behavior. The generative AI analyzes your pet's behavioral patterns and builds a predictive model for abnormal behavior. For example, if your pet moves in a way that is different from normal, it will determine that this is abnormal. The generative AI installed in the surveillance camera learns your pet's behavioral patterns in real time and predicts abnormal behavior. For example, if your pet suddenly stops moving, it will determine that this is abnormal. In this way, by learning your pet's behavioral patterns and predicting abnormal behavior, it becomes possible to detect abnormalities early.

[0031] The surveillance camera has an additional temperature sensor, which monitors changes in your pet's body temperature in real time. The surveillance camera has an additional temperature sensor, which monitors your pet's body temperature in real time. For example, the surveillance camera detects an abnormality if your pet's body temperature suddenly rises. The temperature sensor records changes in your pet's body temperature and detects abnormal changes. For example, it determines that an abnormality exists if your pet develops a fever. The temperature sensor installed in the surveillance camera constantly monitors your pet's body temperature and notifies you of any abnormal changes in body temperature in real time. For example, it determines that an abnormality exists if your pet's body temperature drops. In this way, by monitoring changes in your pet's body temperature in real time, abnormalities can be detected early.

[0032] The surveillance camera has added a voice recognition function to detect abnormalities from your pet's cries and sounds. The surveillance camera has added a voice recognition function to analyze your pet's cries. For example, it will detect an abnormality if your pet makes an abnormal cry. The voice recognition function records your pet's cries and sounds and detects abnormal sounds. For example, it will determine an abnormality if your pet makes a distressed cry. The voice recognition function built into the surveillance camera analyzes your pet's cries in real time and detects abnormalities. For example, it will determine an abnormality if your pet makes a sound that is different from normal. This makes it possible to detect abnormalities early by detecting them from your pet's cries and sounds.

[0033] Multiple surveillance cameras are installed and footage from different angles is integrated to generate a 3D model, allowing for a three-dimensional understanding of your pet's movements. Multiple surveillance cameras are installed and footage from different angles is integrated to generate a 3D model. For example, a surveillance camera can capture your pet's movements in three dimensions. Multiple surveillance cameras are used to record your pet's movements from different angles and generate a 3D model. For example, analyzing how your pet is moving in three dimensions. A system is built that installs multiple surveillance cameras and integrates footage to generate a 3D model. For example, your pet's movements are captured in three dimensions in real time. This allows for a three-dimensional understanding of your pet's movements, improving the accuracy of detecting abnormalities.

[0034] The recording unit uses the generation AI to analyze the pet's sleep patterns and detect abnormal sleep rhythms. The recording unit uses the generation AI to analyze the pet's sleep patterns and detect abnormal sleep rhythms. For example, the recording unit determines that an abnormality exists if the pet sleeps for shorter periods of time than usual. The generation AI analyzes the pet's sleep data and identifies abnormal patterns. For example, it determines that an abnormality exists if the pet wakes up frequently. The generation AI installed in the recording unit analyzes the pet's sleep patterns in real time and detects abnormal rhythms. For example, it determines that an abnormality exists if the pet sleeps at a different time than usual. In this way, by analyzing the pet's sleep patterns and detecting abnormal sleep rhythms, abnormalities in health can be discovered early.

[0035] The recording unit automatically analyzes the color and shape of urine and stool to evaluate the health condition. The recording unit automatically analyzes the color and shape of urine and stool to evaluate the health condition. For example, the recording unit determines that an abnormality exists if the urine color is abnormally dark. The automatic analysis function records the color and shape of excrement and evaluates the health condition. For example, it determines that an abnormality exists if the stool shape is abnormal. The automatic analysis function installed in the recording unit analyzes the color and shape of urine and stool in real time to evaluate the health condition. For example, it determines that an abnormality exists if the urine color is different from normal. In this way, by automatically analyzing the color and shape of urine and stool, abnormalities in health condition can be detected early.

[0036] The recording unit records the pet's eating habits and analyzes the relationship between eating patterns and health conditions. The recording unit records the pet's eating habits and analyzes the relationship between eating patterns and health conditions. For example, the recording unit records how much food the pet eats. A system is constructed that records dietary data and analyzes the relationship between health conditions. For example, if the pet does not eat, it is determined that there is an abnormality in the pet's health. A function built into the recording unit records the pet's eating habits in real time and analyzes the relationship between eating patterns and health conditions. For example, it records the time of day the pet eats. This allows for more accurate health management by recording the pet's eating habits and analyzing the relationship between eating patterns and health conditions.

[0037] The notification unit is equipped with a GPS function and simultaneously transmits the pet's location information. The notification unit is equipped with a GPS function and transmits the pet's location information in real time. For example, if the pet exhibits abnormal behavior, the notification unit simultaneously notifies the pet of its location information. The GPS function constantly monitors the pet's location information and transmits a notification including the location information if an abnormality occurs. For example, it determines that an abnormality has occurred if the pet leaves a designated area. The GPS function installed in the notification unit creates a system that transmits the pet's location information in real time. For example, if the pet exhibits abnormal behavior, the notification includes the location information. This allows the pet's location to be quickly determined by simultaneously transmitting the pet's location information.

[0038] The notification unit works in conjunction with the smart home device to automatically activate lights and audio alarms when an abnormality is detected. The notification unit works in conjunction with the smart home device to automatically turn on lights when an abnormality is detected. For example, the notification unit turns on the lights in a room if a pet behaves abnormally. The smart home device builds a system that activates an audio alarm when an abnormality is detected. For example, the notification unit sounds an audio alarm if a pet behaves abnormally. The smart home device equipped with the notification unit automatically activates lights and audio alarms when an abnormality is detected. For example, the notification unit turns on the lights in a room and sounds an audio alarm if a pet behaves abnormally. This enables a quick response by automatically activating lights and audio alarms when an abnormality is detected.

[0039] The notification unit sends notifications of abnormality detection not only to the owner but also to all family members and pet sitters. The notification unit adds a function to send notifications of abnormality detection not only to the owner but also to all family members and pet sitters. For example, if a pet exhibits abnormal behavior, the notification unit sends a notification to all family members. The notification system adds a function to send notifications of abnormality detection to multiple recipients. For example, notifications are sent to pet sitters and veterinary clinic staff. The functions included in the notification unit create a system that sends notifications of abnormality detection not only to the owner but also to all family members and pet sitters. For example, if a pet exhibits abnormal behavior, a notification is sent to multiple recipients. This allows for a quick response by sending notifications of abnormality detection to multiple recipients.

[0040] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0041] The surveillance camera system is further equipped with a voice recognition unit that can analyze the cries and sounds of pets. For example, if the pet makes an abnormal cry, it will detect an abnormality. The voice recognition unit records the pet's cries and sounds and detects abnormal sounds. For example, if the pet makes a distressed cry, it will determine that there is an abnormality. The voice recognition unit installed in the surveillance camera system analyzes the pet's cries in real time and detects abnormalities. For example, if the pet makes a sound that is different from normal, it will determine that there is an abnormality. This makes it possible to detect abnormalities from the pet's cries and sounds, enabling early detection of abnormalities.

[0042] The monitoring camera system is further equipped with a temperature sensor, allowing it to monitor your pet's body temperature in real time. For example, the monitoring camera will detect an abnormality if your pet's body temperature suddenly rises. The temperature sensor records changes in your pet's body temperature and detects abnormal changes. For example, if your pet develops a fever, it will determine that something is abnormal. The temperature sensor installed in the monitoring camera system constantly monitors your pet's body temperature and notifies you of any abnormal changes in body temperature in real time. For example, if your pet's body temperature drops, it will determine that something is abnormal. By monitoring changes in your pet's body temperature in real time, it is possible to detect abnormalities early on.

[0043] Surveillance camera systems can also be configured with multiple cameras and integrate footage from different angles to generate a 3D model. For example, a surveillance camera can capture a pet's movements in three dimensions. Multiple surveillance cameras can be used to record a pet's movements from different angles and generate a 3D model. For example, a pet's movements can be analyzed in three dimensions. Surveillance camera systems can be configured with multiple cameras and integrate footage to generate a 3D model. For example, a pet's movements can be captured in three dimensions in real time. This allows a three-dimensional view of a pet's movements, improving the accuracy of detecting abnormalities.

[0044] The monitoring camera system also uses generation AI in the recording unit to analyze your pet's sleep patterns and detect abnormal sleep rhythms. For example, the recording unit will determine if your pet is sleeping for shorter hours than usual, which is abnormal. The generation AI will analyze your pet's sleep data and identify abnormal patterns. For example, it will determine if your pet wakes up frequently, which is abnormal. The generation AI installed in the recording unit will analyze your pet's sleep patterns in real time and detect abnormal rhythms. For example, it will determine if your pet is sleeping at a different time than usual, which is abnormal. This allows you to analyze your pet's sleep patterns and detect abnormal sleep rhythms, making it possible to detect abnormalities in your pet's health early on.

[0045] The surveillance camera system also has a function in the recording unit that automatically analyzes the color and shape of urine and feces, making it possible to evaluate health conditions. For example, the recording unit will determine that an abnormality exists if the color of urine is abnormally dark. The automatic analysis function records the color and shape of excrement and evaluates health conditions. For example, it will determine that an abnormality exists if the shape of the feces is abnormal. The automatic analysis function built into the recording unit analyzes the color and shape of urine and feces in real time to evaluate health conditions. For example, it will determine that an abnormality exists if the color of urine is different from normal. This allows for early detection of abnormalities in health conditions by automatically analyzing the color and shape of urine and feces.

[0046] The monitoring camera system can also add a GPS function to the notification unit, allowing it to transmit pet location information in real time. For example, if the pet exhibits abnormal behavior, the notification unit will simultaneously notify the pet of its location information. The GPS function constantly monitors the pet's location information and sends a notification including the location information if an abnormality occurs. For example, it determines that an abnormality has occurred if the pet leaves a designated area. The GPS function built into the notification unit creates a system that transmits pet location information in real time. For example, if the pet exhibits abnormal behavior, it will simultaneously notify the pet of its location information. This allows the pet's location to be quickly determined by simultaneously transmitting the pet's location information.

[0047] The processing flow of the first embodiment will be briefly explained below.

[0048] Step 1: The surveillance camera constantly monitors your pet. For example, a surveillance camera can capture your pet's movements and expressions clearly in high resolution, allowing you to monitor your pet 24 hours a day. Step 2: The recording unit records the pet's sleep and excrement as observed by the monitoring camera. For example, the recording unit accumulates data on how long the pet sleeps, the frequency and amount of excrement, etc., and can analyze the sleep time and excrement data to check the pet's health. Step 3: The detection unit detects abnormalities in the pet based on the data recorded by the recording unit. For example, the detection unit can detect abnormal behavior such as the pet suddenly collapsing or making abnormal movements, and detect signs that the pet may have a health problem. Step 4: The notification unit notifies the owner, pet hotel, or veterinary clinic staff of any abnormalities detected by the detection unit. For example, the notification unit may send a notification containing details of the time and circumstances when the abnormality occurred, and may work in conjunction with a dedicated smartphone app, allowing you to check the pet's condition in real time.

[0049] (Example 2) The surveillance camera system according to the embodiment of the present invention is a system that constantly monitors the state of a pet, and the AI ​​that generates it detects and notifies the user of any abnormalities. This allows the surveillance camera system to constantly monitor the health of a pet and quickly notify the user if an abnormality occurs.

[0050] A surveillance camera system according to an embodiment includes a surveillance camera, a recording unit, a detection unit, and a notification unit. The surveillance camera constantly monitors the behavior of a pet. For example, the surveillance camera can clearly capture the pet's movements and facial expressions with high resolution. The surveillance camera can also monitor the pet's behavior 24 hours a day. The recording unit records the pet's sleep and excretion behavior observed by the surveillance camera. For example, the recording unit accumulates data such as how long the pet sleeps and the frequency and amount of excretion. The recording unit can also analyze the sleep time and excretion data to check the pet's health. The detection unit detects abnormalities in the pet based on the data recorded by the recording unit. For example, the detection unit detects abnormal behavior, such as when the pet suddenly collapses or makes abnormal movements. The detection unit can also detect signs that indicate a possible problem with the pet's health. The notification unit notifies the owner, pet hotel staff, or veterinary clinic staff of any abnormalities detected by the detection unit. For example, the notification unit sends a notification including details of the time and circumstances when the abnormality occurred. The notification unit also works in conjunction with a dedicated smartphone app, allowing the user to check the pet's condition in real time. This allows the surveillance camera system according to the embodiment to constantly monitor the pet's health and quickly notify the owner if an abnormality occurs. For example, even when the owner is out, the owner can check the pet's condition via smartphone and quickly take any necessary action. Staff at pet hotels and veterinary clinics can also constantly monitor the pet's condition and take any necessary action.

[0051] The surveillance camera is equipped with a generative AI that learns your pet's behavioral patterns and predicts abnormal behavior. The surveillance camera is equipped with a generative AI that learns your pet's behavioral patterns. For example, the surveillance camera records what time of day your pet is usually active and how it moves, and predicts abnormal behavior. The generative AI analyzes your pet's behavioral patterns and builds a predictive model for abnormal behavior. For example, if your pet moves in a way that is different from normal, it will determine that this is abnormal. The generative AI installed in the surveillance camera learns your pet's behavioral patterns in real time and predicts abnormal behavior. For example, if your pet suddenly stops moving, it will determine that this is abnormal. In this way, by learning your pet's behavioral patterns and predicting abnormal behavior, it becomes possible to detect abnormalities early.

[0052] The surveillance camera has an additional temperature sensor, which monitors changes in your pet's body temperature in real time. The surveillance camera has an additional temperature sensor, which monitors your pet's body temperature in real time. For example, the surveillance camera detects an abnormality if your pet's body temperature suddenly rises. The temperature sensor records changes in your pet's body temperature and detects abnormal changes. For example, it determines that an abnormality exists if your pet develops a fever. The temperature sensor installed in the surveillance camera constantly monitors your pet's body temperature and notifies you of any abnormal changes in body temperature in real time. For example, it determines that an abnormality exists if your pet's body temperature drops. In this way, by monitoring changes in your pet's body temperature in real time, abnormalities can be detected early.

[0053] The monitoring camera has an added emotion estimation function that estimates emotions from pets' facial expressions and assesses their stress level. The monitoring camera is equipped with an emotion estimation function that estimates emotions from pets' facial expressions. For example, if a pet looks anxious, the stress level is assessed. The emotion estimation function analyzes a pet's facial expression and assesses its stress level. For example, if a pet looks relaxed, it is determined that the pet has low stress. The emotion estimation function installed in the monitoring camera analyzes a pet's facial expression in real time and assesses its stress level. For example, if a pet looks excited, it is determined that the pet has high stress. In this way, by estimating a pet's emotions and assessing its stress level, it is possible to understand the pet's psychological state.

[0054] The surveillance camera has added a voice recognition function to detect abnormalities from your pet's cries and sounds. The surveillance camera has added a voice recognition function to analyze your pet's cries. For example, it will detect an abnormality if your pet makes an abnormal cry. The voice recognition function records your pet's cries and sounds and detects abnormal sounds. For example, it will determine an abnormality if your pet makes a distressed cry. The voice recognition function built into the surveillance camera analyzes your pet's cries in real time and detects abnormalities. For example, it will determine an abnormality if your pet makes a sound that is different from normal. This makes it possible to detect abnormalities early by detecting them from your pet's cries and sounds.

[0055] Multiple surveillance cameras are installed and footage from different angles is integrated to generate a 3D model, allowing for a three-dimensional understanding of your pet's movements. Multiple surveillance cameras are installed and footage from different angles is integrated to generate a 3D model. For example, a surveillance camera can capture your pet's movements in three dimensions. Multiple surveillance cameras are used to record your pet's movements from different angles and generate a 3D model. For example, analyzing how your pet is moving in three dimensions. A system is built that installs multiple surveillance cameras and integrates footage to generate a 3D model. For example, your pet's movements are captured in three dimensions in real time. This allows for a three-dimensional understanding of your pet's movements, improving the accuracy of detecting abnormalities.

[0056] The monitoring camera has been equipped with an emotion estimation function that analyzes a pet's reaction when an owner speaks to the pet through the camera, improving the quality of communication. The monitoring camera is equipped with an emotion estimation function that analyzes a pet's reaction when an owner speaks to the pet through the camera. For example, it evaluates whether the pet is happy. The emotion estimation function analyzes a pet's reaction to the owner's voice in real time, improving the quality of communication. For example, it determines whether the pet is relaxed. The emotion estimation function installed in the monitoring camera analyzes communication between owners and pets, building a system to improve the quality. For example, it evaluates whether the pet is feeling stressed. This can improve the quality of communication between owners and pets.

[0057] The recording unit uses the generation AI to analyze the pet's sleep patterns and detect abnormal sleep rhythms. The recording unit uses the generation AI to analyze the pet's sleep patterns and detect abnormal sleep rhythms. For example, the recording unit determines that an abnormality exists if the pet sleeps for shorter periods of time than usual. The generation AI analyzes the pet's sleep data and identifies abnormal patterns. For example, it determines that an abnormality exists if the pet wakes up frequently. The generation AI installed in the recording unit analyzes the pet's sleep patterns in real time and detects abnormal rhythms. For example, it determines that an abnormality exists if the pet sleeps at a different time than usual. In this way, by analyzing the pet's sleep patterns and detecting abnormal sleep rhythms, abnormalities in health can be discovered early.

[0058] The recording unit automatically analyzes the color and shape of urine and stool to evaluate the health condition. The recording unit automatically analyzes the color and shape of urine and stool to evaluate the health condition. For example, the recording unit determines that an abnormality exists if the urine color is abnormally dark. The automatic analysis function records the color and shape of excrement and evaluates the health condition. For example, it determines that an abnormality exists if the stool shape is abnormal. The automatic analysis function installed in the recording unit analyzes the color and shape of urine and stool in real time to evaluate the health condition. For example, it determines that an abnormality exists if the urine color is different from normal. In this way, by automatically analyzing the color and shape of urine and stool, abnormalities in health condition can be detected early.

[0059] The recording unit uses the emotion estimation function to estimate stress and anxiety from the facial expression of the sleeping pet and evaluate the quality of sleep. The recording unit uses the emotion estimation function to analyze the facial expression of the sleeping pet and estimate stress and anxiety. For example, the recording unit determines that the sleep quality is low if the pet looks anxious. The emotion estimation function analyzes the facial expression of the sleeping pet in real time and evaluates stress and anxiety. For example, it determines that the sleep quality is high if the pet looks relaxed. The emotion estimation function installed in the recording unit analyzes the facial expression of the sleeping pet and builds a system to evaluate the sleep quality. For example, it evaluates whether the pet is feeling stressed. In this way, by estimating stress and anxiety from the facial expression of the sleeping pet and evaluating the sleep quality, the pet's health condition can be more accurately understood.

[0060] The recording unit records the pet's eating habits and analyzes the relationship between eating patterns and health conditions. The recording unit records the pet's eating habits and analyzes the relationship between eating patterns and health conditions. For example, the recording unit records how much food the pet eats. A system is constructed that records dietary data and analyzes the relationship between health conditions. For example, if the pet does not eat, it is determined that there is an abnormality in the pet's health. A function built into the recording unit records the pet's eating habits in real time and analyzes the relationship between eating patterns and health conditions. For example, it records the time of day the pet eats. This allows for more accurate health management by recording the pet's eating habits and analyzing the relationship between eating patterns and health conditions.

[0061] The recording unit uses the emotion estimation function to estimate the health condition from the pet's facial expression when it is defecating, and detects abnormalities early. The recording unit uses the emotion estimation function to analyze the pet's facial expression when it is defecating, and estimates the health condition. For example, the recording unit detects abnormalities if the pet looks distressed. The emotion estimation function analyzes the pet's facial expression when it is defecating in real time and evaluates the health condition. For example, it determines that the pet is in good health if it looks relaxed. The emotion estimation function installed in the recording unit analyzes the pet's facial expression when it is defecating, and builds a system that detects abnormalities early. For example, it detects abnormalities if the pet is feeling stressed. This allows the health condition to be estimated from the pet's facial expression when it is defecating, and abnormalities to be detected early, allowing for more accurate pet health management.

[0062] The notification unit is equipped with a GPS function and simultaneously transmits the pet's location information. The notification unit is equipped with a GPS function and transmits the pet's location information in real time. For example, if the pet exhibits abnormal behavior, the notification unit simultaneously notifies the pet of its location information. The GPS function constantly monitors the pet's location information and transmits a notification including the location information if an abnormality occurs. For example, it determines that an abnormality has occurred if the pet leaves a designated area. The GPS function installed in the notification unit creates a system that transmits the pet's location information in real time. For example, if the pet exhibits abnormal behavior, the notification includes the location information. This allows the pet's location to be quickly determined by simultaneously transmitting the pet's location information.

[0063] The notification unit uses the emotion estimation function to estimate the emotion of the pet when the pet behaves abnormally and evaluate the severity of the abnormality. The notification unit uses the emotion estimation function to analyze the emotion of the pet when the pet behaves abnormally and evaluate the severity of the abnormality. For example, the notification unit determines that a serious abnormality exists when the pet looks very anxious. The emotion estimation function analyzes the emotion of the pet when the pet behaves abnormally in real time and evaluates the severity of the abnormality. For example, it determines that a serious abnormality exists when the pet is in a panicked state. The emotion estimation function installed in the notification unit analyzes the emotion of the pet when the pet behaves abnormally and builds a system to evaluate the severity of the abnormality. For example, it determines that a serious abnormality exists when the pet is feeling stressed. In this way, by estimating the emotion of the pet when the pet behaves abnormally and evaluating the severity of the abnormality, it becomes possible to take appropriate action.

[0064] The notification unit works in conjunction with the smart home device to automatically activate lights and audio alarms when an abnormality is detected. The notification unit works in conjunction with the smart home device to automatically turn on lights when an abnormality is detected. For example, the notification unit turns on the lights in a room if a pet behaves abnormally. The smart home device builds a system that activates an audio alarm when an abnormality is detected. For example, the notification unit sounds an audio alarm if a pet behaves abnormally. The smart home device equipped with the notification unit automatically activates lights and audio alarms when an abnormality is detected. For example, the notification unit turns on the lights in a room and sounds an audio alarm if a pet behaves abnormally. This enables a quick response by automatically activating lights and audio alarms when an abnormality is detected.

[0065] The notification unit sends notifications of abnormality detection not only to the owner but also to all family members and pet sitters. The notification unit adds a function to send notifications of abnormality detection not only to the owner but also to all family members and pet sitters. For example, if a pet exhibits abnormal behavior, the notification unit sends a notification to all family members. The notification system adds a function to send notifications of abnormality detection to multiple recipients. For example, notifications are sent to pet sitters and veterinary clinic staff. The functions included in the notification unit create a system that sends notifications of abnormality detection not only to the owner but also to all family members and pet sitters. For example, if a pet exhibits abnormal behavior, a notification is sent to multiple recipients. This allows for a quick response by sending notifications of abnormality detection to multiple recipients.

[0066] The notification unit uses the emotion estimation function to advise the owner on how to respond to their pet when an abnormality is detected. The notification unit adds a function to use the emotion estimation function to advise the owner on how to respond to their pet when an abnormality is detected. For example, if the pet appears anxious, the notification unit advises the owner on how to calm the pet. The emotion estimation function advises the owner on an appropriate response when an abnormality is detected. For example, if the pet is in a panicked state, the emotion estimation function suggests to the owner how to calm the pet. The emotion estimation function included in the notification unit builds a system that advises the owner on how to respond to their pet when an abnormality is detected. For example, if the pet is feeling stressed, the function suggests to the owner how to help the pet relax. This allows the owner to take appropriate action when an abnormality is detected, thereby ensuring the safety of the pet.

[0067] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0068] The surveillance camera system is further equipped with a voice recognition unit that can analyze the cries and sounds of pets. For example, if the pet makes an abnormal cry, it will detect an abnormality. The voice recognition unit records the pet's cries and sounds and detects abnormal sounds. For example, if the pet makes a distressed cry, it will determine that there is an abnormality. The voice recognition unit installed in the surveillance camera system analyzes the pet's cries in real time and detects abnormalities. For example, if the pet makes a sound that is different from normal, it will determine that there is an abnormality. This makes it possible to detect abnormalities from the pet's cries and sounds, enabling early detection of abnormalities.

[0069] The monitoring camera system is further equipped with a temperature sensor, allowing it to monitor your pet's body temperature in real time. For example, the monitoring camera will detect an abnormality if your pet's body temperature suddenly rises. The temperature sensor records changes in your pet's body temperature and detects abnormal changes. For example, if your pet develops a fever, it will determine that something is abnormal. The temperature sensor installed in the monitoring camera system constantly monitors your pet's body temperature and notifies you of any abnormal changes in body temperature in real time. For example, if your pet's body temperature drops, it will determine that something is abnormal. By monitoring changes in your pet's body temperature in real time, it is possible to detect abnormalities early on.

[0070] The monitoring camera system is also equipped with an emotion estimation function that can estimate the emotions from a pet's facial expression and assess its stress level. For example, if a pet looks anxious, the stress level is assessed. The emotion estimation function analyzes a pet's facial expression and assesses its stress level. For example, if a pet looks relaxed, it is determined that the pet has low stress. The emotion estimation function installed in the monitoring camera system analyzes a pet's facial expression in real time and assesses its stress level. For example, if a pet looks excited, it is determined that the pet has high stress. In this way, by estimating a pet's emotions and assessing its stress level, it is possible to understand the pet's psychological state.

[0071] Surveillance camera systems can also be configured with multiple cameras and integrate footage from different angles to generate a 3D model. For example, a surveillance camera can capture a pet's movements in three dimensions. Multiple surveillance cameras can be used to record a pet's movements from different angles and generate a 3D model. For example, a pet's movements can be analyzed in three dimensions. Surveillance camera systems can be configured with multiple cameras and integrate footage to generate a 3D model. For example, a pet's movements can be captured in three dimensions in real time. This allows a three-dimensional view of a pet's movements, improving the accuracy of detecting abnormalities.

[0072] The monitoring camera system is also equipped with an emotion estimation function that analyzes the pet's reaction when the owner speaks to the pet through the camera, improving the quality of communication. For example, it evaluates whether the pet is happy. The emotion estimation function analyzes the pet's reaction to the owner's voice in real time to improve the quality of communication. For example, it determines whether the pet is relaxed. The emotion estimation function installed in the monitoring camera system analyzes communication between the owner and pet, building a system to improve the quality. For example, it evaluates whether the pet is feeling stressed. This can improve the quality of communication between the owner and pet.

[0073] The monitoring camera system also uses generation AI in the recording unit to analyze your pet's sleep patterns and detect abnormal sleep rhythms. For example, the recording unit will determine if your pet is sleeping for shorter hours than usual, which is abnormal. The generation AI will analyze your pet's sleep data and identify abnormal patterns. For example, it will determine if your pet wakes up frequently, which is abnormal. The generation AI installed in the recording unit will analyze your pet's sleep patterns in real time and detect abnormal rhythms. For example, it will determine if your pet is sleeping at a different time than usual, which is abnormal. This allows you to analyze your pet's sleep patterns and detect abnormal sleep rhythms, making it possible to detect abnormalities in your pet's health early on.

[0074] The monitoring camera system can also use an emotion estimation function in the recording unit to analyze the facial expressions of a sleeping pet and estimate stress or anxiety. For example, the recording unit determines that the quality of sleep is low if the pet looks anxious. The emotion estimation function analyzes the facial expressions of a sleeping pet in real time and evaluates stress or anxiety. For example, it determines that the quality of sleep is high if the pet looks relaxed. The emotion estimation function built into the recording unit analyzes the facial expressions of a sleeping pet and builds a system to evaluate the quality of sleep. For example, it evaluates whether the pet is feeling stressed. This makes it possible to estimate stress or anxiety from the facial expressions of a sleeping pet and evaluate the quality of sleep, thereby more accurately understanding the health condition of the pet.

[0075] The surveillance camera system also has a function in the recording unit that automatically analyzes the color and shape of urine and feces, making it possible to evaluate health conditions. For example, the recording unit will determine that an abnormality exists if the color of urine is abnormally dark. The automatic analysis function records the color and shape of excrement and evaluates health conditions. For example, it will determine that an abnormality exists if the shape of the feces is abnormal. The automatic analysis function built into the recording unit analyzes the color and shape of urine and feces in real time to evaluate health conditions. For example, it will determine that an abnormality exists if the color of urine is different from normal. This allows for early detection of abnormalities in health conditions by automatically analyzing the color and shape of urine and feces.

[0076] The monitoring camera system can also add a GPS function to the notification unit, allowing it to transmit pet location information in real time. For example, if the pet exhibits abnormal behavior, the notification unit will simultaneously notify the pet of its location information. The GPS function constantly monitors the pet's location information and sends a notification including the location information if an abnormality occurs. For example, it determines that an abnormality has occurred if the pet leaves a designated area. The GPS function built into the notification unit creates a system that transmits pet location information in real time. For example, if the pet exhibits abnormal behavior, it will simultaneously notify the pet of its location information. This allows the pet's location to be quickly determined by simultaneously transmitting the pet's location information.

[0077] The monitoring camera system can further use an emotion estimation function in the notification unit to analyze the pet's emotion when the pet behaves abnormally and evaluate the severity of the abnormality. For example, the notification unit determines that a serious abnormality exists if the pet looks very anxious. The emotion estimation function analyzes the pet's emotion when the pet behaves abnormally in real time and evaluates the severity of the abnormality. For example, it determines that a serious abnormality exists if the pet is in a panicked state. The emotion estimation function installed in the notification unit analyzes the pet's emotion when the pet behaves abnormally and builds a system to evaluate the severity of the abnormality. For example, it determines that a serious abnormality exists if the pet is feeling stressed. This makes it possible to estimate the pet's emotion when the pet behaves abnormally and evaluate the severity of the abnormality, thereby enabling appropriate response.

[0078] The processing flow of the second embodiment will be briefly explained below.

[0079] Step 1: The surveillance camera constantly monitors your pet. For example, a surveillance camera can capture your pet's movements and expressions clearly in high resolution, allowing you to monitor your pet 24 hours a day. Step 2: The recording unit records the pet's sleep and excrement as observed by the monitoring camera. For example, the recording unit accumulates data on how long the pet sleeps, the frequency and amount of excrement, etc., and can analyze the sleep time and excrement data to check the pet's health. Step 3: The detection unit detects abnormalities in the pet based on the data recorded by the recording unit. For example, the detection unit can detect abnormal behavior such as the pet suddenly collapsing or making abnormal movements, and detect signs that the pet may have a health problem. Step 4: The notification unit notifies the owner, pet hotel, or veterinary clinic staff of any abnormalities detected by the detection unit. For example, the notification unit may send a notification containing details of the time and circumstances when the abnormality occurred, and may work in conjunction with a dedicated smartphone app, allowing you to check the pet's condition in real time.

[0080] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0081] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> Examples of generative AIs include the data generation model 58, such as a neural network model (e.g., a neural network model), and a neural network model (e.g., a neural network model). The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating speech, text data indicating text, and image data indicating an image is also input to the data generation model 58. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specification processing unit 290 performs the above-mentioned specification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0082] Furthermore, the processing by the data processing system 10 described above is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart device 14, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart device 14. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart device 14 or an external device, and the smart device 14 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0083] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0084] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0085] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0086] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0087] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0088] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0089] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0090] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0091] The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0092] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0093] In the smart glasses 214, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. The smart glasses 214 also have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0094] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0095] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0096] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0097] The data processing system 210 according to the second embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 210 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart glasses 214, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart glasses 214. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the smart glasses 214 or an external device, etc., and the smart glasses 214 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0098] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0099] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0100] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0101] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0102] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0103] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0104] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0105] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0106] The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0107] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0108] In the headset type terminal 314, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the headset type terminal 314 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

[0109] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0110] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0111] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0112] The data processing system 310 according to the third embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 310 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the headset type terminal 314, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the headset type terminal 314. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the headset type terminal 314 or an external device, etc., and the headset type terminal 314 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0113] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0114] 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.

[0115] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0116] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[0117] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0118] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS image sensor or a CCD image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0119] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0120] The control object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[0121] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0122] The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0123] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0124] In the robot 414, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. The robot 414 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

[0125] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0126] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[0127] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0128] The data processing system 410 according to the fourth embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 410 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the robot 414, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the robot 414. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the robot 414 or an external device, etc., and the robot 414 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0129] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0130] FIG. 9 illustrates an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and behaviors arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion encompasses both emotions and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[0131] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[0132] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[0133] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. Emotions can also be created for robots, cars, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on speech emotion recognition and brain physiological signal analysis systems for emotions, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the area called "reaction," where sensation is dominant. The right half of the emotion map lists emotions belonging to the area called "situation," where situational awareness is dominant.

[0134] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[0135] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[0136] In the above embodiment, an example was given in which a specific process is performed by one computer 22, but the technology disclosed herein is not limited to this, and distributed processing of the specific process may be performed by multiple computers including computer 22.

[0137] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[0138] 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.

[0139] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[0140] The hardware resource for executing a specific process can be any of the following types of processors: A processor, for example, is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. A processor also includes a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[0141] The hardware resource that executes the specific process may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific process may be a single processor.

[0142] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[0143] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[0144] In the above example, the first to fourth embodiments have been described separately, but some or all of these embodiments may be combined. The smart device 14, smart glasses 214, headset terminal 314, and robot 414 are merely examples, and they may be combined, or other devices may be used. In the above example, the first and second embodiments have been described separately, but they may be combined.

[0145] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[0146] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference. [Explanation of symbols]

[0147] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot

Claims

1. A monitoring camera that constantly monitors your pet's condition, a recording unit that records the sleeping and excretory behavior of the pet observed by the monitoring camera; a detection unit that detects abnormalities in the pet based on the data recorded by the recording unit; and a notification unit that notifies the owner, pet hotel, or veterinary clinic staff of the abnormality detected by the detection unit. A system characterized by:

2. The surveillance camera is Equipped with generative AI, it learns the pet's behavioral patterns and predicts abnormal behavior.

2. The system of claim 1.

3. The surveillance camera is Add a temperature sensor to monitor the pet's temperature changes in real time.

2. The system of claim 1.

4. The surveillance camera is Add emotion estimation function to estimate emotions from the pet's facial expressions and evaluate stress levels 2. The system of claim 1.

5. The surveillance camera is Add a voice recognition function to detect the abnormality from the pet's cries and voices.

2. The system of claim 1.

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