A smart community based on AI for health care management

Abstract

This application relates to a smart community that uses AI artificial intelligence for health care management. This application obtains behavioral monitoring data of smart community users; reports the behavioral monitoring data to the smart community's cloud service platform at a set reporting frequency; the cloud service platform receives the behavioral monitoring data and uses a behavior recognition model to perform cloud computing on the behavioral monitoring data. When it is found that the behavior meets the preset conditions, it sends a behavioral warning message to the smart community; the management center of the smart community receives the behavioral warning message and goes to the warning point to perform health care management on the user. It can perform AI intelligent recognition and judgment on the behavior of residents indoors and outdoors in the community, respond to behavioral warnings in a timely manner and go to the location point for health management. It uses cloud models to perform cloud computing on data to create an intelligent smart community and provide good intelligent services to community residents.

Description

Technical Field

[0001] The present disclosure relates to the technical field, and in particular to a smart community, a health care management method, and a control system for health care management based on AI artificial intelligence. Background Art

[0002] A smart community is a new management model for social innovation. It refers to the full use of the integrated application of new generation information technologies such as the Internet of Things, cloud computing, and mobile Internet to provide community residents with a safe, comfortable, convenient, modern, and intelligent living environment, thereby forming a new management form of community based on information-based and intelligent social management and services.

[0003] In smart community management, the most important thing is to handle the living behavior issues of residents. Residents' food, clothing, housing, transportation, medical care, health care, etc. must all be taken care of to avoid management deficiencies in certain aspects.

[0004] Existing smart communities primarily rely on behavioral monitoring based on the Internet of Things (IoT), collecting behavioral, audio, and video information about residents. This serves as a single management requirement for tracking residents, but rarely involves deeper smart health and wellness management. The collected information only addresses low-level smart management, falling short of the definition of a smart community and failing to provide high-level services to residents.

[0005] For residents of smart communities, the key concern is how to receive effective health and wellness management, as well as attentive and timely care for their daily lives. However, existing community health and wellness services fall far short of these requirements. For example, when falls, injuries, or sudden illnesses occur at home or in the community, community managers lack timely and accurate information on residents' behavior and needs. Therefore, it is necessary to optimize the application of smart communities in health and wellness management, providing targeted health management tailored to residents' behavior. Summary of the Invention

[0006] In order to solve the above problems, this application proposes a smart community, health care management method and control system based on AI artificial intelligence for health care management.

[0007] On the one hand, this application proposes a smart community based on AI for health care management, which is characterized by including:

[0008] A home monitoring unit is used to obtain home monitoring data A of smart community users at home;

[0009] A community monitoring unit, used to obtain community monitoring data B of user activities in the smart community;

[0010] The clock module is used to set the reporting frequency of the smart gateway message to the cloud service platform;

[0011] The smart gateway is used to regularly report the home monitoring data A and / or community monitoring data B to the cloud service platform of the smart community according to the set reporting frequency;

[0012] The cloud service platform is used to receive the behavior monitoring data and perform cloud computing on the home monitoring data A and / or community monitoring data B using a behavior recognition model. When it is found that the behavior meets the preset conditions, a behavior warning information is issued and sent to the smart community.

[0013] As an optional implementation scheme of the present application, optionally, the cloud service platform is deployed with:

[0014] A home behavior recognition model is used to perform cloud computing on the home monitoring data A to identify and obtain home behavior warning information that meets preset conditions;

[0015] A community behavior recognition model is used to perform cloud computing on the community monitoring data B to identify and obtain community behavior warning information that meets preset conditions;

[0016] This port is used to send behavior warning information identified by the above model to the management center of the smart community.

[0017] As an optional implementation scheme of the present application, optionally, the cloud service platform further deploys:

[0018] Authorization management module, used to authorize the administrator of the smart community to send passwords;

[0019] When the administrator of the smart community management center receives the home behavior warning information from the cloud service platform, he / she will go to the community user who received the warning according to the warning information and request a response to the smart access control system of the community user;

[0020] If it is found that the community user's smart access control has no response, an authorization request is sent to the authorization management module of the cloud service platform;

[0021] The authorization management module receives the authorization request, authenticates the administrator and records the identity in a log, and authorizes the sending of the password after the authentication is passed;

[0022] After the smart access control receives the password sent by the authorization management module, it automatically opens the door, and the administrator enters and performs health care management for the community users.

[0023] On the other hand, this application proposes a health care management method, which is implemented based on the above-mentioned smart community for health care management based on AI artificial intelligence, including the following steps:

[0024] Obtain behavioral monitoring data of smart community users;

[0025] Report the behavior monitoring data to the smart community cloud service platform regularly according to the set reporting frequency;

[0026] The cloud service platform receives the behavior monitoring data and performs cloud computing on the behavior monitoring data using a behavior recognition model. When it is found that the behavior meets the preset conditions, a behavior warning message is sent to the smart community;

[0027] The management center of the smart community receives the behavioral warning information and goes to the warning point to carry out health care management for the user.

[0028] As an optional implementation scheme of the present application, optionally, obtaining behavior monitoring data of smart community users includes:

[0029] Preset behavioral characteristics;

[0030] Setting the behavior collection type according to the behavior characteristics;

[0031] Within the behavior collection type, obtaining home monitoring data A of the smart community user at home through the home monitoring unit;

[0032] Within the behavior collection type, community monitoring data B of user activities in the smart community is obtained through the community monitoring unit;

[0033] A dynamic hard disk is used to back up and store the home monitoring data A and the community monitoring data B respectively.

[0034] As an optional implementation scheme of the present application, optionally, a method for creating a behavior recognition model includes:

[0035] Collect behavioral data samples;

[0036] Based on deep learning technology, the behavior data sample is used as input to perform model training to obtain a corresponding behavior recognition model;

[0037] Performing model testing and correction on the behavior recognition model;

[0038] After the test is passed and corrections are made, the working parameters of the behavior recognition model are configured;

[0039] The behavior recognition model is deployed on the cloud service platform, and a port is allocated to the behavior recognition model.

[0040] As an optional implementation scheme of the present application, optionally, regularly reporting the behavior monitoring data to the cloud service platform of the smart community according to the set reporting frequency includes:

[0041] The intelligent gateway receives the behavior monitoring data and determines the type of the collection device of the behavior monitoring data;

[0042] According to the type of the collection device, set the reporting frequency of the collected data for the collection device;

[0043] According to the set reporting frequency, the behavior monitoring data collected by the collection device is regularly reported to the cloud service platform of the smart community.

[0044] As an optional implementation scheme of the present application, optionally, the cloud service platform receives the behavior monitoring data and performs cloud computing on the behavior monitoring data using a behavior recognition model. When it is found that the behavior meets the preset conditions, a behavior warning information is issued to the smart community, including:

[0045] Presetting behavior recognition conditions for each behavior recognition model;

[0046] The cloud service platform receives the behavior monitoring data and determines the data type of the behavior monitoring data;

[0047] Calling the corresponding behavior recognition model according to the data type;

[0048] The behavior recognition model is used to perform cloud computing on the behavior monitoring data to identify and determine whether the behavior in the behavior monitoring data meets the behavior recognition conditions preset in the behavior recognition model:

[0049] If yes, a behavioral warning message will be sent to the smart community;

[0050] Otherwise it ends.

[0051] As an optional implementation scheme of the present application, optionally, the management center of the smart community receives the behavior warning information and goes to the warning point to perform health care management on the user, including:

[0052] The management center of the smart community receives and analyzes the behavior warning information to obtain the user behavior information, user identity information and warning point location information related to the warning;

[0053] Based on the user behavior information, user identity information, and location information of the warning point, the administrator will go to the warning point to conduct health care management for the user, including:

[0054] (1) If it is community behavior warning information, the administrator of the smart community management center will go to the community warning point to carry out health care management for the user;

[0055] (2) If it is a home behavior warning information, when the administrator of the smart community management center receives the home behavior warning information issued by the cloud service platform, he / she will go to the community user who received the warning according to the warning information and request a response to the smart access control of the community user;

[0056] If it is found that the community user's smart access control has no response, an authorization request is sent to the authorization management module of the cloud service platform;

[0057] The authorization management module receives the authorization request, authenticates the administrator and records the identity in a log, and authorizes the sending of the password after the authentication is passed;

[0058] After the smart access control receives the password sent by the authorization management module, it automatically opens the door, and the administrator enters and performs health care management for the community users.

[0059] On the other hand, the present application also proposes a control system, comprising:

[0060] processor;

[0061] a memory for storing processor-executable instructions;

[0062] Wherein, the processor is configured to implement the above-mentioned health care management method when executing the executable instructions.

[0063] Technical effects of the present invention:

[0064] Based on the embodiments of this application, this application obtains the behavior monitoring data of smart community users; reports the behavior monitoring data to the smart community cloud service platform at a set reporting frequency; the cloud service platform receives the behavior monitoring data and uses a behavior recognition model to perform cloud computing on the behavior monitoring data. When it is found that the behavior meets the preset conditions, a behavior warning information is issued to the smart community; the management center of the smart community receives the behavior warning information and goes to the warning point to provide health management for users. It can perform AI intelligent recognition and judgment on the behavior of residents indoors and outdoors in the community, respond to behavioral warnings in a timely manner and go to the location point for health management. It uses cloud models to perform cloud computing on data, create an intelligent smart community, and provide good intelligent services for community residents.

[0065] Further features and aspects of the present disclosure will become apparent from the following detailed description of exemplary embodiments with reference to the attached drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] The accompanying drawings, which are incorporated in and constitute a part of the specification, illustrate exemplary embodiments, features, and aspects of the disclosure and, together with the description, serve to explain the principles of the disclosure.

[0067] Figure 1 A schematic diagram of the application system of a smart community for health care management based on AI artificial intelligence is shown in the present invention;

[0068] Figure 2 Shown is a schematic diagram of the deployment and application of the cloud service platform of the present invention;

[0069] Figure 3 A schematic diagram of an application of remote authorization to open a door on the cloud service platform of the present invention is shown;

[0070] Figure 4 Shown is a schematic diagram of the process of the health care management method of the present invention;

[0071] Figure 5 Shown is a flow chart of the training model of the present invention. DETAILED DESCRIPTION

[0072] Various exemplary embodiments, features, and aspects of the present disclosure will be described in detail below with reference to the accompanying drawings. The same reference numerals in the accompanying drawings represent elements with the same or similar functions. Although various aspects of the embodiments are shown in the accompanying drawings, the drawings are not necessarily drawn to scale unless otherwise indicated.

[0073] The word “exemplary” is used exclusively herein to mean “serving as an example, example, or illustration.” Any embodiment described herein as “exemplary” is not necessarily to be construed as preferred or advantageous over other embodiments.

[0074] In addition, numerous specific details are provided in the following detailed description to better illustrate the present disclosure. Those skilled in the art will appreciate that the present disclosure can be practiced without certain specific details. In some instances, methods, means, components, and circuits well known to those skilled in the art are not described in detail in order to highlight the main points of the present disclosure.

[0075] This application combines intelligent IoT technology and deep learning technology to build a smart community. It uses various IoT devices to collect indoor and outdoor resident behavior data in the smart community and reports it to the cloud server through the smart gateway. The administrator of the smart community can obtain real-time information about the home conditions of indoor home users and outdoor resident activities in the community from the background management system. The behavior recognition model obtained through training can identify and analyze the two types of behavior data to determine whether the resident behavior is dangerous or meets the preset behavioral characteristics / conditions. If it meets the requirements, an early warning will be issued. The administrator can receive location information of the early warning point, dangerous behavior information, and even information about the residents, and can go to the early warning point in a timely and accurate manner to manage and care for the residents' health.

[0076] Example 1

[0077] like Figure 1 As shown, on one hand, this application proposes a smart community for health care management based on AI artificial intelligence, which is characterized by including:

[0078] The home monitoring unit is used to obtain home monitoring data A of the smart community user's home; home monitoring can be a cloud camera or other equipment to record the home behavior of the elderly (indoor behavior), and the acquired data can be uniformly reported to the cloud server through the community gateway; the detection of home behavior can be the monitoring of the elderly's falls or other behavioral actions, which is not limited in this embodiment;

[0079] The community monitoring unit is used to obtain community monitoring data B of user activities in the smart community. Community monitoring mainly monitors residents' outdoor behavior through devices deployed in the community, such as infrared cameras and cloud cameras. Community activity monitoring can include community activities, children playing by the pool, and other community outdoor activities.

[0080] The clock module is used to set the frequency of intelligent gateway message reporting to the cloud service platform. Indoor and outdoor behavior monitoring data is transmitted through the community-deployed intelligent gateway. This embodiment adopts a timed messaging mechanism and deploys a clock module to set the timing mode for the intelligent gateway. The clock module can be implemented as a clock circuit, a timer, or a remote timing system. Its installation method is based on the selected clock solution, such as a clock circuit board card (clock chip) installed in the intelligent gateway. After the timing time is set, the intelligent gateway transmits the message according to the timing mode.

[0081] The smart gateway is used to regularly report the home monitoring data A and / or community monitoring data B to the smart community cloud service platform according to the set reporting frequency. As a common gateway device in the Internet of Things system, the smart gateway is used to provide network capabilities and distribute and collect data. It can adopt a conventional gateway device;

[0082] The cloud service platform is used to receive the behavior monitoring data and perform cloud computing on the home monitoring data A and / or community monitoring data B using the behavior recognition model. When behavior is found to meet preset conditions, a behavior warning message is issued and sent to the smart community. The cloud service platform uses cloud server technology for cloud computing and uses the cloud server as the data processing center of the smart community. The behavior recognition model and the smart community management system, control system, database, authorization management system, etc. are deployed on the cloud server. The smart community administrator interacts with the cloud service platform through backend management software to obtain behavior data and warning information after behavior recognition.

[0083] This embodiment does not elaborate on the description of storing community resident identity information, resident residence information, and other housing information in the cloud service database.

[0084] Smart communities and their residents all register for identity authorization on cloud servers, facilitating secure data transfer and interaction within the same intelligent management platform.

[0085] The cloud service platform for this application prioritizes Huawei Cloud to provide computing capabilities, which can handle business computing capabilities in multiple scenarios.

[0086] like Figure 2 As shown, as an optional implementation scheme of the present application, optionally, the cloud service platform is deployed with:

[0087] A home behavior recognition model is used to perform cloud computing on the home monitoring data A to identify and obtain home behavior warning information that meets preset conditions;

[0088] A community behavior recognition model is used to perform cloud computing on the community monitoring data B to identify and obtain community behavior warning information that meets preset conditions;

[0089] This port is used to send behavior warning information identified by the above model to the management center of the smart community.

[0090] In this embodiment, community behaviors are divided into: indoor home behaviors and outdoor community behaviors. Behaviors include several different types of actions, which are specifically defined by the community administrator and the behavioral characteristics of the corresponding actions are specified.

[0091] This embodiment uses deep learning to obtain corresponding behavior recognition models for the above two aspects of behavior: a home behavior recognition model and a community behavior recognition model. It identifies and judges each type of behavior data, and issues a behavior warning when it is found to meet specific behavior characteristics / conditions.

[0092] When different behavioral data is regularly reported to the cloud server through the intelligent gateway, the data type is determined and the corresponding behavior recognition model is called to perform cloud computing on the pre-processed behavioral data. The analysis determines whether the specific behavior or behaviors in the behavior data meet the preset behavioral standards. If the behavior meets the standards, the current behavior judgment ends. Otherwise, the behavior judgment continues and an early warning message is output if the behavior does not meet the standards. For example, an early warning prompt (with color) is sent to the backend. When the administrator sees the prompt, he or she clicks the early warning event.

[0093] The model training method will be described in Example 2 and will not be elaborated in this example.

[0094] like Figure 3 As shown, as an optional implementation scheme of the present application, optionally, the cloud service platform further deploys:

[0095] Authorization management module, used to authorize the administrator of the smart community to send passwords;

[0096] When the administrator of the smart community management center receives the home behavior warning information from the cloud service platform, he / she will go to the community user who received the warning according to the warning information and request a response to the smart access control system of the community user;

[0097] If it is found that the community user's smart access control has no response, an authorization request is sent to the authorization management module of the cloud service platform;

[0098] The authorization management module receives the authorization request, authenticates the administrator and records the identity in a log, and authorizes the sending of the password after the authentication is passed;

[0099] After the smart access control receives the password sent by the authorization management module, it automatically opens the door, and the administrator enters and performs health care management for the community users.

[0100] In this embodiment, with respect to the home behavior warning information obtained by identifying home behavior, after the administrator obtains a home warning prompt of a certain resident, he or she will go to the resident's home to perform health management according to the warning prompt.

[0101] Here, the smart community uses smart access control. The password of the smart access control is reported to the administrator in advance by the user. Because the administrator and residents have registered and authenticated their identities, the identity information of the administrator and residents and the corresponding houses, such as access control information, are stored in the database of the cloud server. The authorized use of this information is uniformly managed by the authorization management module deployed on the cloud server.

[0102] After the administrator receives a fall behavior warning for an elderly person at home, the warning information will send the user's identity information, fall behavior data, and residential information to the administrator through an early warning event notification. The administrator can then go to the community user who received the warning based on the warning information and request a response to the smart access control of the community user (elderly person living alone).

[0103] (This excludes the situation where the elderly living alone have family members at home and are unable to open the door by themselves)

[0104] The administrator applies to the system for a door opening request, requesting the backend to authorize the access control system to open the door. The smart access control obtains the administrator's information and uploads it to the cloud server. The authorization management module of the cloud service platform authenticates the administrator and records the log. After identity identification and authentication, the access control password is authorized to be sent;

[0105] After the smart access control receives the password sent by the authorization management module, it automatically opens the door, and the administrator enters and manages the health care of the community users. The elderly receive health management and can respond to early warning prompts in a timely manner.

[0106] Therefore, this application uses the behavior recognition model to quickly identify and judge, obtain the behavior recognition results and respond to early warnings, so that the health management of the smart community can be effectively upgraded to intelligent levels.

[0107] Obviously, those skilled in the art should understand that the implementation of all or part of the processes in the above-mentioned embodiment method can be completed by instructing the relevant hardware through a computer program, and the program can be stored in a computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above-mentioned control methods. Those skilled in the art can understand that the implementation of all or part of the processes in the above-mentioned embodiment method can be completed by instructing the relevant hardware through a computer program, and the program can be stored in a computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above-mentioned control methods. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only memory (ROM), a random access memory (RAM), a flash memory, a hard disk (HDD) or a solid-state drive (SSD), etc.; the storage medium can also include a combination of the above-mentioned types of memory.

[0108] Example 2

[0109] like Figure 4 As shown, based on the implementation principle of Example 1, this application, on the other hand, proposes a health care management method, which is implemented based on the above-mentioned smart community based on AI artificial intelligence for health care management, including the following steps:

[0110] S1. Obtain behavioral monitoring data of smart community users;

[0111] S2. Regularly report the behavior monitoring data to the smart community cloud service platform according to the set reporting frequency;

[0112] S3. The cloud service platform receives the behavior monitoring data and performs cloud computing on the behavior monitoring data using a behavior recognition model. When it is found that the behavior meets the preset conditions, a behavior warning message is sent to the smart community;

[0113] S4. The management center of the smart community receives the behavioral warning information and goes to the warning point to perform health care management on the user.

[0114] The collection and acquisition methods of the home monitoring data A and the community monitoring data B are specifically described in Example 1. The above steps can be understood in conjunction with the description of Example 1.

[0115] In this embodiment, specific implementation details of each step will be described.

[0116] As an optional implementation scheme of the present application, optionally, obtaining behavior monitoring data of smart community users includes:

[0117] Preset behavioral characteristics;

[0118] Setting the behavior collection type according to the behavior characteristics;

[0119] Within the behavior collection type, obtaining home monitoring data A of the smart community user at home through the home monitoring unit;

[0120] Within the behavior collection type, community monitoring data B of user activities in the smart community is obtained through the community monitoring unit;

[0121] A dynamic hard disk is used to back up and store the home monitoring data A and the community monitoring data B respectively.

[0122] The implementation of this application will collect data on planned actions and define behavioral characteristics for effective actions to avoid wasting hardware / software application resources of the smart community.

[0123] Administrators will plan the data that needs to be monitored based on the community's activities and exclude data that does not need to be regulated or monitored. The behavioral data that needs to be collected will be collected according to the pre-set collection type. Unnecessary behavioral data will be pre-processed and cleaned after collection (general pre-processing methods).

[0124] Different types of actions can be defined using behavioral features. Different actions, such as falling or drowning, can have corresponding behavioral features, such as the definition of action posture. By extracting the behavioral features of a behavior, we can determine the type of behavior.

[0125] The definition and extraction of behavioral features can be performed using convolutional neural networks.

[0126] When collecting home monitoring data A and community monitoring data B, the data is collected within the set behavior collection type. That is, after collecting the corresponding behavior monitoring data, the behavior data is controlled within the behavior data specified by the behavior collection type through data cleaning, and redundant action behavior data is eliminated. For example, if the behavior characteristics are found to be shooting behavior, which is not within the preset behavior characteristics range, the community monitoring data B1 for the community activity behavior of shooting will be deleted.

[0127] This embodiment uses a dynamic hard disk to back up and store the home monitoring data A and the community monitoring data B respectively to avoid data omission.

[0128] like Figure 5 As shown, as an optional implementation scheme of the present application, optionally, the method for creating a behavior recognition model includes:

[0129] Collect behavioral data samples;

[0130] Based on deep learning technology, the behavior data sample is used as input to perform model training to obtain a corresponding behavior recognition model;

[0131] Performing model testing and correction on the behavior recognition model;

[0132] After the test is passed and corrections are made, the working parameters of the behavior recognition model are configured;

[0133] The behavior recognition model is deployed on the cloud service platform, and a port is allocated to the behavior recognition model.

[0134] This embodiment trains and generates two types of models - a home behavior recognition model and a community behavior recognition model, which can also be called an "indoor model" and an "outdoor model", corresponding to the recognition of indoor and outdoor behavior data respectively.

[0135] The two behavior recognition models, "indoor model" and "outdoor model", can be trained using their respective corresponding community big data. Deep learning technology is a constant technology and will not be described in detail in this embodiment.

[0136] After the model is trained and generated, it can be tested and corrected, and then published to the cloud server for operation. The corresponding data port is allocated for data transmission and reception. The port type is not limited.

[0137] As an optional implementation scheme of the present application, optionally, regularly reporting the behavior monitoring data to the cloud service platform of the smart community according to the set reporting frequency includes:

[0138] The intelligent gateway receives the behavior monitoring data and determines the type of the collection device of the behavior monitoring data;

[0139] According to the type of the collection device, set the reporting frequency of the collected data for the collection device;

[0140] According to the set reporting frequency, the behavior monitoring data collected by the collection device is regularly reported to the cloud service platform of the smart community.

[0141] When the smart gateway transmits data, it will schedule the message based on the data type. Based on the behavior monitoring data, it will track and determine the type of collection device its data source is, and then regularly report the data according to the reporting frequency set for the device.

[0142] Here, device types are divided into devices that collect home behavior data and outdoor devices that collect community behavior data. When deploying the Internet of Things system, you only need to set the corresponding message frequency for each device. After the smart gateway receives the data from the device, it will know its device type and the corresponding reporting frequency, and send messages accordingly.

[0143] As an optional implementation scheme of the present application, optionally, the cloud service platform receives the behavior monitoring data and performs cloud computing on the behavior monitoring data using a behavior recognition model. When it is found that the behavior meets the preset conditions, a behavior warning information is issued to the smart community, including:

[0144] Presetting behavior recognition conditions for each behavior recognition model;

[0145] The cloud service platform receives the behavior monitoring data and determines the data type of the behavior monitoring data;

[0146] Calling the corresponding behavior recognition model according to the data type;

[0147] The behavior recognition model is used to perform cloud computing on the behavior monitoring data to identify and determine whether the behavior in the behavior monitoring data meets the behavior recognition conditions preset in the behavior recognition model:

[0148] If yes, a behavioral warning message will be sent to the smart community;

[0149] Otherwise it ends.

[0150] Different models have different conditions for identifying and judging corresponding behaviors. The cloud server first determines the type of behavior data received (it can also be the device type) to call the corresponding recognition model. For example, if it is determined that a certain behavior data is a fall behavior on xx road in the community, it can be recognized as community monitoring data. If the behavior is an outdoor community behavior, the community behavior recognition model will be called to identify and judge the behavior to determine whether it meets the behavior recognition conditions.

[0151] Here, the algorithms for behavior calculation, behavior feature extraction, and recognition judgment of each model are determined by the functions of each model. This embodiment does not limit the recognition algorithms and feature extraction methods of each model.

[0152] If the model finds that the current behavior meets the preset behavior recognition conditions (behavioral characteristics), it indicates that the resident may have behavioral deviations and issues a warning to remind the resident in time. Otherwise, no warning is issued and the next behavior judgment is made.

[0153] As an optional implementation scheme of the present application, optionally, the management center of the smart community receives the behavior warning information and goes to the warning point to perform health care management on the user, including:

[0154] The management center of the smart community receives and analyzes the behavior warning information to obtain the user behavior information, user identity information and warning point location information related to the warning;

[0155] Based on the user behavior information, user identity information, and location information of the warning point, the administrator will go to the warning point to conduct health care management for the user, including:

[0156] (1) If it is community behavior warning information, the administrator of the smart community management center will go to the community warning point to carry out health care management for the user;

[0157] (2) If it is a home behavior warning information, when the administrator of the smart community management center receives the home behavior warning information issued by the cloud service platform, he / she will go to the community user who received the warning according to the warning information and request a response to the smart access control of the community user;

[0158] If it is found that the community user's smart access control has no response, an authorization request is sent to the authorization management module of the cloud service platform;

[0159] The authorization management module receives the authorization request, authenticates the administrator and records the identity in a log, and authorizes the sending of the password after the authentication is passed;

[0160] After the smart access control receives the password sent by the authorization management module, it automatically opens the door, and the administrator enters and performs health care management for the community users.

[0161] After the warning information is issued, the backend administrator can see the identity information and warning behavior information of the resident who triggered the warning, and can quickly locate the resident's home location.

[0162] Community outdoor early warning, which can quickly locate residents' locations based on early warning images;

[0163] On the contrary, the administrator finds the home of the home user, requests to open the access control system, enters the resident's door, and enters the home to rescue the fallen elderly person.

[0164] After the administrator comes to the rescue, the access control system can use a dynamic password generation method to generate a password for the user.

[0165] The modules or steps of the present invention described above can be implemented using a general-purpose computing device. They can be centralized on a single computing device or distributed across a network of multiple computing devices. Alternatively, they can be implemented using program code executable by the computing device, which can then be stored in a storage device and executed by the computing device. Alternatively, they can be fabricated into separate integrated circuit modules, or multiple modules or steps can be fabricated into a single integrated circuit module for implementation. Thus, the present invention is not limited to any specific combination of hardware and software.

[0166] Example 3

[0167] Furthermore, in another aspect, the present application also proposes a control system, comprising:

[0168] processor;

[0169] a memory for storing processor-executable instructions;

[0170] Wherein, the processor is configured to implement the above-mentioned health care management method when executing the executable instructions.

[0171] The control system of the present disclosure includes a processor and a memory for storing processor-executable instructions. The processor is configured to implement any of the aforementioned smart communities for health care management based on AI artificial intelligence when executing the executable instructions.

[0172] It should be noted that the number of processors can be one or more. Furthermore, the control system of the disclosed embodiment may also include an input device and an output device. The processor, memory, input device, and output device may be connected via a bus or other means, which are not specifically limited herein.

[0173] Memory, as a computer-readable storage medium, can be used to store software programs, computer-executable programs, and various modules, such as the programs or modules corresponding to the AI-based health care management smart community in the embodiments of the present disclosure. The processor executes the software programs or modules stored in memory to perform various functional applications and data processing of the control system.

[0174] The input device can be used to receive input numbers or signals. The signals can be key signals related to user settings and function control of the device / terminal / server. The output device can include a display device such as a display screen.

[0175] While various embodiments of the present disclosure have been described above, the foregoing description is intended to be illustrative, non-exhaustive, and not limited to the disclosed embodiments. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is selected to best explain the principles of the embodiments, their practical applications, or technical improvements to existing technologies, or to enable others skilled in the art to understand the embodiments disclosed herein.

Claims

1. A smart community based on AI for health care management, characterized by: include: A home monitoring unit is used to obtain home monitoring data A of smart community users at home; A community monitoring unit, used to obtain community monitoring data B of user activities in the smart community; The clock module is used to set the reporting frequency of the smart gateway message to the cloud service platform; The smart gateway is used to regularly report the home monitoring data A and community monitoring data B to the cloud service platform of the smart community according to the set reporting frequency; The cloud service platform collects data within the set behavior collection type. That is, after collecting the corresponding behavior monitoring data, it cleans the data to control the behavior data within the behavior data specified by the behavior collection type and eliminates redundant action behavior data. Different types of behavior actions are defined by behavioral characteristics. By extracting the behavioral characteristics of the behavior, it can be determined what kind of behavior it is. The definition and extraction of behavioral features are performed using convolutional neural networks; The cloud service platform is used to receive the behavior monitoring data and perform cloud computing on the home monitoring data A and the community monitoring data B using a behavior recognition model. When it is found that the behavior meets the preset conditions, a behavior warning information is issued and sent to the smart community, including: Presetting behavior recognition conditions for each behavior recognition model; The cloud service platform receives the behavior monitoring data and determines the data type of the behavior monitoring data; Calling the corresponding behavior recognition model according to the data type; The behavior recognition model is used to perform cloud computing on the behavior monitoring data to identify and determine whether the behavior in the behavior monitoring data meets the behavior recognition conditions preset in the behavior recognition model: If yes, a behavioral warning message will be sent to the smart community; Otherwise, it ends; Deployed on the cloud service platform are: A home behavior recognition model is used to perform cloud computing on the home monitoring data A to identify and obtain home behavior warning information that meets preset conditions; A community behavior recognition model is used to perform cloud computing on the community monitoring data B to identify and obtain community behavior warning information that meets preset conditions; Port, used to send the behavior warning information identified by the above model to the management center of the smart community; Two behavior recognition models are trained using their respective corresponding community big data to respectively identify indoor and outdoor behavior data; wherein, the method for creating the behavior recognition model includes: collecting behavior data samples; based on deep learning technology, using the behavior data samples as input to perform model training to obtain a corresponding behavior recognition model; performing model testing and correction on the behavior recognition model; after the test passes and correction is performed, configuring working parameters for the behavior recognition model; deploying the behavior recognition model on the cloud service platform, and allocating ports for the behavior recognition model.

2. The smart community for health care management based on AI artificial intelligence according to claim 1 is characterized in that: The cloud service platform also has: Authorization management module, used to authorize the administrator of the smart community to send passwords; When the administrator of the smart community management center receives the home behavior warning information from the cloud service platform, he / she will go to the community user who received the warning according to the warning information and request a response to the smart access control system of the community user; If it is found that the community user's smart access control has no response, an authorization request is sent to the authorization management module of the cloud service platform; The authorization management module receives the authorization request, authenticates the administrator and records the identity in a log, and authorizes the sending of the password after the authentication is passed; After the smart access control receives the password sent by the authorization management module, it automatically opens the door, and the administrator enters and performs health care management for the community users.

3. A health care management method, implemented based on the smart community for health care management based on AI artificial intelligence as described in claim 2, characterized in that: The steps include: Obtain behavioral monitoring data of smart community users; Report the behavior monitoring data to the smart community cloud service platform regularly according to the set reporting frequency; The cloud service platform receives the behavior monitoring data and performs cloud computing on the behavior monitoring data using a behavior recognition model. When it is found that the behavior meets the preset conditions, a behavior warning message is sent to the smart community; The management center of the smart community receives the behavioral warning information and goes to the warning point to carry out health care management for the user.

4. A health care management method according to claim 3, characterized in that: Obtain behavioral monitoring data of smart community users, including: Preset behavioral characteristics; Setting the behavior collection type according to the behavior characteristics; Within the behavior collection type, obtaining home monitoring data A of the smart community user at home through the home monitoring unit; Within the behavior collection type, community monitoring data B of user activities in the smart community is obtained through the community monitoring unit; A dynamic hard disk is used to back up and store the home monitoring data A and the community monitoring data B respectively.

5. A health care management method according to claim 3, characterized in that: Regularly report the behavior monitoring data to the smart community cloud service platform according to the set reporting frequency, including: The intelligent gateway receives the behavior monitoring data and determines the type of the collection device of the behavior monitoring data; According to the type of the collection device, set the reporting frequency of the collected data for the collection device; According to the set reporting frequency, the behavior monitoring data collected by the collection device is regularly reported to the cloud service platform of the smart community.

6. A health care management method according to claim 3, characterized in that: The management center of the smart community receives the behavioral warning information and goes to the warning point to provide health care management for the user, including: The management center of the smart community receives and analyzes the behavior warning information to obtain the user behavior information, user identity information and warning point location information related to the warning; Based on the user behavior information, user identity information, and location information of the warning point, the administrator will go to the warning point to conduct health care management for the user, including: (1) If it is community behavior warning information, the administrator of the smart community management center will go to the community's warning point to provide health care management for the user; (2) If it is a home behavior warning information, when the administrator of the smart community management center receives the home behavior warning information issued by the cloud service platform, he / she will go to the community user who received the warning according to the warning information and request a response from the smart access control system of the community user; If it is found that the community user's smart access control has no response, an authorization request is sent to the authorization management module of the cloud service platform; The authorization management module receives the authorization request, authenticates the administrator and records the identity in a log, and authorizes the sending of the password after the authentication is passed; After the smart access control receives the password sent by the authorization management module, it automatically opens the door, and the administrator enters and performs health care management for the community users.

7. A control system, characterized in that: include: processor; a memory for storing processor-executable instructions; Wherein, the processor is configured to implement a health care management method according to any one of claims 3 to 6 when executing the executable instructions.

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