Smart old-age care management method, device and equipment based on Internet of Things

Abstract

The invention discloses an intelligent old-age care management method, device and equipment based on the Internet of Things, and the method comprises the steps: collecting user data of an activity region in real time through Internet of Things equipment, and carrying out the user classification of call types through a clustering algorithm according to the number of demands; selecting service items by calling according to health requirements of the classified users, performing data analysis on user requests according to types of the service items, acquiring service providing information corresponding to calling levels, and then running corresponding pension service response intervention; the user performs data feedback on the service quality according to the call type; the feedback result of the activity area and the user data are displayed in real time through a big data visualization platform; before collecting the user data of the activity area, the endowment informatization management platform checks the entering qualification, and enters the endowment informatization management platform after passing the qualification check; and performing entering operation on the user passing the qualification audit. And intelligent and refined behavior analysis and abnormal behavior management of old-age care are realized.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of old-age management, and particularly relates to a smart old-age management method, device and equipment based on Internet of Things. BACKGROUND

[0002] At present, population aging has become a trend of social development, and developing an aging industry is an important content for responding to an aging society, meeting the needs of a large number of old people, and promoting the coordinated development of economy and society. In order to strengthen the comprehensiveness and security of health and safety monitoring of the elderly, it is necessary to establish a health and safety co-monitoring system under the authorization of the terminal user, so that the health and safety data of the terminal user (the old people) can indeed and feasibly serve the old people themselves, achieve the health of the old people managed by multiple people and institutions at the same time, and obtain the concern of children, the attention of old-age care institutions and communities, and the solutions provided by doctors at the first time when problems occur. When the service is needed, the related service can be quickly and accurately obtained, and the life of the old people is facilitated. Since the physical conditions of the terminal users are complex, although the current wearing of various portable body index detection products can discover and handle some sudden accidents, it is difficult to guarantee the accuracy of the alarm, and false alarm may occur. Moreover, sometimes the terminal user may have some minor symptoms and does not want to go to the hospital for diagnosis and treatment, so how to balance it is a big problem at present. Moreover, under the condition that the physical conditions and living habits of different terminal users are different, if the same judgment standard is still used to judge and warn the physical condition of each terminal user, a large error will inevitably occur. Therefore, how to conveniently provide personalized health management services for each terminal user is also a problem to be solved at present. SUMMARY

[0003] The application aims to overcome the defects of the prior art and provide a smart old-age management method, device and equipment based on Internet of Things. The method can solve the problem that the existing old-age management service platform has low management mechanism efficiency, unreasonable scheduling, and the terminal user who needs help cannot obtain timely service. An information management platform is built by using Internet of Things, and an accurate and detailed database and an electronic file of old-age service are established.

[0004] In order to solve the above technical problems, the application provides the following technical scheme: In a first aspect, the application provides a smart old-age management method based on Internet of Things, comprising: Real-time collection of user data of an activity area by an Internet of Things device, setting of a call level of the user, and user classification of call types by using a clustering algorithm according to a demand number; The data analysis response module is used for selecting service items according to the health needs of classified users, performing data analysis on user requests according to service item types, obtaining service providing information corresponding to the call level, and then running corresponding old-age service response intervention. The user feeds back data on service quality according to the call type, and the feedback results and user data of the active area are displayed in real time through a big data visualization platform. Before collecting user data of the active area, the old-age information management platform audits the entry qualification, enters the old-age information management platform after passing the qualification audit, and performs entry operation on the user passing the qualification audit according to the entry type.

[0005] In a second aspect, the present application provides a smart old-age management device based on the Internet of Things, comprising: The data collection module is used for collecting user data of the active area in real time through the Internet of Things equipment, setting the call level of the user, and classifying the call type of the user according to the demand number using a clustering algorithm. The data analysis response module is used for selecting service items according to the health needs of classified users, performing data analysis on user requests according to service item types, obtaining service providing information corresponding to the call level, and then running corresponding old-age service response intervention. The display module is used for the user to feed back data on service quality according to the call type, and the feedback results and user data of the active area are displayed in real time through a big data visualization platform. The entry module is used for the old-age information management platform to audit the entry qualification before collecting user data of the active area, to enter the old-age information management platform after passing the qualification audit, and to perform entry operation on the user passing the qualification audit according to the entry type.

[0006] In a third aspect, the present application provides an electronic device, which comprises one or more processors, a memory for storing one or more programs, and when the one or more programs are executed by the one or more processors, the one or more processors implement the smart old-age management method based on the Internet of Things provided by any embodiment of the present application.

[0007] Compared with the prior art, the present application has the following beneficial effects: The present application can cover multiple active areas, solve the problem that the existing community management machine is not reasonable in scheduling, and the old people seeking help cannot get timely service. It can realize intelligent and fine behavior analysis and behavior anomaly management for the elderly, optimize user experience, and provide decision support for old-age institutions. BRIEF DESCRIPTION OF DRAWINGS

[0008] Figure 1This is a flowchart illustrating the IoT-based smart elderly care management method of the present invention.

[0009] Figure 2 This is a schematic diagram illustrating the service response intervention of the IoT-based smart elderly care management method of the present invention.

[0010] Figure 3 This is a schematic diagram of the structure of the smart elderly care management device based on the Internet of Things of the present invention.

[0011] Figure 4 This is a schematic diagram of the structure of the smart elderly care management device based on the Internet of Things of the present invention. Detailed Implementation

[0012] To enable those skilled in the art to better understand the technical solutions of the present invention, the present invention will be further described in detail below with reference to the accompanying drawings and preferred embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the invention without inventive effort are within the scope of protection of the invention.

[0013] Building a smart elderly care platform can enhance the comprehensive service capabilities of activity areas, conduct comprehensive monitoring and analysis of infrastructure and environmental spaces in activity areas, fully grasp the operational status of activity areas, and optimize user experience.

[0014] Example 1 Figure 1 As shown, this invention provides a smart elderly care management method based on the Internet of Things, comprising: S1: Collect user data in the activity area in real time through IoT devices, set user call levels, and classify users by call type according to the number of calls required; S2: Based on the health needs of categorized users, call to select service items, analyze user requests according to service item type, obtain service provision information corresponding to call level, and then run corresponding elderly care service response intervention. S3: Users provide data feedback on service quality based on call type; the feedback results and user data of the activity area are displayed in real time through a big data visualization platform; S4: Before collecting user data from the activity area, the elderly care information management platform reviews the eligibility of users to join. Users who pass the eligibility review are then allowed to join the platform. According to the joining type, users who pass the eligibility review are allowed to join the platform. Companies that have passed the review and joined the platform are subject to merchant supervision.

[0015] Preferably, S1, before collecting user data in real time through IoT devices, includes screening candidate areas according to established extended criteria and classifying the location levels of the candidate areas as activity areas.

[0016] Further set the call level of the user includes setting the health management emergency degree as the call level.

[0017] Preferably, S1, collecting user data in real time through the Internet of Things device includes: deploying Internet of Things devices in the activity area, and marking the completed Internet of Things devices as activity area collection devices; collecting user life data in real time based on the activity area collection device, and constructing an old-age information management platform.

[0018] The Internet of Things device includes various sensors and all-in-one machine devices, and the user type includes terminal users and family terminal users. Collecting user life data in real time based on the activity area collection device includes: terminal user health status, activity trajectory and environmental data, health data based on real-time monitoring of terminal user health status; collecting environmental data of the terminal user's residence, and extracting safety parameters of the living environment based on the environmental data, including temperature, humidity, air quality and safety hazard data; real-time monitoring of the action data of the intelligent device in the activity area where the terminal user is located, extracting the moving path and activity range of the terminal user in the activity area based on human features, and identifying the behavior characteristics of the terminal user. The health data establishes a health record including basic information, family information, residence information, health condition and health record.

[0019] As shown in Figure 2 The activity area is also provided with a calling device connected to the community emergency center. The calling device is provided with an AI sound wave recognition voice unit: through voiceprint analysis, it can accurately capture distress signals with various dialects, and automatically identify and intercept contents containing similar words or synonyms based on machine learning and natural language processing (NLP); the calling device receives a call request initiated by the terminal device of the terminal user, obtains the online state and busy state of multiple managers in the activity area according to the call request, and generates a manager that is online and idle; the priority score of the manager that is online and idle is calculated based on the Bayesian belief network, and the managers are called one by one according to the priority score until the home terminal device and the manager are connected, and the Bayesian belief network is calculated based on the effective distance, effective state, idle rate, response time and call reliability of the manager, to ensure "second-level response" in emergency situations. The false positive rate is low under environmental noise, and the calling device can integrate one-key calling and positioning tracking functions to ensure that users can obtain rapid assistance in emergency situations.

[0020] Preferably, S2, data analysis of user requests according to service item types includes: processing and storing the collected life data, analyzing the behavior patterns of users, identifying life rules and abnormal behaviors, predicting potential risks based on the identification results, and performing abnormal response intervention; The identification of life rules and analysis of abnormal behavior includes: motion detection, behavior recognition and object detection of the monitored person, motion detection is to detect abnormal motion in the video using background subtraction method, abnormal motion is abnormal movement and long time stillness; behavior recognition is to detect abnormal behavior in the video using convolutional neural network, abnormal behavior includes falling and long time stillness; object detection is to detect abnormal objects in the video using convolutional neural network.

[0021] Preferably, S2, running the corresponding old-age service response intervention includes: selecting service items according to the set call level, the service items generating health management and life services according to the user demand type, the health management including health monitoring suggestions and intervention measures of health indicators, the selection of service items involving the user type of order cost determination, the life services including housekeeping services and social entertainment, the intervention measures including emergency rescue, the emergency rescue being divided into emergency help, fall detection and positioning tracking. The health monitoring suggestions include behavior characteristic suggestions and abnormal detection suggestions based on real-time detection, drug management warning and remote medical treatment, the behavior characteristic suggestions being personalized health suggestions generated for different behavior characteristic end users, and the abnormal detection suggestions being targeted health suggestions provided for the end users with abnormal detection. The housekeeping services include daily cleaning, deep cleaning and travel assistance, the daily cleaning being daily home hygiene services (sweeping, wiping table, washing laundry, cooking, garbage cleaning, etc.), and the deep cleaning being wall cleaning and glass wiping services in addition to daily hygiene services.

[0022] The service providing information corresponding to the call level includes: collecting the health information and life service information of the solitary end user in real time, making a warning according to the real-time data and providing corresponding comprehensive services according to the service request and the behavior analysis result of data analysis.

[0023] The service request includes: constructing an old-age information management platform based on Internet of Things equipment and generating an interactive channel with a mobile terminal, and calling the interactive channel to receive the service request of the user according to the old-age demand.

[0024] Preferably, S4, the old-age information management platform audits the registered qualifications includes: company qualification audit and individual service staff qualification audit. There are intelligent audit and manual audit. After the company qualification audit, the individual service staff qualification audit is started.

[0025] The company qualification audit includes basic information, qualification certificate and service details. The company qualification audit registered in the old-age information management platform includes service management, order management, financial management and data statistics operation.

[0026] The personal service personnel audit includes personal basic information, skill proof, service setting and personal display. The personal service personnel qualification audit is registered in the old-age information management platform, and includes personal management, order management, income management, training and promotion and data statistics operation, and personal data storage. The corresponding comprehensive service includes: after receiving the service request order issued by the user, the personal service personnel is delivered according to the service type to perform corresponding service order.

[0027] The merchant supervision includes credit score generated based on user evaluation, complaint rate, order completion degree and random service record check.

[0028] The application can enhance user experience, realize intelligent and fine behavior analysis and behavior abnormality management of the old-age.

[0029] Embodiment two Figure 3 As shown in the preceding embodiments, a smart old-age management device based on the Internet of Things is also proposed, which comprises: The data collection module 01 is used to collect user data of the activity area in real time through the Internet of Things equipment, set the call level of the user, and use the clustering algorithm according to the demand times to classify the user according to the call type; The data analysis and response module 02 is used to select the service item according to the health demand of the classified user, analyze the user request according to the service item type, obtain the service providing information corresponding to the call level, and then run the corresponding old-age service response intervention; The display module 03 is used for the user to feed back the data of the service quality according to the call type; the feedback results and user data of the activity area are displayed in real time through the big data visualization platform; The registration module 04 is used for the old-age information management platform to audit the registration qualification before collecting the user data of the activity area, and register in the old-age information management platform after the qualification audit; according to the registration type, the user who passes the qualification audit is registered, and the company that has passed the audit receives the merchant supervision.

[0030] Preferably, the data collection module comprises: the activity area division module comprises: used for screening out the candidate area according to the formulated expansion standard, and dividing the site level of the candidate area as the activity area.

[0031] Preferably, the data collection module comprises: the life data collection module comprises: used for deploying the Internet of Things equipment in the activity area, and marking the completed Internet of Things equipment as the activity area collection equipment; based on the activity area collection equipment, the life data of the user is collected in real time, and the old-age information management platform is constructed.

[0032] The life data module includes: health data based on real-time monitoring of the health status of the end user, activity trajectory and environmental data of the end user; environmental data of the end user, based on the environmental data, extracting the safety parameters of the living environment including temperature, humidity, air quality and safety hazard data; real-time monitoring of the action data of the intelligent device in the activity area of the end user, based on the human body characteristics, extracting the moving path and activity range of the end user in the activity area, and identifying the behavior characteristics of the end user.

[0033] The activity area is also provided with a calling device connected to the community emergency center, and the calling device is provided with an AI sound wave recognition voice unit. The AI sound wave recognition voice unit: accurately captures the distress signals with various dialects through voiceprint analysis, and automatically identifies and intercepts the contents containing similar words or synonyms according to machine learning and natural language processing; the calling device receives the call request initiated by the terminal device of the end user, obtains the online state and busy state of a plurality of managers in the activity area according to the call request, to generate a manager in online and idle state; the priority score of the manager in online and idle state is calculated according to the Bayesian belief network, and the managers are called one by one according to the priority score until the home terminal device and the manager are connected, and the Bayesian belief network is calculated based on the effective distance, effective state, idle rate, response time and call reliability of the manager.

[0034] Preferably, the data loading response module includes: processing and storing the collected life data, analyzing the behavior mode of the user, and the identification module predicting potential risks based on the identification results and performing abnormal response intervention; The identification module includes: motion detection, behavior recognition and object detection of the monitored person, the motion detection is to detect the abnormal motion in the video using background subtraction method, the abnormal motion is abnormal movement and long-time stillness; the behavior recognition is to detect the abnormal behavior in the video using convolutional neural network, the abnormal behavior includes falling and long-time stillness; the object detection is to detect the abnormal object in the video using convolutional neural network.

[0035] Preferably, the data loading response module includes: a life service module including: a service item selection service according to a set call level, the service item generates health management and life service according to the demand type of the end user, the health management includes health monitoring suggestion and intervention measures according to the health index, and the selection of the service item involves the user type of the order cost determination; the life service includes housekeeping service and social entertainment, and the intervention measures include emergency rescue including emergency help, fall detection and positioning tracking.

[0036] The service providing module is used for collecting health information and life service information of the solitary terminal user in real time, processing and calculating real-time data according to the service request and the behavior analysis result of the data analysis module, making early warning according to the real-time data, and providing corresponding comprehensive services.

[0037] The service request module includes an interactive channel generated by a mobile terminal based on an Internet of Things device, and the interactive channel is used to receive service requests of users according to the needs of the elderly.

[0038] Preferably, the qualification auditing module includes a company qualification auditing module and a personal service staff qualification auditing module.

[0039] The company qualification auditing module includes basic information, qualification certificates and service details. The company qualification auditing module includes service management, order management, financial management and data statistical operation.

[0040] The personal service staff auditing module includes personal basic information, skill certificates, service settings and personal display. The personal service staff auditing module includes personal management, order management, income management, training and promotion and data statistical operation.

[0041] Preferably, the service providing module includes: after receiving the service request order sent by the user, the personal service staff is delivered according to the service type to perform corresponding service dispatching.

[0042] Preferably, the merchant supervision module includes: credit score generated based on user evaluation, complaint rate and order completion degree, and service inspection of randomly selected service records.

[0043] Embodiment three is as follows: Figure 4 A structure schematic diagram of the smart elderly care management device based on the Internet of Things provided by the embodiment of the application is as shown in the figure. Figure 4 The smart elderly care management device based on the Internet of Things includes at least one processor 310, a memory 320, an input device 330 and an output device 340. Figure 4 The number of processors 310 in the smart elderly care management device based on the Internet of Things can be one or more, and one processor 310 is taken as an example. Figure 4 The processor 310, the memory 320, the input device 330 and the output device 340 in the smart elderly care management device based on the Internet of Things can be connected through a bus or other means.

[0044] The memory 320, as a computer readable storage medium, can be used to store software programs, computer executable programs and modules, such as program instructions / modules (for example, data collection modules, data analysis loading modules, display modules, and moving-in modules) corresponding to the Internet of Things-based smart elderly care management method in the embodiments of the present application. The processor 310 executes the software programs, instructions and modules stored in the memory 320, thereby performing various functional applications and data processing of the Internet of Things-based smart elderly care management device, that is, implementing the above-mentioned Internet of Things-based smart elderly care management method.

[0045] The memory 320 can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system and at least one application required by a function; the data storage area can store data created according to the use of the terminal, etc. In addition, the memory 320 can include a high-speed random access memory, and can also include a non-volatile memory, such as at least one magnetic disk storage device, a flash memory device, or other non-volatile solid-state memory device. In some examples, the memory 320 can further include a memory remotely arranged with respect to the processor 310, which can be connected to the Internet of Things-based smart elderly care management device through a network. Examples of the above-mentioned network include but are not limited to the Internet, an intranet, a local area network, a mobile communication network, and a combination thereof.

[0046] The input device 330 can be used to receive input digital or character information, and generate key signal inputs related to user settings and function control of the Internet of Things-based smart elderly care management device. The output device 340 can include a display device such as a display screen.

[0047] The above only describes the embodiments of the present application and is not intended to limit the present application. Any modification, equivalent replacement, improvement, etc. made by those skilled in the art within the spirit and principles of the present application shall be included in the protection scope of the present application.

Claims

1. A smart elderly care management method based on the Internet of Things, characterized in that, include: By collecting user data in the activity area in real time through IoT devices, setting user call levels, and using clustering algorithms to classify users by call type according to the number of calls required; Based on the health needs of categorized users, call to select service items. After analyzing user requests according to service item type, obtain service provision information corresponding to call level, and then run the corresponding elderly care service response intervention. Users provide data feedback on service quality based on call type; the feedback results and user data of the activity area are displayed in real time through a big data visualization platform; Before collecting user data from the activity area, the elderly care information management platform reviews the eligibility of users to join. Users who pass the eligibility review are then added to the platform. The platform then processes the onboarding process for users who pass the eligibility review, according to their onboarding type.

2. The smart elderly care management method based on the Internet of Things according to claim 1, characterized in that: Before collecting user data in real time via IoT devices, the process includes: selecting candidate areas according to established extended criteria, and classifying the location levels of the candidate areas as activity areas.

3. The smart elderly care management method based on the Internet of Things according to claim 2, characterized in that: The real-time collection of user data through IoT devices includes: deploying IoT devices in the activity area, and labeling the completed IoT devices as activity area collection devices; and constructing an elderly care information management platform based on the real-time collection of user life data by the activity area collection devices.

4. The smart elderly care management method based on the Internet of Things according to claim 3, characterized in that: The real-time data collection of end-users based on the activity area collection device includes: end-user health status, activity trajectory, and environmental data; health data based on real-time monitoring of end-user health status; collection of environmental data of the end-user's residence, and extraction of safety parameters of the residence environment based on the environmental data, including temperature, humidity, air quality, and safety hazard data; real-time monitoring of the action data of smart devices in the activity area of ​​the end-user, and extraction of the end-user's movement path and activity range in the activity area based on human characteristics, and identification of the user's behavioral characteristics.

5. The smart elderly care management method based on the Internet of Things according to claim 4, characterized in that: The data analysis of user requests according to service item type includes: processing and storing the collected life data, analyzing user behavior patterns, identifying life routines and abnormal behaviors, predicting potential risks based on the identification results, and intervening in abnormal responses.

6. The smart elderly care management method based on the Internet of Things according to claim 5, characterized in that: The corresponding elderly care service response intervention includes: selecting service items based on the set call level; generating health management and life services based on user needs; health management including health monitoring recommendations and intervention measures based on health indicators; and determining the user type of the order based on the fees involved in the selected service items.

7. The smart elderly care management method based on the Internet of Things according to claim 6, characterized in that: The process of obtaining service provision information corresponding to the call level includes: collecting health and life service information of users living alone in real time, processing and calculating real-time data based on service requests and behavioral analysis results, issuing early warnings based on real-time data, and providing corresponding comprehensive services.

8. The smart elderly care management method based on the Internet of Things according to claim 1, characterized in that: The elderly care information management platform reviews the qualifications of those joining the platform, including company qualification review and individual service personnel qualification review.

9. A smart elderly care management device based on the Internet of Things, characterized in that, include: The data acquisition module is used to collect user data in the activity area in real time through IoT devices, set the user's call level, and classify users by call type according to the number of calls required; The data analysis and response module is used to select service items by calling according to the health needs of classified users, analyze user requests according to service item type, obtain service provision information corresponding to call level, and then run corresponding elderly care service response intervention. The display module allows users to provide data feedback on service quality based on call type; the feedback results and user data of the activity area are displayed in real time through a big data visualization platform. Before collecting user data from the activity area, the elderly care information management platform reviews the eligibility of users for onboarding. Users who pass the eligibility review are then registered on the platform. The onboarding process is then carried out according to the onboarding type.

10. An electronic device, characterized in that, The electronic device includes: one or more processors; a memory for storing one or more programs; and when the one or more programs are executed by the one or more processors, the one or more processors implement the IoT-based smart elderly care management method as described in any one of claims 1-8.

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