Service fixed-point pushing method and system based on Internet of Things platform and service terminal

Abstract

The invention discloses a service fixed-point pushing method and system based on an Internet of Things platform and a service terminal, and the method comprises the steps: collecting stage behavior parameters of an old person, and carrying out the risk or demand prediction according to the stage behavior parameters through an intelligent human body activity behavior analysis model; potential service demand information of the elderly is determined according to the prediction result, and service chain parameters are generated according to the potential service demand information; determining a plurality of service items based on the service chain parameters, obtaining a service index of each service item, and determining service information according to the service indexes; and determining real-time position information of the elderly, determining a service pushing strategy according to the real-time position information, selecting an optimal service terminal according to the service pushing strategy, and performing fixed-point pushing of the service information. According to the invention, a personalized service information pushing strategy can be made based on the real-time position, service demand and preference of the elderly, and the optimal service terminal is selected according to the use habit of the elderly, so that the service efficiency and the service experience are improved, and the service process is optimized.

Description

Technical Field

[0001] The present invention relates to the technical field of service management, and in particular to a method and system for pushing services to a specific location based on an Internet of Things platform and a service terminal. Background Art

[0002] With the aging population, the demand for elderly care services is growing. Traditional elderly care service models suffer from fragmented service resources, information asymmetry, and low service efficiency, making them unable to meet the diverse and personalized service needs of the elderly. To address these issues, a number of smart elderly care solutions based on IoT technology have emerged in recent years. For example, wearable health monitoring systems for the elderly use wearable devices to monitor the elderly's physiological indicators in real time and promptly identify health risks. Smart home-based elderly care systems use smart home devices to provide a safe, convenient, and comfortable home environment for the elderly. Location-based elderly emergency assistance systems use GPS or indoor positioning technology to obtain real-time location information of the elderly, providing timely assistance in emergencies. While existing technologies have addressed the challenges of traditional elderly care service models to some extent, they still have the following shortcomings: Inaccurate service information delivery: It is difficult to accurately deliver information based on the elderly's real-time location and needs, resulting in service information overload or omissions; and inflexible service delivery strategies: It is difficult to dynamically adjust service delivery strategies based on different service scenarios and elderly needs. Summary of the Invention

[0003] In response to the problems shown above, the present invention provides a service fixed-point push method and system based on the Internet of Things platform and service terminal to solve the problems mentioned in the background technology, such as the service information push is not accurate enough: it is difficult to push accurately according to the real-time location and needs of the elderly, resulting in service information overload or omission, and the service push strategy is not flexible enough: it is difficult to dynamically adjust the service push strategy according to different service scenarios and the needs of the elderly.

[0004] A method for sending a service to a specific location based on an Internet of Things platform and a service terminal comprises the following steps:

[0005] Collect the elderly's stage-specific behavioral parameters and use the intelligent human activity behavior analysis model to predict risks or needs based on these parameters.

[0006] Determine the potential service demand information of the elderly based on the prediction results, and generate service chain parameters based on the potential service demand information;

[0007] Determine multiple service items based on service chain parameters, obtain service indicators for each service item, and determine service information based on the service indicators;

[0008] Determine the real-time location information of the elderly, determine the service push strategy based on the real-time location information, select the best service terminal based on the service push strategy, and push service information to a specific point through the best service terminal.

[0009] Preferably, the step of collecting the elderly's stage-specific behavioral parameters and predicting risk or demand based on the stage-specific behavioral parameters using an intelligent human activity behavior analysis model includes:

[0010] Collect the elderly's physiological data, activity data and voice data at different stages, and determine the elderly's posture changes based on the activity data;

[0011] Determine the elderly's current behavior pattern based on posture changes and physiological data, and perform emotion analysis on voice data to determine the elderly's current emotional pattern;

[0012] Based on data samples of normal data behavior and abnormal data behavior, as well as data samples of stable emotions and data samples of irrational emotions, a deep learning model is trained to generate an intelligent human activity behavior analysis model;

[0013] Determine risk or demand prediction based on current behavior patterns and current emotional patterns through intelligent human activity behavior analysis models;

[0014] Among them, predicted risks include: fall risk, health risk and psychological risk; predicted needs include: dietary needs, medical needs, exercise needs and social needs.

[0015] Preferably, determining the potential service demand information of the elderly according to the prediction results and generating service chain parameters according to the potential service demand information include:

[0016] Determine potential service types and service contents for the elderly based on the prediction results, and determine service attributes based on the potential service types and service contents, wherein the service attributes include: emergency services, daily services, and long-term services;

[0017] Determine the service risk level based on service attributes, determine the service priority based on the service risk level, and sort and organize the service content according to the service priority;

[0018] Determine the gradient level of each service content based on the sorting results, determine the service cost based on the gradient level, and determine the service resource configuration parameters for each service content based on the service cost;

[0019] Perform resource configuration for each service content according to the service resource configuration parameters, and generate service chain parameters based on the configuration results and the service sequence of each service content.

[0020] Preferably, the determining of multiple service items based on the service chain parameters, obtaining service indicators for each service item, and determining service information according to the service indicators includes:

[0021] Determine multiple service requirements and service scenarios for each service requirement based on service chain parameters, and determine multiple service items based on the service requirements and their service scenarios;

[0022] Determine the service quality quantitative index, service efficiency quantitative index and service cost quantitative index of each service item and their respective response parameters;

[0023] Determine the service achievement target parameters for each service item based on the response parameters, and determine the service indicators based on the service achievement target parameters;

[0024] The service object starting state information and ending state information of each service item are determined according to the service indicators, and service information is generated according to the service object starting state information and ending state information.

[0025] Preferably, the determining of the real-time location information of the elderly, determining a service push strategy based on the real-time location information, selecting the best service terminal based on the service push strategy, and performing targeted service information push through the best service terminal include:

[0026] The millimeter-wave radar is used to detect the real-time location information of the elderly, and the current area where the elderly are located is determined based on the real-time location information. The distribution of service terminals in the current area is obtained, and the regional attributes of the current area are determined. The regional attributes include: medical area, entertainment area, living area, and dining area;

[0027] Determine the mapping relationship between real-time location information and service content, and determine the push frequency and timing based on the mapping relationship and the distribution of service terminals;

[0028] Generate a service push strategy based on push frequency and push timing, determine the interaction requirements and visual requirements of each service terminal, and determine the interaction elements based on the service push strategy;

[0029] Match the interactive elements with the interactive requirements and visual requirements of each service terminal, identify the target service terminal with the highest matching value as the best service terminal, and push service information to the best service terminal.

[0030] A service fixed-point push system based on an Internet of Things platform and a service terminal, the system comprising:

[0031] The prediction module is used to collect the elderly's stage-by-stage behavioral parameters and use the intelligent human activity behavior analysis model to predict risks or needs based on the stage-by-stage behavioral parameters;

[0032] A generation module is used to determine the potential service demand information of the elderly based on the prediction results and generate service chain parameters based on the potential service demand information;

[0033] A determination module is used to determine multiple service projects based on service chain parameters, obtain service indicators for each project, and determine a service push strategy based on the service indicators;

[0034] The push module is used to determine the real-time location information of the elderly, determine the service push strategy based on the real-time location information, select the best service terminal based on the service push strategy, and push the service information to a specific point through the best service terminal.

[0035] Preferably, the prediction module includes:

[0036] The first determination submodule is used to collect the elderly's physiological data, activity data and voice data at different stages, and determine the elderly's posture changes based on the activity data;

[0037] The analysis submodule is used to determine the elderly person's current behavior pattern based on posture changes and physiological data, and to perform emotion analysis on voice data to determine the elderly person's current emotion pattern;

[0038] The first generation submodule is used to train the deep learning model based on data samples of normal data behavior and abnormal data behavior, as well as data samples of stable emotions and data samples of irrational emotions to generate an intelligent human activity behavior analysis model;

[0039] The second determination submodule is used to determine risk or demand prediction based on current behavior patterns and current emotional patterns through an intelligent human activity behavior analysis model;

[0040] Among them, predicted risks include: fall risk, health risk and psychological risk; predicted needs include: dietary needs, medical needs, exercise needs and social needs.

[0041] Preferably, the generating module includes:

[0042] The third determination submodule is used to determine the potential service type and service content of the elderly according to the prediction results, and determine the service attributes according to the potential service type and service content, wherein the service attributes include: emergency service, daily service and long-term service;

[0043] The sorting and combing submodule is used to determine the service risk level based on service attributes, determine the service priority based on the service risk level, and sort and comb the service content according to the service priority;

[0044] A fourth determination submodule is configured to determine the gradient level of each service content according to the sorting results, determine the service cost according to the gradient level, and determine the service resource configuration parameters for each service content based on the service cost;

[0045] The second generating submodule is used to perform resource configuration on each service content according to the service resource configuration parameters, and generate service chain parameters according to the configuration results and the service sequence of each service content.

[0046] Preferably, the determining module includes:

[0047] a fifth determination submodule, configured to determine a plurality of service requirements and a service scenario for each service requirement based on the service chain parameters, and determine a plurality of service items based on the service requirements and their service scenarios;

[0048] A sixth determination submodule is used to determine the service quality quantitative index, service efficiency quantitative index and service cost quantitative index of each service item and their respective response parameters;

[0049] A seventh determination submodule is configured to determine a service achievement target parameter for each service item according to the response parameter, and determine a service indicator based on the service achievement target parameter;

[0050] The third generating submodule is configured to determine the service object start state information and the end state information of each service item according to the service indicator, and generate service information according to the service object start state information and the end state information.

[0051] Preferably, the push module includes:

[0052] an eighth determination submodule, configured to detect the real-time location information of the elderly person through a millimeter-wave radar, determine the current area where the elderly person is located based on the real-time location information, obtain the distribution of service terminals in the current area, and determine the regional attributes of the current area, wherein the regional attributes include: a medical area, an entertainment area, a living area, and a dining area;

[0053] A ninth determination submodule is configured to determine a mapping relationship between real-time location information and service content, and to determine a push frequency and a push timing based on the mapping relationship and the distribution of service terminals;

[0054] a tenth determination submodule, configured to generate a service push strategy based on push frequency and push timing, determine the interaction requirements and visual requirements of each service terminal, and determine interaction elements based on the service push strategy;

[0055] The push submodule is used to match the interactive elements with the interactive requirements and visual requirements of each service terminal, identify the target service terminal with the highest matching value as the best service terminal, and push service information to the best service terminal.

[0056] Other features and advantages of the present invention will be described in the following description, and in part will become apparent from the description, or will be understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description and the accompanying drawings.

[0057] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] The accompanying drawings are used to provide further understanding of the present invention and constitute a part of the specification. They are used to explain the present invention together with the embodiments of the present invention and do not constitute a limitation of the present invention.

[0059] Figure 1 This is a workflow diagram of a method for pushing services to specific locations based on an Internet of Things platform and a service terminal provided by the present invention;

[0060] Figure 2 Another workflow diagram of a method for sending targeted services based on an Internet of Things platform and a service terminal provided by the present invention;

[0061] Figure 3 This is a structural diagram of a service fixed-point push system based on an Internet of Things platform and a service terminal provided by the present invention;

[0062] Figure 4 This is a structural diagram of a prediction module in a service fixed-point push system based on an Internet of Things platform and a service terminal provided by the present invention. DETAILED DESCRIPTION

[0063] Exemplary embodiments will be described in detail herein, with examples illustrated in the accompanying drawings. In the following description, when referring to the drawings, identical numerals in different figures represent identical or similar elements, unless otherwise indicated. The embodiments described in the following exemplary embodiments are not intended to represent all possible embodiments consistent with the present disclosure. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present disclosure, as detailed in the appended claims.

[0064] Currently, with the increasing aging of society, the demand for elderly care services is growing. Traditional elderly care service models suffer from problems such as fragmented service resources, information asymmetry, and low service efficiency, making it difficult to meet the diverse and personalized service needs of the elderly. To address these issues, a number of smart elderly care solutions based on IoT technology have emerged in recent years. For example, wearable health monitoring systems for the elderly use wearable devices to monitor the elderly's physiological indicators in real time and promptly identify health risks. Smart home-based elderly care systems use smart home devices to provide elderly people with a safe, convenient, and comfortable home environment. Location-based elderly emergency assistance systems use GPS or indoor positioning technology to obtain the elderly's location information in real time and provide timely assistance in emergencies. Although existing technologies have addressed the problems of traditional elderly care service models to a certain extent, they still have the following shortcomings: insufficiently accurate service information push: it is difficult to accurately push service information based on the elderly's real-time location and needs, resulting in service information overload or omissions; and insufficiently flexible service push strategies: it is difficult to dynamically adjust service push strategies based on different service scenarios and elderly needs. To address the above issues, this embodiment discloses a method for targeted service push based on an IoT platform and a service terminal.

[0065] A method for pushing services to specific locations based on an Internet of Things platform and a service terminal, such as Figure 1 As shown, the following steps are included:

[0066] Step S101: collecting the elderly's stage-specific behavioral parameters, and using an intelligent human activity behavior analysis model to predict risk or demand based on the stage-specific behavioral parameters;

[0067] Step S102: Determine the elderly's potential service demand information based on the prediction results, and generate service chain parameters based on the potential service demand information;

[0068] Step S103: determining multiple service items based on the service chain parameters, obtaining service indicators for each service item, and determining service information based on the service indicators;

[0069] Step S104: determine the real-time location information of the elderly, determine a service push strategy based on the real-time location information, select the best service terminal based on the service push strategy, and push service information to a specific location through the best service terminal.

[0070] The working principle of the above technical solution is: collect the stage-by-stage behavioral parameters of the elderly, and use the intelligent human activity behavior analysis model to predict risks or needs based on the stage-by-stage behavioral parameters; determine the elderly's potential service demand information based on the prediction results, and generate service chain parameters based on the potential service demand information; determine multiple service items based on the service chain parameters, obtain the service indicators of each service item, and determine the service information based on the service indicators; determine the real-time location information of the elderly, determine the service push strategy based on the real-time location information, select the best service terminal based on the service push strategy, and push the service information to a specific point through the best service terminal.

[0071] The beneficial effects of the above technical solution are: by generating service chain parameters, a service system covering multiple service items can be constructed to meet the diverse needs of the elderly, improve practicality and the elderly's experience, and further, by accurately determining the service push strategy based on the elderly's real-time location information and then selecting the best service terminal for service push, it is possible to formulate personalized service information push strategies based on the elderly's real-time location, service needs and preferences, and select the best service terminal according to the elderly's usage habits, thereby improving service efficiency and service experience and optimizing service processes, and solving the problems mentioned in the prior art that the service information push is not accurate enough: it is difficult to accurately push according to the elderly's real-time location and needs, resulting in service information overload or omission, and the service push strategy is not flexible enough: it is difficult to dynamically adjust the service push strategy according to different service scenarios and elderly needs.

[0072] In this embodiment, the method further includes:

[0073] Obtain the basic disease parameters of each elderly person, and determine the physical health status parameters of each elderly person based on the basic disease parameters;

[0074] Determine necessary push services based on physical health status parameters, behavioral parameters, and location information of each elderly person;

[0075] Determine the in-depth service process based on the service items of the necessary push services, and select specific service items, service objects, and service plans based on the in-depth service process;

[0076] Provide specific and exclusive services to each elderly person through service items, service objects and service plans.

[0077] In this embodiment, the service items include: diet planning service, health tracking service and health monitoring service;

[0078] In this embodiment, the service object is represented by the service object for the elderly corresponding to the service item, for example, the service object of the meal planning service is the restaurant;

[0079] In this embodiment, the service plan refers to a service plan in which the service recipient takes effective measures for the health of the elderly in terms of service items, for example, formulating a low-sugar diet recipe combination plan for the elderly with diabetes.

[0080] The beneficial effects of the above technical solution are: by determining the physical health status parameters of each elderly person and formulating targeted necessary service processes for them, it is possible to track and monitor the physical health status of each elderly person while also providing them with adaptive services that meet their physical needs, thereby improving the user experience and practicality and achieving accurate service docking.

[0081] In this embodiment, after generating the service chain parameters according to the potential service demand information, the following steps are further included:

[0082] Determine multiple related service items based on service chain parameters, determine the core service strategy between each service item, and determine service status parameters based on the core service strategy;

[0083] Determine the service response parameters of each service item based on the service status parameters, and determine the daily service throughput and throughput cooling cycle of each service item based on the service response parameters;

[0084] Determine the service sequence of each service project based on the daily service throughput and throughput cooling cycle, and construct a project service arrangement sequence based on service chain parameters according to the service sequence;

[0085] Determine the microservice set for the elderly based on the project service arrangement sequence, and determine the service instance path of each microservice in the microservice set;

[0086] Determine the spatial domain mobility attribute of each microservice based on the service instance path, where the spatial domain mobility attributes include short-distance mobility, medium-distance mobility, and long-distance mobility;

[0087] Determine the service delay coefficient of each microservice based on the spatial domain mobility attribute of each microservice, and determine the service order deployment strategy of each microservice based on the service delay coefficient and the service standard of each microservice;

[0088] Determine the service emphasis weight of each microservice based on the service sequence deployment strategy of the microservice, and build a hierarchical service structure diagram of all microservices based on the service emphasis weight;

[0089] Determine the deep service request characteristics of each layer of microservices based on the hierarchical service structure diagram, and determine the service architecture of each layer of microservices based on the deep service request characteristics;

[0090] Determine the service parameter configuration of the service chain parameters according to the service architecture, and configure the service equipment, terminals and scenarios based on the service parameter configuration.

[0091] The beneficial effects of the above technical solution are: by arranging the service chain parameters in time sequence to determine the microservice sequence set and then dividing the hierarchical structure and service deployment of all microservices, it is possible to ensure the consistency and reliability of the equipment and environment provided for all microservices in the service chain, while also providing users with different levels of service enjoyment, improving the user experience and practicality.

[0092] In one embodiment, Figure 2 As shown, the method of collecting the elderly's stage-specific behavioral parameters and predicting risks or needs based on the stage-specific behavioral parameters through an intelligent human activity behavior analysis model includes:

[0093] Step S201: collecting the elderly's physiological data, activity data, and voice data at different stages, and determining the elderly's posture changes based on the activity data;

[0094] Step S202: determining the elderly person's current behavior pattern based on posture changes and physiological data, and performing emotion analysis on the voice data to determine the elderly person's current emotion pattern;

[0095] Step S203: training a deep learning model based on data samples of normal data behaviors and abnormal data behaviors, as well as data samples of stable emotions and data samples of irrational emotions to generate an intelligent human activity behavior analysis model;

[0096] Step S204: determining risk or demand prediction based on current behavior patterns and current emotional patterns through the intelligent human activity behavior analysis model;

[0097] Among them, predicted risks include: fall risk, health risk and psychological risk; predicted needs include: dietary needs, medical needs, exercise needs and social needs.

[0098] The beneficial effects of the above technical solution are: by constructing an intelligent human activity behavior analysis model, the expected service needs of the elderly can be quickly and accurately judged based on their real-time behavior and emotions based on their daily behavior and emotional expressions, thereby improving the judgment accuracy and reliability as well as the elderly's experience.

[0099] In one embodiment, determining the elderly's potential service demand information based on the prediction results and generating service chain parameters based on the potential service demand information includes:

[0100] Determine potential service types and service contents for the elderly based on the prediction results, and determine service attributes based on the potential service types and service contents, wherein the service attributes include: emergency services, daily services, and long-term services;

[0101] Determine the service risk level based on service attributes, determine the service priority based on the service risk level, and sort and organize the service content according to the service priority;

[0102] Determine the gradient level of each service content based on the sorting results, determine the service cost based on the gradient level, and determine the service resource configuration parameters for each service content based on the service cost;

[0103] Perform resource configuration for each service content according to the service resource configuration parameters, and generate service chain parameters based on the configuration results and the service sequence of each service content.

[0104] The beneficial effects of the above technical solution are: by sorting and sorting the various service contents, a reasonable and stable service process can be formulated for the elderly based on the urgency of the service items, ensuring the real-time nature of each service and the immediate needs of the elderly, and improving stability and reliability.

[0105] In one embodiment, determining multiple service items based on the service chain parameters, obtaining service indicators for each service item, and determining service information according to the service indicators include:

[0106] Determine multiple service requirements and service scenarios for each service requirement based on service chain parameters, and determine multiple service items based on the service requirements and their service scenarios;

[0107] Determine the service quality quantitative index, service efficiency quantitative index and service cost quantitative index of each service item and their respective response parameters;

[0108] Determine the service achievement target parameters for each service item based on the response parameters, and determine the service indicators based on the service achievement target parameters;

[0109] The service object starting state information and ending state information of each service item are determined according to the service indicators, and service information is generated according to the service object starting state information and ending state information.

[0110] The beneficial effects of the above technical solution are: by generating service information based on the starting state information and ending state information of the service object, the service information can be accurately defined according to the changing state of each service for the service object before and after the service, ensuring the adaptability and service compatibility of the service process with the effects desired by the elderly, and further improving practicality and reliability.

[0111] In one embodiment, determining the real-time location information of the elderly, determining a service push strategy based on the real-time location information, selecting the best service terminal based on the service push strategy, and performing targeted service information push through the best service terminal include:

[0112] The millimeter-wave radar is used to detect the real-time location information of the elderly, and the current area where the elderly are located is determined based on the real-time location information. The distribution of service terminals in the current area is obtained, and the regional attributes of the current area are determined. The regional attributes include: medical area, entertainment area, living area, and dining area;

[0113] Determine the mapping relationship between real-time location information and service content, and determine the push frequency and timing based on the mapping relationship and the distribution of service terminals;

[0114] Generate a service push strategy based on push frequency and push timing, determine the interaction requirements and visual requirements of each service terminal, and determine the interaction elements based on the service push strategy;

[0115] Match the interactive elements with the interactive requirements and visual requirements of each service terminal, identify the target service terminal with the highest matching value as the best service terminal, and push service information to the best service terminal.

[0116] The beneficial effect of the above technical solution is that by using the interactive element matching method to select the best service terminal, reasonable terminal selection can be carried out according to the interactive compatibility between each service terminal and the service push strategy, thereby improving the terminal adaptability and practicality.

[0117] In one embodiment, this embodiment also discloses a service fixed-point push system based on the Internet of Things platform and service terminal, such as Figure 3 As shown, the system includes:

[0118] Prediction module 301 is used to collect the elderly's stage behavior parameters and make risk or demand predictions based on the stage behavior parameters through the intelligent human activity behavior analysis model;

[0119] A generating module 302 is used to determine the potential service demand information of the elderly according to the prediction results, and generate service chain parameters according to the potential service demand information;

[0120] A determination module 303 is configured to determine multiple service items based on the service chain parameters, obtain service indicators for each item, and determine a service push strategy based on the service indicators;

[0121] The push module 304 is used to determine the real-time location information of the elderly, determine the service push strategy based on the real-time location information, select the best service terminal based on the service push strategy, and push the service information to a specific point through the best service terminal.

[0122] The working principle and beneficial effects of the above technical solution have been explained in the method embodiment and will not be repeated here.

[0123] In one embodiment, Figure 4As shown, the prediction module 301 includes:

[0124] The first determination submodule 3011 is used to collect the elderly's physiological data, activity data and voice data at different stages, and determine the elderly's posture changes based on the activity data;

[0125] Analysis submodule 3012, for determining the elderly person's current behavior pattern based on posture changes and physiological data, and performing emotion analysis on voice data to determine the elderly person's current emotion pattern;

[0126] The first generating submodule 3013 is used to train the deep learning model based on the data samples of normal data behavior and abnormal data behavior, as well as the data samples of stable emotions and the data samples of irrational emotions to generate an intelligent human activity behavior analysis model;

[0127] The second determination submodule 3014 is configured to determine risk or demand prediction based on the current behavior pattern and the current emotion pattern through the intelligent human activity behavior analysis model;

[0128] Among them, predicted risks include: fall risk, health risk and psychological risk; predicted needs include: dietary needs, medical needs, exercise needs and social needs.

[0129] In one embodiment, the generating module includes:

[0130] The third determination submodule is used to determine the potential service type and service content of the elderly according to the prediction results, and determine the service attributes according to the potential service type and service content, wherein the service attributes include: emergency service, daily service and long-term service;

[0131] The sorting and combing submodule is used to determine the service risk level based on service attributes, determine the service priority based on the service risk level, and sort and comb the service content according to the service priority;

[0132] A fourth determination submodule is configured to determine the gradient level of each service content according to the sorting results, determine the service cost according to the gradient level, and determine the service resource configuration parameters for each service content based on the service cost;

[0133] The second generating submodule is used to perform resource configuration on each service content according to the service resource configuration parameters, and generate service chain parameters according to the configuration results and the service sequence of each service content.

[0134] In one embodiment, the determining module includes:

[0135] a fifth determination submodule, configured to determine a plurality of service requirements and a service scenario for each service requirement based on the service chain parameters, and determine a plurality of service items based on the service requirements and their service scenarios;

[0136] A sixth determination submodule is used to determine the service quality quantitative index, service efficiency quantitative index and service cost quantitative index of each service item and their respective response parameters;

[0137] A seventh determination submodule is configured to determine a service achievement target parameter for each service item according to the response parameter, and determine a service indicator based on the service achievement target parameter;

[0138] The third generating submodule is configured to determine the service object start state information and the end state information of each service item according to the service indicator, and generate service information according to the service object start state information and the end state information.

[0139] In one embodiment, the push module includes:

[0140] an eighth determination submodule, configured to detect the real-time location information of the elderly person through a millimeter-wave radar, determine the current area where the elderly person is located based on the real-time location information, obtain the distribution of service terminals in the current area, and determine the regional attributes of the current area, wherein the regional attributes include: a medical area, an entertainment area, a living area, and a dining area;

[0141] A ninth determination submodule is configured to determine a mapping relationship between real-time location information and service content, and to determine a push frequency and a push timing based on the mapping relationship and the distribution of service terminals;

[0142] a tenth determination submodule, configured to generate a service push strategy based on push frequency and push timing, determine the interaction requirements and visual requirements of each service terminal, and determine interaction elements based on the service push strategy;

[0143] The push submodule is used to match the interactive elements with the interactive requirements and visual requirements of each service terminal, identify the target service terminal with the highest matching value as the best service terminal, and push service information to the best service terminal.

[0144] Those skilled in the art should understand that the first and second in the present invention simply refer to different application stages.

[0145] Other embodiments of the present disclosure will readily occur to those skilled in the art after considering the specification and practicing the disclosure herein. This application is intended to cover any variations, uses, or adaptations of the present disclosure that follow from the general principles of the present disclosure and include common knowledge or customary techniques in the art not disclosed herein. The description and examples are to be considered as exemplary only, with the true scope and spirit of the present disclosure being indicated by the following claims.

[0146] It should be understood that the present disclosure is not limited to the exact structures that have been described above and shown in the drawings, and that various modifications and changes can be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

Claims

1. A method for pushing services to designated locations based on an Internet of Things platform and a service terminal, characterized in that: The following steps are involved: Collect the elderly's stage-specific behavioral parameters and use the intelligent human activity behavior analysis model to predict risks or needs based on these parameters. Determine the potential service demand information of the elderly based on the prediction results, and generate service chain parameters based on the potential service demand information; Determine multiple service items based on service chain parameters, obtain service indicators for each service item, and determine service information based on the service indicators; Determine the real-time location information of the elderly, determine the service push strategy based on the real-time location information, select the best service terminal based on the service push strategy, and push service information to a specific point through the best service terminal.

2. The method for pushing services to designated locations based on an Internet of Things platform and a service terminal according to claim 1, characterized in that: The collecting of the elderly's stage-specific behavioral parameters and the prediction of risk or demand based on the stage-specific behavioral parameters using an intelligent human activity behavior analysis model include: Collect the elderly's physiological data, activity data and voice data at different stages, and determine the elderly's posture changes based on the activity data; Determine the elderly's current behavior pattern based on posture changes and physiological data, and perform emotion analysis on voice data to determine the elderly's current emotional pattern; Based on data samples of normal data behavior and abnormal data behavior, as well as data samples of stable emotions and data samples of irrational emotions, a deep learning model is trained to generate an intelligent human activity behavior analysis model; Determine risk or demand prediction based on current behavior patterns and current emotional patterns through intelligent human activity behavior analysis models; Among them, predicted risks include: fall risk, health risk and psychological risk; predicted needs include: dietary needs, medical needs, exercise needs and social needs.

3. The method for pushing services to designated locations based on an Internet of Things platform and a service terminal according to claim 1, characterized in that: Determining the potential service demand information of the elderly based on the prediction results and generating service chain parameters based on the potential service demand information includes: Determine potential service types and service contents for the elderly based on the prediction results, and determine service attributes based on the potential service types and service contents, wherein the service attributes include: emergency services, daily services, and long-term services; Determine the service risk level based on service attributes, determine the service priority based on the service risk level, and sort and organize the service content according to the service priority; Determine the gradient level of each service content based on the sorting results, determine the service cost based on the gradient level, and determine the service resource configuration parameters for each service content based on the service cost; Perform resource configuration for each service content according to the service resource configuration parameters, and generate service chain parameters based on the configuration results and the service sequence of each service content.

4. The method for pushing services to designated locations based on an Internet of Things platform and a service terminal according to claim 1, characterized in that: The determining of multiple service items based on the service chain parameters, obtaining service indicators for each service item, and determining service information according to the service indicators include: Determine multiple service requirements and service scenarios for each service requirement based on service chain parameters, and determine multiple service items based on the service requirements and their service scenarios; Determine the service quality quantitative index, service efficiency quantitative index and service cost quantitative index of each service item and their respective response parameters; Determine the service achievement target parameters for each service item based on the response parameters, and determine the service indicators based on the service achievement target parameters; The service object starting state information and ending state information of each service item are determined according to the service indicators, and service information is generated according to the service object starting state information and ending state information.

5. The method for pushing services to designated locations based on an Internet of Things platform and a service terminal according to claim 1, characterized in that: The method of determining the real-time location information of the elderly, determining a service push strategy based on the real-time location information, selecting the best service terminal based on the service push strategy, and performing fixed-point service information push through the best service terminal includes: The millimeter-wave radar is used to detect the real-time location information of the elderly, and the current area where the elderly are located is determined based on the real-time location information. The distribution of service terminals in the current area is obtained, and the regional attributes of the current area are determined. The regional attributes include: medical area, entertainment area, living area, and dining area; Determine the mapping relationship between real-time location information and service content, and determine the push frequency and timing based on the mapping relationship and the distribution of service terminals; Generate a service push strategy based on push frequency and push timing, determine the interaction requirements and visual requirements of each service terminal, and determine the interaction elements based on the service push strategy; Match the interactive elements with the interactive requirements and visual requirements of each service terminal, identify the target service terminal with the highest matching value as the best service terminal, and push service information to the best service terminal.

6. A service fixed-point push system based on the Internet of Things platform and service terminal, characterized in that: The system includes: The prediction module is used to collect the elderly's stage-by-stage behavioral parameters and use the intelligent human activity behavior analysis model to predict risks or needs based on the stage-by-stage behavioral parameters; A generation module is used to determine the potential service demand information of the elderly based on the prediction results and generate service chain parameters based on the potential service demand information; A determination module is used to determine multiple service projects based on service chain parameters, obtain service indicators for each project, and determine a service push strategy based on the service indicators; The push module is used to determine the real-time location information of the elderly, determine the service push strategy based on the real-time location information, select the best service terminal based on the service push strategy, and push the service information to a specific point through the best service terminal.

7. The service fixed-point push system based on the Internet of Things platform and service terminal according to claim 6 is characterized in that: The prediction module includes: The first determination submodule is used to collect the elderly's physiological data, activity data and voice data at different stages, and determine the elderly's posture changes based on the activity data; The analysis submodule is used to determine the elderly person's current behavior pattern based on posture changes and physiological data, and to perform emotion analysis on voice data to determine the elderly person's current emotion pattern; The first generation submodule is used to train the deep learning model based on data samples of normal data behavior and abnormal data behavior, as well as data samples of stable emotions and data samples of irrational emotions to generate an intelligent human activity behavior analysis model; The second determination submodule is used to determine risk or demand prediction based on current behavior patterns and current emotional patterns through an intelligent human activity behavior analysis model; Among them, predicted risks include: fall risk, health risk and psychological risk; predicted needs include: dietary needs, medical needs, exercise needs and social needs.

8. The service point push system based on the Internet of Things platform and service terminal according to claim 6 is characterized in that: The generation module includes: The third determination submodule is used to determine the potential service type and service content of the elderly according to the prediction results, and determine the service attributes according to the potential service type and service content, wherein the service attributes include: emergency service, daily service and long-term service; The sorting and combing submodule is used to determine the service risk level based on service attributes, determine the service priority based on the service risk level, and sort and comb the service content according to the service priority; A fourth determination submodule is configured to determine the gradient level of each service content according to the sorting results, determine the service cost according to the gradient level, and determine the service resource configuration parameters for each service content based on the service cost; The second generating submodule is used to perform resource configuration on each service content according to the service resource configuration parameters, and generate service chain parameters according to the configuration results and the service sequence of each service content.

9. The service fixed-point push system based on the Internet of Things platform and service terminal according to claim 6 is characterized in that: The determining module includes: a fifth determination submodule, configured to determine a plurality of service requirements and a service scenario for each service requirement based on the service chain parameters, and determine a plurality of service items based on the service requirements and their service scenarios; A sixth determination submodule is used to determine the service quality quantitative index, service efficiency quantitative index and service cost quantitative index of each service item and their respective response parameters; A seventh determination submodule is configured to determine a service achievement target parameter for each service item according to the response parameter, and determine a service indicator based on the service achievement target parameter; The third generating submodule is configured to determine the service object start state information and the end state information of each service item according to the service indicator, and generate service information according to the service object start state information and the end state information.

10. The service fixed-point push system based on the Internet of Things platform and service terminal according to claim 6, characterized in that: The push module includes: an eighth determination submodule, configured to detect the real-time location information of the elderly person through a millimeter-wave radar, determine the current area where the elderly person is located based on the real-time location information, obtain the distribution of service terminals in the current area, and determine the regional attributes of the current area, wherein the regional attributes include: a medical area, an entertainment area, a living area, and a dining area; A ninth determination submodule is configured to determine a mapping relationship between real-time location information and service content, and to determine a push frequency and a push timing based on the mapping relationship and the distribution of service terminals; a tenth determination submodule, configured to generate a service push strategy based on push frequency and push timing, determine the interaction requirements and visual requirements of each service terminal, and determine interaction elements based on the service push strategy; The push submodule is used to match the interactive elements with the interactive requirements and visual requirements of each service terminal, identify the target service terminal with the highest matching value as the best service terminal, and push service information to the best service terminal.

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