Intelligent old-age care service management system based on Internet of Things

Abstract

The invention relates to the technical field of old-age service, and discloses an Internet of Things-based smart old-age service management system, which comprises a health detection module used for collecting physiological data of old people in real time by adopting a sensor group and a smart wearable device, the communication module is used for transmitting the collected data through a wireless local area network and a 5G technology; the correction alarm module is used for monitoring the environment when the physiological data exceed a preset normal range; and the information storage and health analysis module is used. According to the invention, synchronous transmission is carried out by means of the wireless local area network and the 5G network, and the data correction unit compares dual-network data errors and carries out linear correction, so that the timeliness and stability of data transmission are ensured, different scene requirements are met, the data accuracy is improved, and a reliable basis is provided for subsequent health analysis and decision-making; and the accuracy and adaptability of the intelligent old-age care system in the data circulation link are effectively improved.

Description

Technical Field

[0001] The present invention relates to the technical field of elderly care services, and in particular to a smart elderly care service management system based on the Internet of Things. Background Art

[0002] With the acceleration of the aging process of the global population, the traditional elderly care model faces many challenges. Against the background of social development and technological progress, the elderly have an increasing demand for the quality, personalization and health management of elderly care services. The Internet of Things can achieve interconnection between things and people, and further improve the efficiency of obtaining the physiological data of the elderly.

[0003] However, with current technology, traditional elderly care service management only relies on a single network or manual measurement of physiological data by medical staff, which affects the timeliness and stability of data transmission and leads to incorrect decision-making in elderly care services. Summary of the invention

[0004] In order to make up for the above shortcomings, the present invention provides a smart elderly care service management system based on the Internet of Things, aiming to improve the problems of low timeliness and stability of data transmission and inaccurate elderly care service decision-making.

[0005] In the first aspect, the present invention provides the following technical solution, a smart elderly care service management system based on the Internet of Things, comprising:

[0006] Health detection module: used to collect physiological data of the elderly in real time using sensor groups and smart wearable devices, and add timestamps to the collected data;

[0007] Information communication module: used to transmit and correct the collected data through wireless LAN and 5G technology;

[0008] Alarm module: used to sound an alarm when physiological data exceeds the preset normal range or when the elderly press the emergency call button;

[0009] Environmental monitoring module: used to monitor the indoor environment and collect external environmental data;

[0010] Information storage and health analysis module: used to arrange and store the collected timestamp information, conduct real-time comprehensive analysis, and generate health reports for the elderly.

[0011] Preferably, the health detection module includes a physiological data acquisition unit and a timestamp adding unit, wherein the physiological data acquisition unit is used to obtain physiological indicator data of the elderly through a sensor group, and the timestamp adding unit is used to add a corresponding time mark to the collected physiological data.

[0012] Preferably, the information communication module includes a data processing unit, a data transmission unit and a data correction unit. The data processing unit is used to uniformly convert data formats from different sensors and smart wearable devices into a standard format. The data transmission unit is used to simultaneously transmit the collected data in real time through wireless LAN technology and 5G network. The data correction unit is used to compare the data transmitted through the 5G network and the wireless LAN technology to obtain the error, and then estimate and correct the data of the error part through a linear relationship based on the accurate data points before and after the error.

[0013] Preferably, the alarm module includes a physiological data monitoring unit, an emergency call response unit and an alarm information triggering unit. The physiological data monitoring unit is used to compare the collected physiological data with the normal range threshold of each physiological indicator in real time. The emergency call response unit is used to monitor the trigger signal of the emergency call button in real time to directly perform an alarm operation. The alarm information triggering unit is used to determine whether the alarm condition is met based on the input of the physiological data monitoring unit.

[0014] Preferably, the environmental monitoring module includes an indoor environment monitoring unit and an external environment data collection unit, the indoor environment monitoring unit is used to monitor the temperature and air quality data distributed in different locations in the room, and the external environment data collection unit is used to obtain real-time weather conditions through an interface with the meteorological department or a third-party weather data service.

[0015] Preferably, the information storage and health analysis module includes a data storage unit, a data analysis unit and a health report generation unit, and the data storage unit is used to receive and organize physiological data and environmental data in a timestamp manner.

[0016] Preferably, the data analysis unit is used to take physiological data characteristics and environmental data characteristics as input through a multivariate regression model to analyze the results of the model output, and the health report generation unit is used to generate a health report, the report content including but not limited to current health status assessment, disease risk prediction, and health advice.

[0017] In a second aspect, the present invention provides the following technical solution, a smart elderly care service management method based on the Internet of Things, the method comprising the following steps:

[0018] S1. Health data detection: Start collecting various physiological data of the elderly through sensor groups and smart wearable devices;

[0019] S2. Data transmission and correction: The raw data from different sensors and smart wearable devices are converted into a unified format, and then the converted data is synchronously transmitted through the wireless LAN and 5G network. After comparing the data errors, they are corrected through linear relationships to obtain complete physiological data;

[0020] S3, Environmental Monitoring: Distributed monitoring of the temperature and air quality of the environment data in various places in the room, and adding timestamps corresponding to the physiological data;

[0021] S4, data storage: using timestamp as index, receiving and sorting physiological data from the health detection module and environmental data from the environmental monitoring module, storing them in corresponding databases by category, and establishing a health data archive for the elderly;

[0022] S5. Health analysis and report generation: The physiological data characteristics and environmental data characteristics of continuous time stamps are retrieved from the database as input, and a multivariate regression model is used for comprehensive analysis;

[0023] S6. Alarm monitoring and response: The collected physiological data are compared with the preset normal range thresholds of each physiological indicator in real time. If the physiological data exceeds the normal range, or the elderly press the trigger signal of the emergency call button, the alarm information trigger unit immediately starts the alarm operation.

[0024] In the third aspect, the invention provides the following technical solution: a computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the above-mentioned smart elderly care service management method based on the Internet of Things when executing the computer program.

[0025] In a fourth aspect, the present invention provides the following technical solution: a readable storage medium having a computer program stored thereon, and the computer program, when executed by a processor, implements the above-mentioned smart elderly care service management method based on the Internet of Things.

[0026] The present invention has the following beneficial effects:

[0027] 1. In the present invention, by synchronously transmitting via wireless LAN and 5G network, the data correction unit compares the data errors of the dual networks and corrects them linearly, which not only ensures the timeliness and stability of data transmission and meets the needs of different scenarios, but also improves data accuracy, providing a reliable basis for subsequent health analysis and decision-making, and effectively improving the accuracy and adaptability of the smart elderly care system in the data flow link.

[0028] 2. In the present invention, a multivariate regression model is used to analyze the correlation between data on health impacts, and a timestamp is added. The generated health report covers comprehensive and targeted content, which can not only provide medical staff with deeper insights and assist in precision medicine, but also enable elderly care service agencies to adjust services according to environmental changes, thereby enhancing the refinement level of smart elderly care services and the effectiveness of health management.

[0029] 3. In the present invention, the physiological data monitoring unit compares the physiological data with the threshold in real time, and the emergency call response unit quickly responds to the button trigger, which effectively shortens the emergency response time and improves the rescue efficiency. At the same time, it avoids false alarms and waste of resources, optimizes the collaborative rescue effect, and builds a solid line of defense for the life safety and health protection of the elderly. It greatly improves the reliability and flexibility of the smart elderly care service management system in emergency situations. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Figure 1 This is a schematic diagram of the framework of a smart elderly care service management system based on the Internet of Things proposed by the present invention;

[0031] Figure 2 This is a schematic diagram of a health detection module of a smart elderly care service management system based on the Internet of Things proposed by the present invention;

[0032] Figure 3 This is a schematic diagram of an information communication module of a smart elderly care service management system based on the Internet of Things proposed by the present invention;

[0033] Figure 4 This is a schematic diagram of an alarm module of a smart elderly care service management system based on the Internet of Things proposed by the present invention;

[0034] Figure 5 This is a schematic diagram of an environmental monitoring module of a smart elderly care service management system based on the Internet of Things proposed by the present invention;

[0035] Figure 6 This is a schematic diagram of an information storage and health analysis module of a smart elderly care service management system based on the Internet of Things proposed by the present invention;

[0036] Figure 7 This is a flow chart of a smart elderly care service management method based on the Internet of Things proposed by the present invention. DETAILED DESCRIPTION

[0037] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0038] Embodiment 1

[0039] Reference Figure 1 - Figure 6 In the first embodiment of the present invention, the present invention provides a smart elderly care service management system based on the Internet of Things, comprising:

[0040] Health detection module: used to collect physiological data of the elderly in real time using sensor groups and smart wearable devices, and add timestamps to the collected data;

[0041] Information communication module: used to transmit and correct the collected data through wireless LAN and 5G technology;

[0042] Alarm module: used to sound an alarm when physiological data exceeds the preset normal range or when the elderly press the emergency call button;

[0043] Environmental monitoring module: used to monitor the indoor environment and collect external environmental data;

[0044] Information storage and health analysis module: used to arrange and store the collected timestamp information, conduct real-time comprehensive analysis, and generate health reports for the elderly.

[0045] Specifically, the health detection module can collect the physiological data of the elderly in real time and add timestamps to achieve comprehensive and timely monitoring of health status. Multi-dimensional physiological data can reflect physical functions, provide a basis for subsequent timestamps to accurately manage data time series and associate traceable events, help medical staff accurately assess health, assist in diagnosis based on real-time data, and formulate preventive intervention measures. At the same time, it provides data support for elderly care service agencies, realizes personalized service customization and effect evaluation optimization, and comprehensively improves the quality of elderly care services and the level of targeted medical security.

[0046] The information communication module is used to build a high-speed, stable and reliable data transmission channel to ensure that the physiological and environmental data of the elderly can be delivered from the collection end to the storage and analysis end in a timely and complete manner. At the same time, the dual network data comparison is used to correct data deviations and ensure the timeliness of data transmission, so that medical staff and elderly care service personnel can grasp the elderly's condition in near real time for timely response. At the same time, the data accuracy is improved, and data errors caused by network interference or equipment failure are reduced, providing a reliable basis for health analysis and decision-making;

[0047] The alarm module can detect the health crisis and emergency needs of the elderly in a timely manner and send out warning signals, effectively shortening the emergency response time, improving the rescue efficiency, and building a key defense line for the life safety and health protection of the elderly. It greatly enhances the response capability and reliability of the smart elderly care service management system in emergency situations;

[0048] The environmental monitoring module can monitor indoor temperature, air quality and other data to ensure the comfort and safety of the living environment, create a high-quality and healthy living environment for the elderly, reduce health problems caused by environmental factors, and provide a basis for personalized adjustment of elderly care services based on subsequent environmental changes. It helps to deeply analyze the potential impact of the environment on the health of the elderly and further improve the refined service level and health management efficiency of the smart elderly care service management system;

[0049] The information storage and health analysis module can build a core data hub and intelligent analysis engine for the health information of the elderly through timestamps to ensure the integrity and traceability of the data, laying the foundation for long-term health tracking. At the same time, in the analysis process, multi-source data is integrated to mine potential associations. The generated health report comprehensively presents the current health status of the elderly, predicts disease risks and provides personalized suggestions, with significant results.

[0050] Reference Figure 2 The health detection module includes a physiological data acquisition unit and a timestamp adding unit. The physiological data acquisition unit is used to obtain the physiological index data of the elderly through the sensor group, and the timestamp adding unit is used to add corresponding time tags to the collected physiological data.

[0051] Specifically, the physiological data acquisition unit uses a sensor group to accurately and comprehensively obtain various physiological index data of the elderly, and can monitor the changes in the elderly's physical functions in real time from multiple dimensions, providing a rich and necessary basic data source for subsequent health assessment, disease diagnosis, and the formulation of personalized elderly care services;

[0052] By adding a timestamp unit, an accurate time tag can be attached to each piece of collected physiological data, so that the massive physiological data has a clear time sequence. When sorting and analyzing the data, it can clearly present the dynamic changes of the elderly's physical indicators over time, enhance the reliability and availability of the data of the entire health detection module, and make the smart elderly care service management system more rigorous, scientific and efficient in the health monitoring link.

[0053] Reference Figure 3 The information communication module includes a data processing unit, a data transmission unit and a data correction unit. The data processing unit is used to uniformly convert the data formats from different sensors and smart wearable devices into a standard format. The data transmission unit is used to simultaneously transmit the collected data in real time through wireless LAN technology and 5G network. The data correction unit is used to compare the data transmitted through 5G network and wireless LAN technology to obtain the error, and then estimate and correct the data of the error part through a linear relationship based on the accurate data points before and after the error.

[0054] Specifically, the data processing unit integrates heterogeneous data from different sensors and smart wearable devices and converts them into a standard format, laying a solid foundation for subsequent data transmission, efficient storage, and accurate analysis, avoiding transmission interruptions, storage errors, or analysis deviations caused by confusing data formats, ensuring that each link can be accurately connected and collaborated, and improving the stability and reliability of the system;

[0055] The data transmission unit uses the advantages of wireless LAN technology and 5G network to transmit the collected data in real time. Wireless LAN can provide a stable and high-speed transmission environment in fixed places such as indoors to meet the daily needs of large-scale data transmission. The 5G network, with its low latency, high bandwidth and wide coverage characteristics, ensures that data can be quickly delivered to the destination in mobile scenarios or when real-time requirements are extremely high, thereby improving the response speed and timeliness of elderly care services.

[0056] The data correction unit compares the data transmitted by the 5G network and the wireless LAN technology to obtain errors. During the data transmission process, different networks may cause data deviations due to signal interference, transmission path differences and other factors. These deviations should be discovered and corrected in time through comparison to ensure data accuracy. It reduces misjudgments or decision-making errors caused by data errors and provides more reliable data basis for health analysis.

[0057] Reference Figure 4 The alarm module includes a physiological data monitoring unit, an emergency call response unit and an alarm information trigger unit. The physiological data monitoring unit is used to compare the collected physiological data with the normal range threshold of each physiological indicator in real time. The emergency call response unit is used to monitor the trigger signal of the emergency call button in real time to directly perform an alarm operation. The alarm information trigger unit is used to determine whether the alarm condition is met based on the input of the physiological data monitoring unit.

[0058] Specifically, the physiological data monitoring unit continuously receives and analyzes the physiological data of the elderly collected by sensors and compares it with the normal range threshold, always paying attention to the subtle changes in various functional indicators of the elderly, and can keenly capture abnormal fluctuations in physiological data that may indicate health risks at the first time, greatly improving the foresight and initiative of the smart elderly care system in health monitoring;

[0059] The emergency call response unit is used to respond to emergencies of the elderly. When the elderly press the emergency call button, the unit will immediately take effect, ensuring that the elderly's distress signal can be transmitted as quickly as possible, increasing the possibility of the elderly receiving timely assistance in critical moments.

[0060] The alarm information trigger unit comprehensively considers the abnormal degree, duration and other relevant factors of physiological data to determine whether a comprehensive alarm process needs to be triggered, avoiding unnecessary waste of resources and rescue confusion, thereby optimizing the collaborative efficiency and rescue effect of the entire smart elderly care service management system when responding to emergencies.

[0061] Reference Figure 5 ,The environmental monitoring module includes an indoor environment monitoring unit and an ,external environment data collection unit. The indoor environment monitoring unit is used to monitor ,the temperature and air quality data at different locations in the room. The ,external environment data collection unit is used to obtain real-time weather conditions through ,the interface with the meteorological department or a third-party weather data service.

[0062] Specifically, the indoor environment monitoring unit uses sensors deployed at different locations in the room to accurately monitor temperature and air quality data, creating a comfortable and safe indoor living micro-environment for the elderly. It also provides a basis for elderly care service agencies to adjust service measures according to environmental conditions, adjust heating or cooling equipment in a timely manner according to temperature data, and arrange air purification or ventilation operations according to air quality conditions, thereby improving the refinement of elderly care services and the quality of life of the elderly.

[0063] Through the external environment data collection unit, with the help of the interface with the meteorological department or third-party weather data services, real-time weather conditions can be obtained efficiently, allowing elderly care service providers to know the outdoor weather changes in advance so that they can make adequate preparations for the elderly's outdoor activities in advance, reduce health risks and life inconveniences caused by sudden weather changes, and enable the elderly care service management system to better combine external environmental factors, comprehensively plan and optimize the content and process of elderly care services, and further improve the adaptability and humane care of smart elderly care services.

[0064] Reference Figure 6 The information storage and health analysis module includes a data storage unit, a data analysis unit and a health report generation unit. The data storage unit is used to receive and organize physiological data and environmental data in a timestamp manner.

[0065] Specifically, the data storage unit is used to receive and organize physiological data and environmental data from multiple sources with timestamps as indexes, ensuring the integrity and traceability of the data, so that massive data can be quickly located and called, providing a solid data foundation for subsequent data analysis.

[0066] Reference Figure 6 The data analysis unit is used to use the physiological data characteristics and environmental data characteristics as input through the multivariate regression model to analyze the results of the model output. The health report generation unit is used to generate a health report, and the report content includes but is not limited to current health status assessment, disease risk prediction, and health recommendations.

[0067] The data analysis unit uses multiple regression model data analysis technology, taking physiological data characteristics and environmental data characteristics as key inputs, and deeply explores the potential correlation and rules between the two and between them and the health status of the elderly, improves the accuracy of the analysis results, and significantly improves the quality and pertinence of services;

[0068] The health report generation unit not only covers the current health status assessment of the elderly, clearly presents whether various physiological indicators are normal, but also gives targeted health advice. It becomes an important reference for all parties to understand the overall health of the elderly and formulate corresponding strategies, promotes the effective transmission and sharing of health information, and facilitates medical staff to formulate accurate treatment and intervention plans.

[0069] Embodiment 2:

[0070] Reference Figure 7 In a second embodiment of the present invention, the present invention provides a smart elderly care service management method based on the Internet of Things, the method comprising the following steps:

[0071] S1. Health data detection: Start collecting various physiological data of the elderly through sensor groups and smart wearable devices;

[0072] S2. Data transmission and correction: The raw data from different sensors and smart wearable devices are converted into a unified format, and then the converted data is synchronously transmitted through the wireless LAN and 5G network. After comparing the data errors, they are corrected through linear relationships to obtain complete physiological data;

[0073] S3, Environmental Monitoring: Distributed monitoring of the temperature and air quality of the environment data in various places in the room, and adding timestamps corresponding to the physiological data;

[0074] S4, data storage: using timestamp as index, receiving and sorting physiological data from the health detection module and environmental data from the environmental monitoring module, storing them in corresponding databases by category, and establishing a health data archive for the elderly;

[0075] S5. Health analysis and report generation: The physiological data characteristics and environmental data characteristics of continuous time stamps are retrieved from the database as input, and a multivariate regression model is used for comprehensive analysis;

[0076] S6. Alarm monitoring and response: The collected physiological data are compared with the preset normal range thresholds of each physiological indicator in real time. If the physiological data exceeds the normal range, or the elderly press the trigger signal of the emergency call button, the alarm information trigger unit immediately starts the alarm operation.

[0077] Specifically, it covers health data detection, transmission correction, environmental monitoring, storage, analysis report generation, and alarm monitoring and response. It comprehensively and accurately grasps the health and living environment of the elderly, and builds a comprehensive health protection system for the elderly through multi-source data collection and processing. On the one hand, it can provide medical staff with detailed and reliable data basis to help them accurately diagnose, scientifically predict disease risks and formulate personalized medical care plans. On the other hand, it can enable elderly care service agencies to optimize service resource allocation, improve service quality and efficiency, and achieve accurate push and personalized customization of services. At the same time, the efficient alarm mechanism can respond quickly in an emergency and notify relevant parties in time to maximize the protection of the life safety and health of the elderly.

[0078] Embodiment 3

[0079] The third embodiment of the present invention is based on the same inventive concept. The present invention proposes a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, it implements the steps of the smart elderly care service management method based on the Internet of Things of the above-mentioned embodiment.

[0080] Embodiment 4

[0081] The fourth embodiment of the present invention is based on the same inventive concept. The present invention proposes a computer, which includes: a processor and a memory; the processor and the memory communicate with each other; the memory is used to store instructions; the processor is used to execute the instructions in the memory, and execute the smart elderly care service management method based on the Internet of Things of the above embodiment.

[0082] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0083] Finally, it should be noted that the above is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, it is still possible for those skilled in the art to modify the technical solutions described in the aforementioned embodiments or to make equivalent substitutions for some of the technical features therein. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A smart elderly care service management system based on the Internet of Things, characterized in that: include: Health detection module: used to collect physiological data of the elderly in real time using sensor groups and smart wearable devices, and add timestamps to the collected data; Information communication module: used to transmit and correct the collected data through wireless LAN and 5G technology; Alarm module: used to sound an alarm when physiological data exceeds the preset normal range or when the elderly press the emergency call button; Environmental monitoring module: used to monitor the indoor environment and collect external environmental data; Information storage and health analysis module: used to arrange and store the collected timestamp information, conduct real-time comprehensive analysis, and generate health reports for the elderly.

2. According to the IoT-based smart elderly care service management system of claim 1, it is characterized in that: The health detection module includes a physiological data acquisition unit and a timestamp adding unit. The physiological data acquisition unit is used to obtain physiological index data of the elderly through a sensor group, and the timestamp adding unit is used to add a corresponding time mark to the collected physiological data.

3. According to the IoT-based smart elderly care service management system of claim 1, it is characterized in that: The information communication module includes a data processing unit, a data transmission unit and a data correction unit. The data processing unit is used to uniformly convert the data formats from different sensors and smart wearable devices into a standard format. The data transmission unit is used to simultaneously transmit the collected data in real time through wireless local area network technology and 5G network. The data correction unit is used to compare the data transmitted through the 5G network and the wireless local area network technology to obtain the error, and then estimate and correct the data of the error part through a linear relationship based on the accurate data points before and after the error.

4. According to the IoT-based smart elderly care service management system of claim 1, it is characterized in that: The alarm module includes a physiological data monitoring unit, an emergency call response unit and an alarm information triggering unit. The physiological data monitoring unit is used to compare the collected physiological data with the normal range threshold of each physiological indicator in real time. The emergency call response unit is used to monitor the trigger signal of the emergency call button in real time to directly perform an alarm operation. The alarm information triggering unit is used to determine whether the alarm condition is met based on the input of the physiological data monitoring unit.

5. According to the IoT-based smart elderly care service management system of claim 1, it is characterized in that: The environmental monitoring module includes an indoor environment monitoring unit and an external environment data collection unit. The indoor environment monitoring unit is used to monitor the temperature and air quality data distributed in different locations in the room, and the external environment data collection unit is used to obtain real-time weather conditions through an interface with the meteorological department or a third-party weather data service.

6. According to the IoT-based smart elderly care service management system of claim 1, it is characterized in that: The information storage and health analysis module includes a data storage unit, a data analysis unit and a health report generation unit. The data storage unit is used to receive and organize physiological data and environmental data in a timestamp manner.

7. The smart elderly care service management system based on the Internet of Things according to claim 6 is characterized in that: The data analysis unit is used to use a multivariate regression model to take physiological data features and environmental data features as input and analyze the results of the model output. The health report generation unit is used to generate a health report, and the report content includes but is not limited to current health status assessment, disease risk prediction, and health advice.

8. A smart elderly care service management method based on the Internet of Things, characterized in that: A smart elderly care service management system based on the Internet of Things as described in any one of claims 1 to 7, the method comprising the following steps: S1. Health data detection: Start collecting various physiological data of the elderly through sensor groups and smart wearable devices; S2. Data transmission and correction: The raw data from different sensors and smart wearable devices are converted into a unified format, and then the converted data is synchronously transmitted through the wireless LAN and 5G network. After comparing the data errors, they are corrected through linear relationships to obtain complete physiological data; S3, Environmental Monitoring: Distributed monitoring of the temperature and air quality of the environment data in various places in the room, and adding timestamps corresponding to the physiological data; S4, data storage: using timestamp as index, receiving and sorting physiological data from the health detection module and environmental data from the environmental monitoring module, storing them in corresponding databases by category, and establishing a health data archive for the elderly; S5. Health analysis and report generation: retrieve the physiological data characteristics and environmental data characteristics of continuous time stamps from the database as input, and use the multivariate regression model for comprehensive analysis; S6. Alarm monitoring and response: The collected physiological data are compared with the preset normal range thresholds of each physiological indicator in real time. If the physiological data exceeds the normal range, or the elderly press the trigger signal of the emergency call button, the alarm information trigger unit immediately starts the alarm operation.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the smart elderly care service management method based on the Internet of Things as described in claim 8 is implemented.

10. A readable storage medium, characterized in that: The readable storage medium stores a computer program, and when the computer program is executed by the processor, the smart elderly care service management method based on the Internet of Things as claimed in claim 8 is implemented.

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