CN111657891A - Method for monitoring health condition of old people based on edge computing platform - Google Patents
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Abstract
The invention relates to an old people health condition monitoring method based on an edge computing platform, and belongs to the technical field of intelligent monitoring and internet of things communication. The monitoring system comprises a data acquisition layer, a data transmission layer and a data storage layer, wherein the data acquisition layer can be worn on the device; the method comprises the following steps: 1) building a data acquisition layer and acquiring data; 2) constructing an edge computing platform based on an MQTT protocol; 3) building a data storage layer, building a cloud database and writing interface and protocol information of the cloud database into an edge computing platform; 4) and forwarding the data through the edge computing platform module, cleaning the format of the acquired data by using a data cleaning rule, and finally storing the data into a cloud database. The method utilizes the low delay, high efficiency, high safety and super-strong real-time computing capability of the edge computing platform to upload and store the acquired vital sign data of the old in real time, thereby achieving real-time monitoring and data storage.
Description
Technical Field
The invention relates to an edge computing platform-based method for monitoring the health condition of old people, in particular to a method for monitoring the old people in a nursing home by applying wearable equipment to the old people in the nursing home by taking the edge computing platform as a management background, and belongs to the technical field of intelligent monitoring and Internet of things communication.
Background
With the improvement of the overall quality of the society, more and more old people are selected to be in the rest year in the nursing home among the old people with the gradually-huge base numbers. Therefore, the ability of the nursing home in all aspects is urgently to be enhanced. Among them, the medical care ability becomes the most important reference for the elderly to select the nursing home, and the state requires more than 50% of the nursing homes in the country to have the medical service ability as early as 2017. Meanwhile, the technology of the internet of things slowly permeates into a plurality of traditional industries, and the rest of the old people's homes are no exception. The combination of nursing in the nursing home and the Internet of things is advanced from the home, and the research on the intelligent nursing apartment for the old people is started a few years ago. China is still in the early development stage in the aspect of intelligence of the nursing home, the research on the aspect is rare at present, and the main problems are as follows:
1) most of the existing researches focus on the management of the service project process of the nursing home by using the Internet of things;
2) the medical care of the old people in most nursing homes still stays in the stage of completely depending on manpower;
3) the use of internet of things products is too complicated for the elderly;
therefore, the wearable device which is simple and portable and is designed for the elderly group is a part which is required to be realized on an intelligent road of an aged nursing home, and data collected by the wearable device can be uploaded and stored by means of an edge computing platform, so that the elderly group is better served. On the one hand, the old people in the nursing home can be provided with more convenient, safe, joyful and high-quality nursing life, and on the other hand, the operation cost of the nursing home is reduced to a certain extent by the design.
Disclosure of Invention
The invention aims to provide a method for monitoring the health condition of old people based on an edge computing platform, aiming at the technical current situation that the existing health monitoring system is low in efficiency, poor in safety and poor in real-time computing capability.
The core idea of the invention is as follows: the intelligent wearable equipment is combined with the edge computing platform, and the characteristics of low delay, high efficiency, high safety and super-strong real-time computing capability of the edge computing platform are utilized to upload and store the vital sign data of the old people collected by the wearable equipment in real time, so that the purposes of real-time monitoring and data storage are achieved.
The purpose of the invention is realized by the following technical scheme:
the monitoring system for the method for monitoring the health condition of the old people comprises a data acquisition layer, a data transmission layer and a data storage layer;
the data acquisition layer is a hardware layer and is used for acquiring vital sign data, namely wearable equipment; the data acquisition layer specifically comprises a development board, a temperature acquisition module, a heart rate acquisition module, a blood oxygen saturation acquisition module and a wireless transmission module;
the temperature acquisition module comprises 1 to 10 temperature sensors, the heart rate acquisition module comprises 1 to 10 heart rate sensors, the oxyhemoglobin saturation acquisition module comprises 1 to 10 oxyhemoglobin saturation sensors, and the wireless transmission module comprises but is not limited to a Bluetooth module, a Wi-Fi module, a CDMA module, a 4G module, a 5G module, a GPRS module and a ZigBee module;
the data transmission layer is an edge computing platform based on an MQTT protocol, and realizes corresponding functions by utilizing each module of the edge computing platform, wherein the edge computing platform comprises a main program module, an agent module, a message routing hub module, a remote message synchronization module and a function module;
loading each module in a main program module according to application configuration to start corresponding services, wherein the corresponding services comprise API interfaces with each module, completing state reporting and issuing in an agent module, providing MQTT-based message routing service by a message routing hub module, providing message synchronization service between the hub and remote MQTT service by a remote message synchronization module, providing function calculation service by a function module, and completing function instance management and function calling of message starting;
the data acquisition layer comprises a data storage layer and a data acquisition layer, wherein the data storage layer is a cloud database and specifically comprises an IoTHub object access module, a TSDB time sequence database module, a Rule Engine module and an IOTVIZ object visual module, data acquired by the data acquisition layer are stored in the cloud, and a user can check the acquired data at the current or designated moment at any time;
the IoTHub object access module is interconnected with the data transmission layer, data enters the IoTHub object access module in the data storage layer through a remote message synchronization module in the data transmission layer, format cleaning of the message data is completed through SQL statements in the Rule Engine module, the message data is stored in the TSDB time sequence database module, and the data can be seen to be displayed in various diagrams in the IOTVIZ object visual module;
the connection mode of each module in the monitoring system is as follows:
the heart rate acquisition module, the temperature acquisition module and the oxyhemoglobin saturation acquisition module are connected with the wireless transmission module; the wireless transmission module is connected with the hub message routing module, the hub message routing module is connected with the function module, and the function module is connected with the remote message synchronization module; the main program module is respectively connected with the hub message routing module, the function module, the remote message synchronization module and the agent module; the remote message synchronization module is connected with the IoTHub object access module, the IoTHub object access module is connected with the Rule Engine module, the Rule Engine module is connected with the TSDB timing database module, and the TSDB timing database module is connected with the IOTVIZ object visual module;
the functions of the modules in the monitoring system are as follows:
the development board in the data acquisition layer is used for receiving information of the temperature acquisition module, the heart rate acquisition module and the oxyhemoglobin saturation acquisition module and transmitting the information to the data transmission layer through the wireless transmission module;
the main program module of the data transmission layer is used for being connected with the API of the agent module, the message routing hub module, the remote message synchronization module of remote and the function module, and the agent module is used for finishing state reporting and issuing; the message routing hub module provides message routing service based on MQTT, the remote message synchronization module provides service for synchronizing messages between the hub and the remote MQTT service, and the function module is used for completing management of function instances and function call of message departure;
the IoTHub object access module in the data storage layer is interconnected with the remote message synchronization module in the data transmission layer; the TSDB time sequence database module is respectively matched with the Rule Engine module and the IOTVIZ object visual module to store the data collected by the data collection layer to a cloud, and specifically comprises the following steps: after format cleaning of message data is completed through SQL statements in the Rule Engine module, the message data are stored in the TSDB time sequence database module, and the TSDB time sequence database module provides data for the IOTVIZ object visual module, so that data displayed in various graph forms can be seen in the IOTVIZ object visual module.
The method for monitoring the health condition of the old comprises the following steps:
step one, building a data acquisition layer of the health condition monitoring system for the old, and acquiring data based on a sensor in the data acquisition layer, wherein the method specifically comprises the following steps:
1.1, connecting the development board with each data acquisition module and each wireless transmission module;
the temperature acquisition module acquires temperature data of the head and the fingertips, the heart rate acquisition module acquires heart rate data of the fingertips, the wrists and the chest, and the oxyhemoglobin saturation acquisition module acquires oxyhemoglobin saturation data of the fingertips and the wrists;
1.2 read human body temperature through temperature sensor, data acquisition layer passes through heart rate sensor and measures IBI and BPM information based on the photoplethysmography, and then calculates the rhythm of the heart, specifically is: obtaining IBI through measurement by using a photoplethysmography, and then obtaining BPM through calculation according to a formula BPM multiplied by IBI which is 60;
wherein IBI, i.e. Interval Beats in ms, pulse Interval; BPM, Beats per Minute, Beats per Minute; the calculation of BPM involves measurement of IBI;
1.3 measuring AC and DC component information of two LED lamps based on a photoelectric volume method through a blood oxygen saturation sensor, and further calculating the blood oxygen saturation SaO2Specifically, the alternative lighting of a common LED lamp and an infrared LED lamp is utilized for measurement, and a value R is calculatedvalueLooking up the table again to determine the current SaO2；
Wherein R isvalueThe calculation formula (1):
wherein, ACL1Indicating the direct current component, DC, of a conventional LED lamp L1L1AC component, AC, of a common LED lamp L1L2Representing the direct component, DC, of the infrared LED lamp L2L2An alternating current component representing the infrared LED lamp L2;
step two, building a data transmission layer, specifically:
2.1 after the data acquisition layer finishes the acquisition of the body temperature, the heart rate and the oxyhemoglobin saturation data, utilizing a wireless transmission module of the data acquisition layer to send the acquired data and the equipment ID to a hub message routing module in a wireless transmission mode;
2.2, eliminating abnormal data in the function module by a Graves test method, and averaging the data after the abnormal data are eliminated if more than one sensor is adopted for a certain vital sign;
2.3 after the remote message synchronization module configures the address, the user name, the password and other information of the cloud database, the data is sent to the data storage layer by the data transmission layer through the remote message synchronization module;
2.4agent module is responsible for reporting the state information of the main program to the cloud;
2.5 programming API interfaces among all modules in the main program module;
step three, building a data storage layer, specifically:
3.1 building an IoTHub access module, and filling the address, the user name and the password into a remote message synchronization module of a data transmission layer;
3.2 creating a Rule Engine, creating Rule names, examples and themes, and cleaning the data format through SQL statements;
3.3 creating a TSDB time sequence database, and using the Rule created in the Rule Engine to format and clean the data transmitted by the data transmission layer and store the data in the TSDB time sequence database;
3.4 creating an IOTVIZ object visual module, calling data in the TSDB time sequence database, and presenting the data in a chart form.
Advantageous effects
The invention relates to a method for monitoring the health condition of old people based on the research of an edge computing platform, which has the following beneficial effects compared with the prior method for monitoring the health condition:
1. different from most of the existing Internet of things management systems designed aiming at the operation management mode of the nursing home, the measurement group of the method is the old people of the nursing home, and the purpose is to realize the physical condition monitoring of the old people through a new technical means;
2. the health condition monitoring system fully considers the conflict and rejection psychology of most of the old people to emerging products, and has no part requiring deep understanding and manual operation of the old people, so the learning cost of the old people is greatly reduced;
3. the invention has low requirement on hardware, requires more common modules and sensors, has lower development cost and is suitable for popularization in the nursing home;
4. the system adopts the edge computing technology of the emerging technology in the direction of the Internet of things, and has the characteristics of high speed, high efficiency and strong safety;
5. according to the invention, the traditional wearable equipment is combined with the edge calculation, so that the application field of traditional hardware is expanded on one hand, and the technology of the Internet of things is utilized on the other hand.
Drawings
FIG. 1 is a block diagram of an edge computing platform based geriatric health monitoring system of the present invention;
FIG. 2 is a flow chart of an implementation of a method by which an edge computing platform based elderly health monitoring system of the present invention is implemented;
fig. 3 is a diagram of internal connection of the wearable device, illustrating a hardware connection manner of the data acquisition layer.
Detailed Description
The present invention relates to a system for monitoring health status of elderly people based on edge computing platform, which is further described in detail with reference to the accompanying drawings and embodiments.
The method will be described in detail with reference to the above mentioned figures for the system for monitoring the health condition of the elderly based on the research of the edge computing platform.
Example 1
This example describes the application of the system according to the invention to a small-scale nursing home in a country. Since the economy of the rural retirement home is not great, the selection of wearable device sensors and development boards should be simplified as much as possible.
Fig. 1 is a structural diagram of the health condition monitoring system for the elderly, which comprises three modules, namely a data acquisition layer, a data transmission layer and a data storage layer. Each module is explained in detail in this embodiment. The data acquisition layer comprises a wireless transmission module, a temperature data acquisition module, a heart rate data acquisition module and an oxyhemoglobin saturation acquisition module, and data and equipment ID acquired by the heart rate, temperature and oxyhemoglobin saturation acquisition module are transmitted to the data transmission layer through the wireless transmission module. The data transmission layer comprises a main program module, an agent module, a message routing hub module, a remote message synchronization module and a function module, data in the data acquisition layer is transmitted to the function module through the hub message routing module, abnormal data are eliminated through a Grabbs inspection method through the function module, and then the abnormal data are transmitted to the remote message synchronization module. The data storage layer comprises an IoTHub object access module, a TSDB time sequence database module, a Rule Engine module and an IOTVIZ object visual module, the remote message transmission module in the data transmission layer transmits data to the IoTHub object access module, after the data format is cleaned by the Rule Engine, the data enters the TSDB time sequence database and is displayed in the IOTVIZ object visual module in a chart form.
Fig. 2 is a flowchart illustrating an implementation of the present health monitoring system for the elderly, which will be described in detail below.
Step one, building a data acquisition layer, specifically comprising the following steps:
firstly, completing the connection of a sensor and a development board;
in this embodiment, select to use the development board for Arduino Uno R3, temperature Sensor selects one to use DS18B20 at the fingertip, and heart rate Sensor selects one to use the Pulse Sensor at the fingertip, and blood oxygen saturation Sensor adopts one to use the MAX30102 Sensor at the fingertip, and bluetooth HC-05 module is selected for use to wireless transmission module. As shown in fig. 3, each sensor is connected to the Arduino motherboard.
The VCC of the temperature sensor DS18B20 is connected with a power supply (5V or 3.3V), the DQ is connected with a set data transmission serial port, and the GND is grounded (namely GND on the development board);
s of the heart rate Sensor is a data transmission end and is connected with a data transmission serial port, and the plus is connected with a power supply (5V or 3.3V); "-" Ground (GND);
VIN of the blood oxygen saturation sensor MAX30102 is connected with a power supply (5V or 3.3V), SDA is connected with SDA (if no serial port of the SDA is available, the serial port of the A4 can also be connected), SCL is connected with SCL (if no serial port of the SCL is available, the serial port of the A5 can also be connected) on the development board, and GND is Grounded (GND);
the wireless transmission module selects an HC-05 Bluetooth module adaptive to Arduino. The +5V/VCC is connected with a power supply (5V or 3.3V), the GND is Grounded (GND), and the RX and the TX are communication interfaces and can be set in a program;
it should be noted here that when configuring the communication serial ports for each module, the serial ports 0 and 1 are the communication serial ports of the development board itself, and cannot occupy.
And compiling a corresponding data acquisition method for each sensor after the connection is finished.
The collection of old person's health body temperature directly acquires and prints through temperature acquisition order.
The idea of the configuration of the heart rate sensor and the blood oxygen saturation sensor is to use a photoelectric volume method. The method utilizes different light transmittance of human tissues during the pulsation of blood vessels to measure the pulse, a light source and a photoelectric transducer are arranged in a sensor, when light beams penetrate through peripheral blood vessels of a human body, arterial pulsation is filled with blood, so that the volume is changed, and the light transmittance of the light source is changed. At this time, the receiver converts the light into an electrical signal, amplifies and outputs the converted electrical signal, and the change period of the electrical signal is the pulse rate.
According to the definition of blood oxygen saturation, it is expressed as formula (2):
among them, SaO2For blood oxygen saturation, HbO2Oxygen and hemoglobin, Hb is hemoglobin,
is the oxygen and hemoglobin concentration, i.e. blood oxygen concentration, CHbIs the hemoglobin concentration;
the blood oxygen saturation is measured by alternating illumination of two LED lamps (RED LED and IR LED), the value R is calculated and looked up to determine the current SaO2；
The calculation formula is (3):
wherein, ACREDRepresenting the direct current component, DC, of the RED lampREDRepresenting the AC component of the RED lamp, ACIRDC represents the direct current component of IR lamps (infrared lamps)IRTo representAc component of IR lamp (infrared lamp);
the heart rate is calculated by means of equation (4):
BPM×IBI＝60 (4)
wherein IBI is obtained by a photoplethysmography, and then BPM is calculated by using the formula (4).
And step two, configuring a data transmission layer. The main program is first configured. In the main program, the mode selects a docker container, so that the flexibility and the expandability of the system are improved; a log storage path and a log grade (debug, info, war or error) need to be set in the loader, and here, debug is selected; and if the configuration is not different from the default setting, the configuration is not needed.
Then, the Baetyl application is configured. What can be configured in the application configuration are application version, service list services of the application, and storage volume list volumes. Wherein, in the services service list, the name is the service name; the image is a service inlet, the docker container mode represents a service mirror image, and the native process mode represents the position of a service operation package; replica is the number of service copies, typically set to 1; mount is a storage volume mapping list, and under the directory, the name, the storage path and the authority (read only or not) of each storage volume need to be configured; policy is a restart policy, and always restart, a default option, no (no restart), on-failure (restart when a service exception exits) can be configured; the memory is a memory configuration, and can configure a memory and an exchange space available for service strength; the pids are the process configurations, the number of processes that the primary configuration service can create. In the list of volumes storage volumes, the names of all storage volumes and the path on the host need to be listed.
Finally, configuring a Baetyl specific module. The module is provided with three sub-modules, namely a baeyl-agent (configuration item for butting a BIE cloud management suite), a baeyl-hub (including monitoring address, certificate configuration, state configuration and the like), and a baeyl-function-manager (including Client related information configuration, routing, function list and log configuration). Only the related information of remote needs to be configured in the Baetyl-Agent, and the related information mainly comprises mqtt (id, address, certificate, public and private key path and the like), http (BIE cloud http channel setting), report (Agent reports cloud configuration) and destination (Agent accepts cloud issuing configuration). The Baetyl-hub is configured with information such as listening address listen (any of tcp/ssl/ws/wss), certificate, subject topic, name of message, address, and the like. In the Baetyl-function-manager, the ID, address and user name of the Client connection hub, the subscription sub of the routing configuration rule rules rule, the function, and the topic and the quality of service qos of the computation result publication publish need to be written in detail. In addition, each of the above-mentioned parts needs to configure the storage path and the log level at the end.
And step three, configuring a data storage layer. Firstly, establishing IoTHub matter access, selecting 'North China-Beijing' as a region, filling a project name, and selecting 'data type' as a project type. The address, username and password are then configured into the remote message synchronization module of Baetyl.
Fx, corresponding information is configured in MQTT.fx, tcp/ssl/ws/wss can be selected, and tcp is taken as an example in the embodiment. Fill out Profile Name, Profile Type selects MQTT Broker. The Broker Address and Broker Port are filled in with the data in BIEIoTHub. After "appliance", can communicate with the cloud through MQTT.
A data cleansing rule is created. And selecting a Rule Engine in the BIE, writing an SQL statement to complete cleaning of a data format after filling in a Rule name, an instance and a subject.
A database is created, and a time sequence database TSDB is selected in the BIE. And after the region, the database name, the written limit, the maximum time sequence, the query limit and the purchase duration are filled, confirming the order and completing the creation of the time sequence database.
Creating an IOTVIZ object in the BIE. And presenting the collected data in a chart mode. Third party data may also be selected visually, and since the data has been uploaded to the TSDB timing database module here, the data in the TSDB timing database module is used directly.
Example 2
This example describes the application of the system according to the invention to medium-sized nursing homes in towns. Compared with the small-scale nursing home in the country, the medium-scale nursing home in the town has better economic conditions and the elderly pay more attention to the old, so that a development board and a sensor module with higher quality can be selected.
Step one, building a data acquisition layer.
In the embodiment, the selected development board is STM32F 103; the temperature acquisition module comprises 3 DS18B20 sensors which are respectively applied to fingertips, heads and wrists of the old; the heart rate acquisition module comprises 3 Pulse Sensor sensors which are respectively applied to fingertips, chest and wrists of the old; the blood oxygen saturation acquisition module comprises 3 MAX30102 modules which are respectively applied to fingertips, chest and wrists of the old; the wireless transmission module comprises a GPRS module, a Bluetooth module and a Wi-Fi module. The connection mode and data acquisition algorithm of each sensor are the same as those in embodiment 1.
And step two, building a data transmission layer.
The main program, agent module, hub message routing module, and remote message synchronization module are the same as those in embodiment 1. In the function module, in addition to eliminating abnormal values from the data acquired by each sensor by using the grassroots test method, the data acquired by the same sensor at different positions needs to be averaged to obtain more accurate vital sign data.
And step three, building a data storage layer.
The IoTHub object access module, Rule Engine module and IOTVIZ object visual module are the same as those in embodiment 1. However, in consideration of the enlargement of the size of the nursing home, the amount of data collected increases. Therefore, when the TSDB time sequence database module is created, a larger writing amount and a larger query amount can be selected. In this embodiment, the created write quota is 20000000 points/month, and the query quota selects 20000000 query units/month.
Example 3
This example describes the application of the system according to the invention to a large-scale urban rest home. Large-scale retirement homes located in cities usually have sufficient capital, and the elderly who choose such retirement homes are also more concerned about the level of medical care and the quality of care. So that the development boards and sensor modules which are currently more expensive on the market can be selected.
Step one, building a data acquisition layer.
In this embodiment, the development board is selected as Raspberry type Raspberry Pi 4B; the temperature acquisition module comprises 10 DS18B20 sensors, wherein 5 sensors are applied to fingertips of the old, 3 sensors are applied to the wrist, and 2 sensors are applied to the head; the heart rate acquisition module comprises 10 Pulse Sensor sensors, wherein 5 sensors are applied to fingertips, 3 sensors are applied to wrists, and 2 sensors are applied to the chest; the blood oxygen saturation acquisition module comprises 10 MAX30102 sensors, 5 sensors are applied to fingertips, 3 sensors are applied to wrists, and 2 sensors are applied to chest; the wireless transmission module comprises five wireless transmission devices of 4G, 5G, Wi-Fi, Bluetooth and ZigBee. The attachment method was the same as in example 1.
And step two, building a data transmission layer.
The main program, agent module, hub message routing module, and remote message synchronization module are the same as those in embodiment 1. Since the modules adopted for each part in this embodiment are not unique, in order to ensure the accuracy of the data, the data collected by different sensors at the same part and in the same data collection type need to be averaged, except that the abnormal values of the data collected by each sensor are eliminated by using the grassbs test method. When data are uploaded, the data are classified according to the same type, and mean values of fingertip temperature, wrist temperature, head temperature, fingertip heart rate, wrist heart rate, chest heart rate, fingertip blood oxygen saturation, wrist blood oxygen saturation and chest blood oxygen saturation are uploaded respectively.
And step three, building a data storage layer.
The IoTHub object access module and the IOTVIZ object visual module are the same as those in embodiment 1. In the Rule Engine module, the cleaning Rule of the data needs to be refined due to the refinement of the type of the uploaded data. In addition, when the TSDB time sequence database module is created, the data volume is increased due to the increase of the size of the nursing home. Therefore, a larger write credit and query credit are required to be selected. In this embodiment, the created write quota is 1000000000 points/month, and the query quota is 100000000 query units/month.
In summary, the elderly health condition monitoring system based on the marginal computing platform research provided by the invention has the advantages that the wearable device is simple in functional structure, the learning cost for the elderly is extremely low, the required functions can be realized relatively simply, and the blank of China in the aspect of intelligent nursing homes is filled to a certain extent. Meanwhile, as can be seen from the embodiment, the edge computing platform is used as the system background, and the characteristics of high edge computing speed, high efficiency and safety are indeed shown.
The above-described embodiments are further illustrative of the present invention and are not intended to limit the scope of the invention, which is to be protected by the accompanying claims.
Claims (10)
1. An old people health condition monitoring method based on an edge computing platform is characterized in that: the monitoring system comprises a data acquisition layer, a data transmission layer and a data storage layer;
the data acquisition layer is a hardware layer and is used for acquiring vital sign data, namely wearable equipment; the data acquisition layer specifically comprises a development board, a temperature acquisition module, a heart rate acquisition module, a blood oxygen saturation acquisition module and a wireless transmission module;
the data transmission layer is an edge computing platform based on an MQTT protocol, and realizes corresponding functions by utilizing each module of the edge computing platform, wherein the edge computing platform comprises a main program module, an agent module, a message routing hub module, a remote message synchronization module and a function module;
the data acquisition layer comprises a data storage layer and a data acquisition layer, wherein the data storage layer is a cloud database and specifically comprises an IoTHub object access module, a TSDB time sequence database module, a Rule Engine module and an IOTVIZ object visual module, data acquired by the data acquisition layer are stored in the cloud, and a user can check the acquired data at the current or designated moment at any time;
the connection mode of each module in the monitoring system is as follows:
the heart rate acquisition module, the temperature acquisition module and the oxyhemoglobin saturation acquisition module are connected with the wireless transmission module; the wireless transmission module is connected with the hub message routing module, the hub message routing module is connected with the function module, and the function module is connected with the remote message synchronization module; the main program module is respectively connected with the hub message routing module, the function module, the remote message synchronization module and the agent module; the remote message synchronization module is connected with the IoTHub object access module, the IoTHub object access module is connected with the Rule Engine module, the Rule Engine module is connected with the TSDB timing database module, and the TSDB timing database module is connected with the IOTVIZ object visual module;
the method for monitoring the health condition of the old comprises the following steps:
step one, building a data acquisition layer of the health condition monitoring system for the old, and acquiring data based on a sensor in the data acquisition layer, wherein the method specifically comprises the following steps:
1.1, connecting the development board with each data acquisition module and each wireless transmission module;
the temperature acquisition module acquires temperature data of the head and the fingertips, the heart rate acquisition module acquires heart rate data of the fingertips, the wrists and the chest, and the oxyhemoglobin saturation acquisition module acquires oxyhemoglobin saturation data of the fingertips and the wrists;
1.2 read human body temperature through temperature sensor, data acquisition layer passes through heart rate sensor and measures IBI and BPM information based on the photoplethysmography, and then calculates the rhythm of the heart, specifically is: obtaining IBI through measurement by using a photoplethysmography, and then obtaining BPM through calculation according to a formula BPM multiplied by IBI which is 60;
wherein IBI, i.e. Interval Beats in ms, pulse Interval; BPM, Beats per Minute, Beats per Minute; the calculation of BPM involves measurement of IBI;
1.3 measuring AC and DC component information of two LED lamps based on a photoelectric volume method through a blood oxygen saturation sensor, and further calculating the blood oxygen saturation SaO2Specifically, the alternative lighting of a common LED lamp and an infrared LED lamp is utilized for measurement and the numerical value is calculatedRvalueLooking up the table again to determine the current SaO2；
Wherein R isvalueThe calculation formula (1):
wherein, ACL1Indicating the direct current component, DC, of a conventional LED lamp L1L1AC component, AC, of a common LED lamp L1L2Representing the direct component, DC, of the infrared LED lamp L2L2An alternating current component representing the infrared LED lamp L2;
step two, building a data transmission layer, specifically:
2.1 after the data acquisition layer finishes the acquisition of the body temperature, the heart rate and the oxyhemoglobin saturation data, utilizing a wireless transmission module of the data acquisition layer to send the acquired data and the equipment ID to a hub message routing module in a wireless transmission mode;
2.2, eliminating abnormal data in the function module by a Graves test method, and averaging the data after the abnormal data are eliminated if more than one sensor is adopted for a certain vital sign;
2.3 after the remote message synchronization module configures the address, the user name, the password and other information of the cloud database, the data is sent to the data storage layer by the data transmission layer through the remote message synchronization module;
2.4agent module is responsible for reporting the state information of the main program to the cloud;
2.5 programming API interfaces among all modules in the main program module;
step three, building a data storage layer, specifically:
3.1 building an IoTHub access module, and filling the address, the user name and the password into a remote message synchronization module of a data transmission layer;
3.2 creating a Rule Engine, creating Rule names, examples and themes, and cleaning the data format through SQL statements;
3.3 creating a TSDB time sequence database, and using the Rule created in the Rule Engine to format and clean the data transmitted by the data transmission layer and store the data in the TSDB time sequence database;
3.4 creating an IOTVIZ object visual module, calling data in the TSDB time sequence database, and presenting the data in a chart form.
2. The method for monitoring the health condition of the elderly based on the edge computing platform as claimed in claim 1, wherein: the temperature acquisition module in the relied monitoring system comprises 1 to 10 temperature sensors.
3. The method for monitoring the health condition of the elderly based on the edge computing platform as claimed in claim 1, wherein: the heart rate acquisition module in the relied-upon monitoring system includes 1 to 10 heart rate sensors.
4. The method for monitoring the health condition of the elderly based on the edge computing platform as claimed in claim 1, wherein: the blood oxygen saturation acquisition module in the supported monitoring system comprises 1-10 blood oxygen saturation sensors.
5. The method for monitoring the health condition of the elderly based on the edge computing platform as claimed in claim 1, wherein: the wireless transmission module in the supported monitoring system comprises but is not limited to a Bluetooth module, a Wi-Fi module, a CDMA module, a 4G module, a 5G module, a GPRS module and a ZigBee module.
6. The method for monitoring the health condition of the elderly based on the edge computing platform as claimed in claim 1, wherein: the method comprises the steps that a main program module in a relied monitoring system loads each module according to application configuration to start corresponding services, the API interfaces with each module are included, state reporting and issuing are completed in an agent module, a message routing hub module provides message routing services based on MQTT, a remote message synchronization module provides messages synchronization services of the hub and the remote MQTT, and a function module provides function calculation services to complete function instance management and function calling of message starting.
7. The method for monitoring the health condition of the elderly based on the edge computing platform as claimed in claim 1, wherein: interconnection with a data transmission layer is realized in an IoTHub object access module in a supported monitoring system, data enters the IoTHub object access module in a data storage layer through a remote message synchronization module in the data transmission layer, format cleaning of the message data is completed through SQL statements in a RuleEngine rule engine module, the message data is stored in a TSDB time sequence database module, and the data can be seen to be displayed in various graph forms in an IOTVIZ object visual module.
8. The method for monitoring the health condition of the elderly based on the edge computing platform as claimed in claim 1, wherein: the development board in the data acquisition layer of the relied monitoring system is used for receiving the information of the temperature acquisition module, the heart rate acquisition module and the oxyhemoglobin saturation acquisition module and transmitting the information to the data transmission layer through the wireless transmission module.
9. The method for monitoring the health condition of the elderly based on the edge computing platform as claimed in claim 1, wherein: the main program module of the data transmission layer in the supported monitoring system is used for being connected with the API of the agent module, the message routing hub module, the remote message synchronization module and the function module, and the agent module is used for finishing state reporting and issuing; the message routing hub module provides message routing service based on MQTT, the remote message synchronization module provides service for synchronizing messages between the hub and the remote MQTT, and the function module is used for completing management of function instances and function calling of message departure.
10. The method for monitoring the health condition of the elderly based on the edge computing platform as claimed in claim 1, wherein: interconnection between an IoTHub object access module in a data storage layer and a remote message synchronization module in a data transmission layer is realized depending on an IoTHub object access module in a monitoring system; the TSDB time sequence database module is respectively matched with the Rule Engine module and the IOTVIZ object visual module to store the data collected by the data collection layer to a cloud, and specifically comprises the following steps: after format cleaning of message data is completed through SQL statements in the Rule Engine module, the message data are stored in the TSDB time sequence database module, and the TSDB time sequence database module provides data for the IOTVIZ object visual module, so that data displayed in various graph forms can be seen in the IOTVIZ object visual module.
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