CN108173967A - A kind of on-line module of wearable built-in support cellular data function - Google Patents
A kind of on-line module of wearable built-in support cellular data function Download PDFInfo
- Publication number
- CN108173967A CN108173967A CN201810092054.3A CN201810092054A CN108173967A CN 108173967 A CN108173967 A CN 108173967A CN 201810092054 A CN201810092054 A CN 201810092054A CN 108173967 A CN108173967 A CN 108173967A
- Authority
- CN
- China
- Prior art keywords
- module
- built
- measured value
- wearable
- cellular data
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/02—Protocols based on web technology, e.g. hypertext transfer protocol [HTTP]
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01D—MEASURING NOT SPECIALLY ADAPTED FOR A SPECIFIC VARIABLE; ARRANGEMENTS FOR MEASURING TWO OR MORE VARIABLES NOT COVERED IN A SINGLE OTHER SUBCLASS; TARIFF METERING APPARATUS; MEASURING OR TESTING NOT OTHERWISE PROVIDED FOR
- G01D21/00—Measuring or testing not otherwise provided for
- G01D21/02—Measuring two or more variables by means not covered by a single other subclass
-
- G—PHYSICS
- G08—SIGNALLING
- G08C—TRANSMISSION SYSTEMS FOR MEASURED VALUES, CONTROL OR SIMILAR SIGNALS
- G08C17/00—Arrangements for transmitting signals characterised by the use of a wireless electrical link
- G08C17/02—Arrangements for transmitting signals characterised by the use of a wireless electrical link using a radio link
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Engineering & Computer Science (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Arrangements For Transmission Of Measured Signals (AREA)
Abstract
The present invention provides a kind of on-line module of wearable built-in support cellular data function, including cellular communication unit and the cellular data collecting unit for being built in wearable device, the cellular data collecting unit for being built in wearable device includes field data acquisition terminal.The error calibration method arranged and proposed by the system to acquisition terminal realizes efficient, the accurately wearable medical device data acquisition based on Internet of Things.
Description
Technical field
The invention belongs to data collecting fields, and in particular to a kind of online of wearable built-in support cellular data function
Module.
Background technology
It is world information industry third after computer, internet and mobile radio communication that Internet of Things, which is recognized by the world as,
Secondary tide.Internet of Things is the network that realization person to person, people and object, object and object interconnect comprehensively premised on perception.At this behind,
It is then that various microchips are implanted on object, the various information of physical world is obtained with these sensors, then pass through part
The various telecommunication network interactions such as wireless network, internet, mobile radio communication are transmitted, so as to fulfill the perception to the world.With generation
National governments of boundary are to the policy inclination of Internet of Things industry and the support energetically of enterprise and input, and Internet of Things industry is by urging rapidly
It is raw, it is shown according to data both domestic and external, Internet of Things has carried out great development from 1999 and penetrated into each industry neck so far
Domain.It is also envisioned that be more and more industry fields and technology, using meeting and Internet of Things generate intersection, to Internet of Things direction
Transformation optimization has become the developing direction in epoch.
Medical Devices distributed areas due to being used for personal medical care and health purpose are wide, distribution density is generally relatively low, need
Real time monitoring is realized by the system of the structures such as sensor, gateway, cloud server, sensor node acquisition, transmission information all need
The energy is consumed, gateway needs constantly to send gathered data to cloud server and cloud server needs are handled largely
Gathered data, to the arrangement of various acquisition system terminals, the mixing of various data, the removal of noise and a variety of mistakes brought
Difference brings very big challenge to the cellular data collecting unit for being built in wearable Medical Devices, also becomes general at present interior
It is placed in the cellular data collecting unit problem encountered of wearable Medical Devices.
Invention content
In view of above analysis, it is a primary object of the present invention to provide a kind of wearable built-in support cellular data function
On-line module, including cellular communication unit and the cellular data collecting unit for being built in wearable device, described be built in can
The cellular data collecting unit of wearable device includes field data acquisition terminal.By to the system of acquisition terminal arrangement and
The error calibration method of proposition realizes efficient, the accurately wearable medical device data acquisition based on Internet of Things.
The purpose of the present invention is what is be achieved through the following technical solutions.
A kind of on-line module of wearable built-in support cellular data function, including cellular communication unit and be built in can
The cellular data collecting unit of wearable device, the cellular communication unit receive described in be built in the cellular data of wearable device
The data information of collecting unit transmission.
The cellular data collecting unit for further, being built in wearable device includes including field data acquisition terminal,
Error correcting system, ZigBee-network module, field data acquisition terminal, live control manipulation node, operating mechanism, wireless biography
Defeated module, display module, memory module, serial communication modular, clock module, power module, wherein operation module, central processing
System respectively with power module, error correcting system, wireless transport module, display module, memory module, serial communication modular,
Clock module, ZigBee-network module, live manipulation operation node are connected, live control manipulation node also with power module phase
Connection, while be connected by corresponding operating module with operating mechanism, to realize the adjusting to medical scene, field data acquisition
Terminal is connect by error correcting system with central processing system.The acquisition terminal connects multiple medical environment sensors, such as
The corresponding sensors such as the various parameters of measurement temperature, humidity, oxygen concentration and gas concentration lwevel.
Further, the data processing system includes following processing step：
Ambient measurements are obtained by multiple sensors, wherein each sensor is carried out ambient measurements and obtained with some cycles
It takes, the data that different time points measure are denoted as xi, wherein i=1,2,3 ..., a nearest measured value is often obtained, all with being
Preset measurement limit value of uniting is compared, if measured value exceeds limits, alarm prompt is carried out, if measured value
In limits, then following steps are carried out.
By this measured value xiMake difference successively with measured value before, obtain xi-xm, wherein m=1,2,3 ... i-
1, if the difference of any two of which measured value is no more than error limit, it is calculated as below：
Z (m | m-1)=Z (m-1 | m-1)
S (m | m-1)=S (m-1 | m-1)+T
Z (m | m)=Z (m | m-1)+U (m) (x (m)-Z (m | m-1))
Wherein
S (m | m)=(1-U (m)) S (m | m-1)
Wherein, wherein, Z is the system mode at m moment, and S (m-1tm-1) is the most effective value at m-1 time points, S (m | m-1)
It is according to the above-mentioned most effective assessed value being worth to, S is the covariance of Z (m | m), and T is the covariance of systematic procedure, and U systems increase
Benefit, Q are variance；
It is iterated by above-mentioned formula, you can obtain satisfactory measurement value sensor.If two measurements
When the difference of value is more than error limit, then Bayesian Estimation and wavelet transformation is carried out to measured value or estimated with neural network
Meter,
Finally obtained measured value is calculated as below：
Wherein, xiFor the measured value after above-mentioned calculating iteration, hiFor corresponding weights, W is final virtual value.
Description of the drawings
Fig. 1 is the on-line module of the wearable built-in support cellular data function of the present invention.
Fig. 2 is the general knot of cellular data collecting unit for being built in wearable Medical Devices the present invention is based on Internet of Things
Structure block diagram.
Wherein 1 is centric acquisition system, and 2 be error correcting system, and 3 be power module, and 4 be live control manipulation node, 5
It is memory module for display module, 6,7 be serial communication modular, and 8 be clock module, and 9 be wireless transport module, and 10 be ZigBee
Network module, 11 be field data acquisition terminal, and 12-16 is respectively environmental sensor, and 17 be operation module, and 18 be operation machine
Structure,
Specific embodiment
As shown in Figure 1, a kind of on-line module 100 of wearable built-in support cellular data function, including cellular communication
Unit 200 and the cellular data collecting unit 300 for being built in wearable device, the cellular communication unit 200 are received in described
It is placed in the data information that the cellular data collecting unit 300 of wearable device transmits.
The cellular data collecting unit 300 for being built in wearable device including field data as shown in Fig. 2, acquire eventually
End include 1, error correcting system 2, ZigBee-network module 10, field data acquisition terminal 11, scene control manipulation node 4,
Operating mechanism 18, wireless transport module 9, display module 5, memory module 6, serial communication modular 7, clock module 8, power module
3rd, operation module 17, wherein central processing system 1 respectively with power module 3, error correcting system 2, wireless transport module 9, aobvious
Show module 5, memory module 6, serial communication modular 7, clock module 8, ZigBee-network module 10, live manipulation operation node 4
It is connected, live control manipulation node 4 is also connected with power module 3, while passes through corresponding operating module 17 and operating mechanism
18 are connected, and to realize the various adjustings to medical scene, field data acquisition terminal 11 passes through error correcting system 2 and center
Processing system 1 connects.The acquisition terminal connects 11 and meets multiple medical environment sensor 12-16, such as measures temperature, humidity, oxygen
The corresponding sensor such as concentration and the various parameters of gas concentration lwevel.The data processing system includes following processing and walks
Suddenly：
Ambient measurements are obtained by multiple sensors, wherein each sensor is carried out ambient measurements and obtained with some cycles
It takes, the data that different time points measure are denoted as xi, wherein i=1,2,3 ..., a nearest measured value is often obtained, all with being
Preset measurement limit value of uniting is compared, if measured value exceeds limits, alarm prompt is carried out, if measured value
In limits, then following steps are carried out.
By this measured value xiMake difference successively with measured value before, obtain xi-xm, wherein m=1,2,3 ... i-
1, if the difference of any two of which measured value is no more than error limit, it is calculated as below：
Z (m | m-1)=Z (m-1 | m-1)
S (m | m-1)=S (m-1 | m-1)+T
Z (m | m)=Z (m | m-1)+U (m) (x (m)-Z (m | m-1))
Wherein
S (m | m)=(1-U (m)) S (m | m-1)
Wherein, wherein, Z is the system mode at m moment, and S (m-1 | m-1) is the most effective value at m-1 time points, S (m | m-1)
It is according to the above-mentioned most effective assessed value being worth to, S is the covariance of Z (m | m), and T is the covariance of systematic procedure, and U systems increase
Benefit, Q are variance；
It is iterated by above-mentioned formula, you can obtain satisfactory measurement value sensor.If two measurements
When the difference of value is more than error limit, then Bayesian Estimation and wavelet transformation is carried out to measured value or estimated with neural network
Meter,
Finally obtained measured value is calculated as below：
Wherein, xiFor the measured value after above-mentioned calculating iteration, hiFor corresponding weights, W is final virtual value.
The foregoing is merely illustrative of the preferred embodiments of the present invention, is not intended to limit the invention, all essences in the present invention
All any modification, equivalent and improvement made within refreshing and principle etc., should all be included in the protection scope of the present invention.
Claims (4)
1. a kind of on-line module of wearable built-in support cellular data function, which is characterized in that including cellular communication unit
With the cellular data collecting unit for being built in wearable device, the cellular communication unit receive described in be built in wearable device
Cellular data collecting unit transmission data information.
2. the on-line module of wearable built-in support cellular data function according to claim 1, which is characterized in that interior
The cellular data collecting unit for being placed in wearable device includes centric acquisition system, error correction including field data acquisition terminal
System, ZigBee-network module, field data acquisition terminal, live control manipulation node, operating mechanism, wireless transport module,
Display module, memory module, serial communication modular, clock module, power module, wherein operation module, central processing system point
Other and power module, error correcting system, wireless transport module, display module, memory module, serial communication modular, clock mould
Block, ZigBee-network module, live manipulation operation node are connected, and live control manipulation node is also connected with power module,
It is connected simultaneously by corresponding operating module with operating mechanism, to realize the adjusting to medical scene, field data acquisition terminal
It is connect by error correcting system with central processing system.
3. the on-line module of wearable built-in support cellular data function as claimed in claim 2, wherein the acquisition is eventually
End connects multiple medical environment sensors.
4. the on-line module of wearable built-in support cellular data function as claimed in claim 2, the error correction system
Error correction used by system includes following processing step：
Ambient measurements are obtained by the multiple sensor, wherein each sensor is carried out ambient measurements and obtained with some cycles
It takes, the data that different time points measure are denoted as xi, wherein i=1,2,3 ..., a nearest measured value is often obtained, all with being
Preset measurement limit value of uniting is compared, if measured value exceeds limits, alarm prompt is carried out, if measured value
In limits, then following steps are carried out：
By this measured value xiMake difference successively with measured value before, obtain xi-xm, wherein m=1,2,3 ... i-1, such as
The difference of fruit any two of which measured value is no more than error limit, then is calculated as below：
Z (m | m-1)=Z (m-1 | m-1)
S (m | m-1)=S (m-1 | m-1)+T
Z (m | m)=Z (m | m-1)+U (m) (x (m)-Z (m | m-1))
Wherein
S (m | m)=(1-U (m)) S (m | m-1)
Wherein, wherein, Z is the system mode at m moment, and S (m-1 | m-1) is the most effective value at m-1 time points, and S (m | m-1) it is root
According to the above-mentioned most effective assessed value being worth to, S is the covariance of Z (m | m), and T is the covariance of systematic procedure, U system gains, Q
For variance；
It is iterated by above-mentioned formula, you can obtain satisfactory measurement value sensor.If two measured values
When difference is more than error limit, then Bayesian Estimation and wavelet transformation is carried out to measured value or are estimated with neural network,
Finally obtained measured value is calculated as below：
Wherein, xiFor the measured value after above-mentioned calculating iteration, hiFor corresponding weights, W is final effective measured value.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810092054.3A CN108173967A (en) | 2018-01-30 | 2018-01-30 | A kind of on-line module of wearable built-in support cellular data function |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810092054.3A CN108173967A (en) | 2018-01-30 | 2018-01-30 | A kind of on-line module of wearable built-in support cellular data function |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN108173967A true CN108173967A (en) | 2018-06-15 |
Family
ID=62512803
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201810092054.3A Pending CN108173967A (en) | 2018-01-30 | 2018-01-30 | A kind of on-line module of wearable built-in support cellular data function |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN108173967A (en) |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103874118A (en) * | 2014-02-25 | 2014-06-18 | 南京信息工程大学 | Bayes Regression-based Radio Map correction method in WiFi (wireless fidelity) indoor location |
| CN104523254A (en) * | 2015-01-22 | 2015-04-22 | 安徽理工大学 | Medical monitoring system for ZigBee-based wearable sensor |
| CN204708827U (en) * | 2015-01-22 | 2015-10-21 | 安徽理工大学 | Based on the medical monitoring system of ZigBee wearable sensors |
| US9210625B1 (en) * | 2015-04-24 | 2015-12-08 | Amazon Technologies, Inc. | Systems and methods for managing network connections |
| CN106361304A (en) * | 2016-08-25 | 2017-02-01 | 叶永飞 | Computer-based wearable medical monitoring system |
| CN107193382A (en) * | 2014-02-24 | 2017-09-22 | 索尼公司 | Intelligent wearable device and it is automatic using sensor come the method for allocative abilities |
-
2018
- 2018-01-30 CN CN201810092054.3A patent/CN108173967A/en active Pending
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107193382A (en) * | 2014-02-24 | 2017-09-22 | 索尼公司 | Intelligent wearable device and it is automatic using sensor come the method for allocative abilities |
| CN103874118A (en) * | 2014-02-25 | 2014-06-18 | 南京信息工程大学 | Bayes Regression-based Radio Map correction method in WiFi (wireless fidelity) indoor location |
| CN103874118B (en) * | 2014-02-25 | 2017-03-15 | 南京信息工程大学 | Radio Map bearing calibrations in WiFi indoor positionings based on Bayesian regression |
| CN104523254A (en) * | 2015-01-22 | 2015-04-22 | 安徽理工大学 | Medical monitoring system for ZigBee-based wearable sensor |
| CN204708827U (en) * | 2015-01-22 | 2015-10-21 | 安徽理工大学 | Based on the medical monitoring system of ZigBee wearable sensors |
| US9210625B1 (en) * | 2015-04-24 | 2015-12-08 | Amazon Technologies, Inc. | Systems and methods for managing network connections |
| CN106361304A (en) * | 2016-08-25 | 2017-02-01 | 叶永飞 | Computer-based wearable medical monitoring system |
Non-Patent Citations (2)
| Title |
|---|
| 曾国强: "卡尔曼滤波在航空C能谱勘查系统自动稳谱中的应用", 《核电子学与探测技术》 * |
| 李小宁: "多传感器数据融合的权值因子确定", 《飞行器测控学报》 * |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US11405268B2 (en) | Fine grained network management to edge device features | |
| Liang et al. | Performance evaluations of LoRa wireless communication in building environments | |
| Pranata et al. | Towards an IoT-based water quality monitoring system with brokerless pub/sub architecture | |
| CN110222925A (en) | Performance quantization wire examination method, device and computer readable storage medium | |
| Bhattacharjee et al. | Development of smart detachable wireless sensing system for environmental monitoring | |
| Wang et al. | Human detection through RSSI processing with packet dropout in wireless sensor network | |
| Macheso et al. | Environmental parameter monitoring system based on nodemcu esp8266, mqtt and node-red | |
| Koushik et al. | Design and Development of Wireless Sensor Network based data logger with ESP-NOW protocol | |
| Phung Cong Phi et al. | Classification of cow’s behaviors based on 3-DoF accelerations from cow’s movements | |
| Moon et al. | Secured data acquisition system for smart water applications using WSN | |
| CN108173967A (en) | A kind of on-line module of wearable built-in support cellular data function | |
| CN108289127A (en) | A kind of Internet of things system for Medical Devices comprehensively monitoring | |
| Nyasulu | Smart under-five health care system | |
| CN108156258A (en) | A kind of general agricultural data acquisition system based on Internet of Things | |
| González et al. | A low-cost IoT architecture based on LPWAN and MQTT for monitoring water resources in andean wetlands | |
| Mudassir et al. | MFVL HCCA: A modified Fast-Vegas-LIA Hybrid Congestion Control Algorithm for MPTCP traffic flows in multihomed smart Gas IoT networks | |
| CN107688878B (en) | Air Quality Forecast method and device | |
| Suaib et al. | Monitoring and Prediction of Temperature and Humidity at Telkom University Landmark Tower (TULT) Using Generalized Additive Model (GAM) and Internet of Things (IoT) | |
| Foerster et al. | Integrating human observations and sensor observations—the example of a noise mapping community | |
| Makode et al. | Smart agriculture solution using LoRa and IoT | |
| Chaiboonruang et al. | Small buildings energy management system based on IEEE1888 standard with data compression | |
| Sinha et al. | An Internet of Things based prototype for smart appliance control | |
| Al Tahtawi et al. | Portable wireless node design for smart agricultural system based on Internet of Things | |
| Ridozub et al. | Sensor node for wireless radiation monitoring network | |
| CN108562694A (en) | A kind of wisdom traffic terminal |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20180615 |
|
| RJ01 | Rejection of invention patent application after publication |