CN106198868A - The method and system of Humidity Detection based on wireless aware - Google Patents
The method and system of Humidity Detection based on wireless aware Download PDFInfo
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- CN106198868A CN106198868A CN201610521465.0A CN201610521465A CN106198868A CN 106198868 A CN106198868 A CN 106198868A CN 201610521465 A CN201610521465 A CN 201610521465A CN 106198868 A CN106198868 A CN 106198868A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
- G01N33/0004—Gaseous mixtures, e.g. polluted air
- G01N33/0009—General constructional details of gas analysers, e.g. portable test equipment
- G01N33/0062—General constructional details of gas analysers, e.g. portable test equipment concerning the measuring method, e.g. intermittent, or the display, e.g. digital
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
- G01N33/0004—Gaseous mixtures, e.g. polluted air
- G01N33/0009—General constructional details of gas analysers, e.g. portable test equipment
- G01N33/0062—General constructional details of gas analysers, e.g. portable test equipment concerning the measuring method, e.g. intermittent, or the display, e.g. digital
- G01N2033/0068—General constructional details of gas analysers, e.g. portable test equipment concerning the measuring method, e.g. intermittent, or the display, e.g. digital using a computer specifically programmed
Abstract
The present invention relates to wireless network signal transmission technology, it discloses the method and system of a kind of Humidity Detection based on wireless aware.The method utilizes the wireless signal that wireless signal acquiring device collection launches from transmitting terminal, and assesses channel condition information, to reach the purpose detecting the humidity information of surrounding.The step of described method includes: use the wireless signal that wireless signal acquiring device launches from transmitting terminal with specific layout collection.The present invention utilizes existing wireless network and equipment, it is not necessary to installs other specific detection equipment, has high popularization.
Description
Technical field
The present invention relates to radio detection field, particularly relate to a kind of method of Humidity Detection based on wireless aware and be
System.
Background technology
Radio network technique had had rapid development in the last few years, and people attempt applying it to the square aspect of life
Face.Simultaneously along with development and the progress of life in epoch, people increasingly pay close attention to the relation of self and the Nature.Atmospheric humidity is made
For a kind of ambient parameter, strongly affect natural economy, and the effect that performer is important in various environmental processes.The most each
The growth planting crops all be unable to do without suitable humidity.In conjunction with current hotspot, wireless aware technology is utilized to carry out atmospheric humidity prison
The research surveyed, thus allow technology preferably serve life.
Existing humidity measuring method can be largely classified into two kinds.One is, look-up table, common drimeter be exactly this
The method of kind.General principles is as follows: owing to the bulb, of wet-bulb thermometer encloses cotton yarn, and the lower end of cotton yarn is soaked in water, the steaming of water
Send out and make the temperature registration of wet-bulb thermometer always be less than the temperature registration of dry-bubble temperature meter, and this temperature gap evaporates with water
Speed (relative humidity the most at that time) about. according to the reading of two temperatures meter, the wettest of air can be found from table or curve
Degree.Two are, damped method, can be affected by steam and the principle that decayed when transmitting in atmosphere based on electromagnetic wave, logical
Cross measurement transmitting terminal and the RSSI (Received Signal Strength Indicator) of receiving terminal, thus according to decay
Degree speculates the size of humidity.
Sum up both the above method.Method one, utilizes physical phenomenon to measure humidity, and artificial error is bigger.And
And when we need the humidity value knowing many places simultaneously, this is accomplished by placing multiple drimeter, and such cost is the highest.Side
Method two, the impact transmitted signal due to steam is the least.Therefore, need in practical operation (long through long-distance
Reach several kilometers) transmission after signal intensity measure.Under distance, add other weather conditions, like rain, snow and mist etc.
Probability to effect of signals, thus cause measuring limited.Furthermore, distance inherently adds the inconvenience of measurement.
Summary of the invention
In order to overcome the weak point in the existing measuring method of above-mentioned indication, the present invention provides a kind of based on wireless aware
The method and system of Humidity Detection.Utilizing the wireless signal transmitting device being widely deployed, such as commercial routers, spy
In fixed layout, by CSI (the Channel State Information channel condition information) data collected, use one
Data are analyzed by serial algorithm, thus detect the humidity information of surrounding.The method has a good basis of reality: nothing
Gauze network is by ubiquitous deployment.Relative to conventional method, decrease measurement cost, improve the suitability.
The present invention is achieved by the following technical solutions:
A kind of humidity detection method based on wireless aware, comprises the steps:
S1, wireless receiving end receive the wireless signal from wireless transmitting terminals, and assess channel condition information；
S2, CSI data characteristics is extracted, and exports target pattern；
S3, the target pattern that will export in step S2, use svm classifier, to detect the humidity information of surrounding；
S4, feedback, for the response message of testing result, adjust the parameter of sorting algorithm, promote accuracy further.
As a further improvement on the present invention: described step S1 assessment channel condition information includes:
S11, collection initial channel status data, based on MIMO technique, described initial channel status data includes M
The CSI value of the N number of subcarrier in spatial flow, M and N is the natural number more than 1；
S12, to each spatial flow, ask for the meansigma methods of the T on same time point the CSI value of subcarrier continuously, this put down
Average is as channel condition information, and T is the natural number more than 1 less than N；
S13, utilize data filtering techniques, channel condition information is carried out filtration treatment, to reduce in surrounding because of object
The interference to channel condition information moved and cause.
As a further improvement on the present invention: described step S2 includes carrying out CSI data average Mean, normalized mark
Quasi-difference The Normalized Standard Deviation, mean absolute deviation Mean Absolute Deviation, four
Divide position scope Interquartile Range and the extraction of signal entropy Signal Entropy totally five aspect features.
As a further improvement on the present invention: described step S3 carries out the sorting algorithm classified according to the feature of CSI data
It it is support vector machines method.
As a further improvement on the present invention: described step S3 includes:
S31, based on Statistical Learning Theory, pre-build using set different moisture levels in space cause channel condition information change as
The high dimensional feature model of training sample；
S32, the target pattern that will export in step S2, use svm classifier, to detect the humidity information of surrounding.
As a further improvement on the present invention: in described step S4, feed back the response message for Humidity Detection result, adjust
The high dimensional feature model of whole support vector machine.
Invention also provides a kind of dust humidity detection system based on wireless aware, including:
CSI acquisition module, receives the wireless signal from wireless transmitting terminals for wireless receiving end, and assesses channel status letter
Breath；
Detection module, for the CSI data collected according to CSI acquisition module, extracts feature, and carries out classification and matching, detection
Go out the humidity information of current environment；
Feedback module, compares with known classification for the result detected by detection module, if there is deviation, then enters
Row correction, so that sorting algorithm is the most accurate；
Display module, is used for showing the result detected.
As a further improvement on the present invention: described CSI acquisition module includes:
Sensing unit, is used for gathering initial channel status data, based on MIMO technique, and described initial channel status number
According to the CSI value of the N number of subcarrier included in M spatial flow, M and N is the natural number more than 1；
Data processing unit, for each spatial flow, asking for the CSI value of the T on same time point continuous subcarrier
Meansigma methods, using this meansigma methods as channel condition information, T is the natural number more than 1 less than N；
Filter element, is used for utilizing data filtering techniques that channel condition information is carried out filtration treatment.
As a further improvement on the present invention: described detection module, including:
Computing unit, for CSI data are carried out feature extraction, the feature of extraction includes: average, normalized standard deviation, flat
All absolute deviation, quartile scope and signal entropy；
Setting up model unit, for based on Statistical Learning Theory, in pre-building to set space, different moisture levels causes channel shape
State information change is as the high dimensional feature model of training sample；
Detector unit, in the high dimensional feature model that the target pattern of output maps to support vector machine, isolates target
Humidity class.
As a further improvement on the present invention: described feedback module includes: for feedback for current environment Humidity Detection
Response message, adjust support vector machine high dimensional feature model；Described display module include but not limited to mobile terminal screen,
Palm PC or LCDs.
Beneficial effects of the present invention: relative to RSSI, CSI as a kind of more preferable assessment to radio propagation channel；This
Invention utilizes the advantage of CSI, have devised a kind of dust humidity detection system based on wireless aware, and enables correction module more accurate
Really the humidity information of surrounding is detected；This detection method is on the basis of existing wireless network and equipment, enters
Row Humidity Detection works, and without installing other specific detection equipment in detected environment, has high popularization.
Accompanying drawing explanation
Accompanying drawing 1 is the system configuration schematic diagram of the Humidity Detection based on wireless aware of a kind of embodiment of the present invention；
Accompanying drawing 2 be the humidity detection method of the present invention realize general flow chart；
Accompanying drawing 3 be the humidity detection method of a kind of embodiment of the present invention realize schematic flow sheet；
Accompanying drawing 4 is the frame diagram of the dust humidity detection system of a kind of embodiment of the present invention.
Detailed description of the invention
For the ease of the understanding of those skilled in the art, with example, the present invention is further retouched below in conjunction with the accompanying drawings
State.
The Support i.e. SVM of Vector Machine
A kind of humidity detection method based on wireless aware, comprises the steps:
S1, wireless receiving end receive the wireless signal from wireless transmitting terminals, and assess channel condition information；
S2, CSI data characteristics is extracted, and exports target pattern；
S3, the target pattern that will export in step S2, use svm classifier, to detect the humidity information of surrounding；
S4, feedback, for the response message of testing result, adjust the parameter of sorting algorithm, promote accuracy further.
Described step S1 assessment channel condition information includes:
S11, collection initial channel status data, based on MIMO technique, described initial channel status data includes M
The CSI value of the N number of subcarrier in spatial flow, M and N is the natural number more than 1；
S12, to each spatial flow, ask for the meansigma methods of the T on same time point the CSI value of subcarrier continuously, this put down
Average is as channel condition information, and T is the natural number more than 1 less than N；
S13, utilize data filtering techniques, channel condition information is carried out filtration treatment, to reduce in surrounding because of object
The interference to channel condition information moved and cause.
Described step S2 includes CSI data carry out average Mean, normalized standard deviation The Normalized
Standard Deviation, mean absolute deviation Mean Absolute Deviation, quartile scope
Interquartile Range and the extraction of signal entropy Signal Entropy totally five aspect features.
Described step S3 is support vector machines method according to the sorting algorithm that the feature of CSI data carries out classifying.
Described step S3 includes:
S31, based on Statistical Learning Theory, pre-build using set different moisture levels in space cause channel condition information change as
The high dimensional feature model of training sample；
S32, the target pattern that will export in step S2, use svm classifier, to detect the humidity information of surrounding.
As a further improvement on the present invention: in described step S4, feed back the response message for Humidity Detection result, adjust
The high dimensional feature model of whole support vector machine.
Invention also provides a kind of dust humidity detection system based on wireless aware, including:
CSI acquisition module, receives the wireless signal from wireless transmitting terminals for wireless receiving end, and assesses channel status letter
Breath；
Detection module, for the CSI data collected according to CSI acquisition module, extracts feature, and carries out classification and matching, detection
Go out the humidity information of current environment；
Feedback module, compares with known classification for the result detected by detection module, if there is deviation, then enters
Row correction, so that sorting algorithm is the most accurate；
Display module, is used for showing the result detected.
Described CSI acquisition module includes:
Sensing unit, is used for gathering initial channel status data, based on MIMO technique, and described initial channel status number
According to the CSI value of the N number of subcarrier included in M spatial flow, M and N is the natural number more than 1；
Data processing unit, for each spatial flow, asking for the CSI value of the T on same time point continuous subcarrier
Meansigma methods, using this meansigma methods as channel condition information, T is the natural number more than 1 less than N；
Filter element, is used for utilizing data filtering techniques that channel condition information is carried out filtration treatment.
Described detection module, including:
Computing unit, for CSI data are carried out feature extraction, the feature of extraction includes: average, normalized standard deviation, flat
All absolute deviation, quartile scope and signal entropy；
Setting up model unit, for based on Statistical Learning Theory, in pre-building to set space, different moisture levels causes channel shape
State information change is as the high dimensional feature model of training sample；
Detector unit, in the high dimensional feature model that the target pattern of output maps to support vector machine, isolates target
Humidity class.
Described feedback module includes: for feedback for the response message of current environment Humidity Detection, adjusts and supports vector
The high dimensional feature model of machine；Described display module includes but not limited to mobile terminal screen, palm PC or LCDs.
In one embodiment, a kind of method of Humidity Detection based on wireless aware, its step includes:
S1, wireless receiving end receive the wireless signal from wireless transmitting terminals, and assess channel condition information；
S2, CSI data characteristics is extracted, and the CSI data collected are made average (Mean), normalized standard deviation (The respectively
Normalized Standard Deviation), mean absolute deviation (Mean Absolute Deviation), quartile model
Enclose (Interquartile Range and signal entropy (Signal Entropy) process, output target pattern；
S3, the target pattern that will export in step S2, use svm classifier, to detect the humidity information of surrounding；
S4, feedback, for the response message of testing result, adjust the parameter of sorting algorithm, promote accuracy further.
Specifically, in step sl, assessment channel condition information includes:
S11, collection initial channel status data, based on MIMO technique, described initial channel status data includes M
The CSI value of N subcarrier in spatial flow, M and N is the natural number more than 1；
S12, to each spatial flow, ask for the meansigma methods of the T on same time point the CSI value of subcarrier continuously, this put down
Average is as channel condition information, and T is the natural number more than 1 less than N；
S13, utilize data filtering techniques, channel condition information is carried out filtration treatment, to reduce in surrounding because of object
The interference to channel condition information moved and cause.
When the system starts of the present invention, wireless transmitting terminals propagates wireless network signal, is simultaneously in specific region
In wireless receiving end (as equipped with the computer of network interface card) CSI can be collected as initial channel status data, then carry out at data
Reason.
Referring to Fig. 1, it is the experimental arrangement figure of whole experiment scene.
Described step S2 includes CSI data carry out average (Mean), normalized standard deviation (The Normalized
Standard Deviation), mean absolute deviation (Mean Absolute Deviation), quartile scope
(Interquartile Range) and the extraction of signal entropy (Signal entropy) totally five aspect features.
Described step S3 includes:
S31, based on Statistical Learning Theory, pre-build using set different moisture levels in space cause channel condition information change as
The high dimensional feature model of training sample；
S32, the target pattern that will export in step S2, use svm classifier, to detect the humidity information of surrounding.
Described step S4 includes: feed back the response message for Humidity Detection result, and the higher-dimension adjusting support vector machine is special
Levy model.
Flow chart as shown in Figure 2, discloses four important steps of the detection method of the present invention, including: channel shape
State assessment, CSI data characteristics are extracted, humidity is classified and feedback testing result.
In another embodiment, as shown in Figure 3, present invention also offers the realization of the humidity detection method of a kind of embodiment
Flow process, its step includes:
S301, wireless receiving end receive the wireless signal from wireless transmitting terminals, gather initial channel status data simultaneously；
S302, take merge subcarrier CSI meansigma methods as channel condition information；
S303, channel condition information is carried out filtration treatment；
S304, channel condition information is carried out feature extraction；
S305, output target pattern；
S306, target pattern is mapped to the high dimensional feature model of support vector machine；
S307, support vector machine is utilized to classify；
S308, whether detect the humidity information of current environment, in this way, perform step S309, otherwise return step S301；
S309, display module show testing result, adjust parameter, optimize detection and sorting algorithm.
Present invention also offers a kind of dust humidity detection system, as shown in Figure 4, including:
CSI acquisition module 41, receives the wireless signal from wireless transmitting terminals for wireless receiving end, and assesses channel status letter
Breath；
Detection module 42, for the CSI data collected according to CSI acquisition module, extracts feature, exports target pattern, and will
The target pattern of output maps to, in the high dimensional feature model of support vector machine, isolate target humidity class；
Feedback module 43, compares with known classification, if there is deviation, then for the result detected by detection module
It is corrected, so that sorting algorithm is the most accurate；
Display module 44, the display screen of available mobile phone terminal or other display modules, it is used for showing the result detected.
Described CSI acquisition module includes:
Sensing unit 411, is used for gathering initial channel status data, based on MIMO technique, and described initial channel shape
State data include the CSI value of the N number of subcarrier in M spatial flow, M and N is the natural number more than 1；
Data processing unit 412, for each spatial flow, asking for the CSI value of the T on same time point continuous subcarrier
Meansigma methods, using this meansigma methods as channel condition information, T is less than the natural number of N more than 1；
Filter element 413, is used for utilizing data filtering techniques that channel condition information is carried out filtration treatment.
Described detection module, including:
Computing unit 421, for CSI data are carried out feature extraction, the feature of extraction includes: average (Mean), normalized
Standard deviation (Normalized Standard Deviation), mean absolute deviation (Mean Absolute Deviation),
Quartile scope (Interquartile Range) and signal entropy (Signal Entropy), export target pattern；
Setting up model unit 422, for based on Statistical Learning Theory, in pre-building to set space, different moisture levels causes channel
State information change is as the high dimensional feature model of training sample；
Humidity recognition unit 423, in the high dimensional feature model that the target pattern of output maps to support vector machine, separates
Go out target humidity class.
The dust humidity detection system of the present invention also includes a feedback module 43, for feedback for current environment Humidity Detection
Response message, adjusts the high dimensional feature model of support vector machine.
The dust humidity detection system of the present invention also includes a display module 44, for showing final testing result, shows mould
Block is mobile terminal screen, palm PC, LCDs and other is for showing that the display device of content is (such as projector
Deng).
Above content is to combine concrete optimal way further description made for the present invention, should not assert this
Bright be embodied as being confined to described above.For those skilled in the art, without departing from present inventive concept
On the premise of, it is also possible to making some simple deduction or replace, the claim being regarded as being submitted to by the present invention determines
Within protection domain.
Claims (10)
1. a humidity detection method based on wireless aware, it is characterised in that comprise the steps:
S1, wireless receiving end receive the wireless signal from wireless transmitting terminals, and assess channel condition information；
S2, CSI data characteristics is extracted, and exports target pattern；
S3, the target pattern that will export in step S2, use svm classifier, to detect the humidity information of surrounding；
S4, feedback, for the response message of testing result, adjust the parameter of sorting algorithm, promote accuracy further.
2. according to the humidity detection method based on wireless aware described in claim 1, it is characterised in that described step S1 is commented
Estimate channel condition information to include:
S11, collection initial channel status data, based on MIMO technique, described initial channel status data includes M
The CSI value of the N number of subcarrier in spatial flow, M and N is the natural number more than 1；
S12, to each spatial flow, ask for the meansigma methods of the T on same time point the CSI value of subcarrier continuously, this put down
Average is as channel condition information, and T is the natural number more than 1 less than N；
S13, utilize data filtering techniques, channel condition information is carried out filtration treatment, to reduce in surrounding because of object
The interference to channel condition information moved and cause.
3. according to the humidity detection method based on wireless aware described in claim 1, it is characterised in that described step S2 bag
Include and CSI data are carried out average Mean, normalized standard deviation The Normalized Standard Deviation, average
Absolute deviation Mean Absolute Deviation, quartile scope Interquartile Range and signal entropy
The extraction of Signal Entropy totally five aspect features.
4. according to the humidity detection method based on wireless aware described in claim 1, it is characterised in that described step S3 root
The sorting algorithm carrying out classifying according to the feature of CSI data is support vector machines method.
5. according to the humidity detection method based on wireless aware described in claim 1, it is characterised in that described step S3 bag
Include:
S31, based on Statistical Learning Theory, pre-build using set different moisture levels in space cause channel condition information change as
The high dimensional feature model of training sample；
S32, the target pattern that will export in step S2, use svm classifier, to detect the humidity information of surrounding.
6. according to the humidity detection method based on wireless aware described in claim 1, it is characterised in that in described step S4,
Feed back the response message for Humidity Detection result, adjust the high dimensional feature model of support vector machine.
7. a dust humidity detection system based on wireless aware, it is characterised in that including:
CSI acquisition module, receives the wireless signal from wireless transmitting terminals for wireless receiving end, and assesses channel status letter
Breath；
Detection module, for the CSI data collected according to CSI acquisition module, extracts feature, and carries out classification and matching, detection
Go out the humidity information of current environment；
Feedback module, compares with known classification for the result detected by detection module, if there is deviation, then enters
Row correction, so that sorting algorithm is the most accurate；
Display module, is used for showing the result detected.
Dust humidity detection system based on wireless aware the most according to claim 7, it is characterised in that described CSI obtains mould
Block includes:
Sensing unit, is used for gathering initial channel status data, based on MIMO technique, and described initial channel status number
According to the CSI value of the N number of subcarrier included in M spatial flow, M and N is the natural number more than 1；
Data processing unit, for each spatial flow, asking for the CSI value of the T on same time point continuous subcarrier
Meansigma methods, using this meansigma methods as channel condition information, T is the natural number more than 1 less than N；
Filter element, is used for utilizing data filtering techniques that channel condition information is carried out filtration treatment.
Dust humidity detection system based on wireless aware the most according to claim 7, it is characterised in that described detection module,
Including:
Computing unit, for CSI data are carried out feature extraction, the feature of extraction includes: average, normalized standard deviation, flat
All absolute deviation, quartile scope and signal entropy；
Setting up model unit, for based on Statistical Learning Theory, in pre-building to set space, different moisture levels causes channel shape
State information change is as the high dimensional feature model of training sample；
Detector unit, in the high dimensional feature model that the target pattern of output maps to support vector machine, isolates target
Humidity class.
Dust humidity detection system based on wireless aware the most according to claim 1, it is characterised in that described feedback module
Including: for feedback for the response message of current environment Humidity Detection, adjust the high dimensional feature model of support vector machine；Described
Display module includes but not limited to mobile terminal screen, palm PC or LCDs.
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| CN201610521465.0A CN106198868A (en) | 2016-07-05 | 2016-07-05 | The method and system of Humidity Detection based on wireless aware |
| CN201710525205.5A CN107294621B (en) | 2016-07-05 | 2017-06-30 | The method and system of Humidity Detection based on wireless aware |
| PCT/CN2017/091670 WO2018006798A1 (en) | 2016-07-05 | 2017-07-04 | Wireless sensing-based temperature detection method and system |
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107273615A (en) * | 2017-06-15 | 2017-10-20 | 东华大学 | A kind of ultra-wideband microwave humidity detection method based on machine learning |
| WO2018006798A1 (en) * | 2016-07-05 | 2018-01-11 | 深圳大学 | Wireless sensing-based temperature detection method and system |
| WO2024040962A1 (en) * | 2022-08-26 | 2024-02-29 | 中兴通讯股份有限公司 | Wireless sensing method, communication device, and storage medium |
Families Citing this family (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109374652B (en) * | 2018-09-05 | 2020-03-20 | 深圳大学 | Humidity sensing and detecting method and system based on millimeter wave signals |
| CN110365429B (en) * | 2019-07-18 | 2020-09-25 | 珠海格力电器股份有限公司 | Detection method, device and system, storage medium and processor |
| CN113485218B (en) * | 2021-08-04 | 2022-06-07 | 广德绿巨人环境管理咨询有限公司 | Wisdom thing allies oneself with supervision platform based on 5G |
Family Cites Families (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| DE19706576A1 (en) * | 1997-02-20 | 1998-08-27 | Alsthom Cge Alcatel | Device and method for the environment-adaptive classification of objects |
| CN101640570A (en) * | 2008-07-29 | 2010-02-03 | 株式会社Ntt都科摩 | Frequency spectrum cognitive method and energy detection method and device |
| EP2463650B1 (en) * | 2010-12-10 | 2015-04-15 | Clariant Produkte (Deutschland) GmbH | Indicator material and indicator device comprising said indicator material and method of manufacture |
| CN103023589A (en) * | 2012-12-06 | 2013-04-03 | 中山大学 | Indoor passive motion detection method and device |
| CN103606248B (en) * | 2013-09-30 | 2016-08-10 | 广州市香港科大霍英东研究院 | A kind of falling over of human body automatic testing method and system |
| CN103647591B (en) * | 2013-12-27 | 2016-06-08 | 中国电子科技集团公司第五十四研究所 | A kind of multipoint cooperative interference detection method based on SVMs |
| CN104062654B (en) * | 2014-07-17 | 2016-04-13 | 电子科技大学 | A kind of soil water meauring method based on ULTRA-WIDEBAND RADAR |
| CN104615244A (en) * | 2015-01-23 | 2015-05-13 | 深圳大学 | Automatic gesture recognizing method and system |
| CN106198868A (en) * | 2016-07-05 | 2016-12-07 | 深圳大学 | The method and system of Humidity Detection based on wireless aware |
-
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2018006798A1 (en) * | 2016-07-05 | 2018-01-11 | 深圳大学 | Wireless sensing-based temperature detection method and system |
| CN107273615A (en) * | 2017-06-15 | 2017-10-20 | 东华大学 | A kind of ultra-wideband microwave humidity detection method based on machine learning |
| WO2024040962A1 (en) * | 2022-08-26 | 2024-02-29 | 中兴通讯股份有限公司 | Wireless sensing method, communication device, and storage medium |
Also Published As
| Publication number | Publication date |
|---|---|
| CN107294621B (en) | 2019-04-02 |
| WO2018006798A1 (en) | 2018-01-11 |
| CN107294621A (en) | 2017-10-24 |
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