CN110009454A - User's behavior learning based on spatial perception and internal network signaling is in decision recommender system - Google Patents
User's behavior learning based on spatial perception and internal network signaling is in decision recommender system Download PDFInfo
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- CN110009454A CN110009454A CN201910238261.XA CN201910238261A CN110009454A CN 110009454 A CN110009454 A CN 110009454A CN 201910238261 A CN201910238261 A CN 201910238261A CN 110009454 A CN110009454 A CN 110009454A
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- 230000008447 perception Effects 0.000 title claims abstract description 27
- 230000013016 learning Effects 0.000 title claims abstract description 24
- 230000011664 signaling Effects 0.000 title claims abstract description 19
- 230000006399 behavior Effects 0.000 title claims abstract description 12
- 238000012545 processing Methods 0.000 claims abstract description 28
- 238000000034 method Methods 0.000 claims description 14
- 230000008569 process Effects 0.000 claims description 12
- 238000006243 chemical reaction Methods 0.000 claims description 9
- 230000003014 reinforcing effect Effects 0.000 claims description 8
- 230000005540 biological transmission Effects 0.000 claims description 7
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- G06Q30/00—Commerce
- G06Q30/06—Buying, selling or leasing transactions
- G06Q30/0601—Electronic shopping [e-shopping]
- G06Q30/0631—Item recommendations
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- 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
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/02—Services making use of location information
- H04W4/029—Location-based management or tracking services
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Abstract
The invention discloses user's behavior learnings based on spatial perception and internal network signaling of spatial perception technical field in decision recommender system, including phy-aware equipment, WiFi sensing module, data processing module, cloud server and expansion interface, phy-aware equipment respectively with expansion interface and the two-way electric connection of data processing module；The present invention identifies the surface as forefathers or object by wireless network signal, motion track, behavioural characteristic and habit feedback model can be constructed by the data perception to space, and user or supervised learning person's mode of learning recognition result are provided based on this model, it assists people or object in the space to provide the decision recommendation of the fitting situation of presence and is executed the decision recommendation, more existing perceptive mode, which has, can recognize people, the exterior contour and motion track of object, in conjunction with perception data building behavioural characteristic and habit feedback model, and provide recognition result and relevant decision recommendation.
Description
Technical field
The present invention relates to spatial perception technical fields, and in particular to is practised based on the user of spatial perception and internal network signaling
Used study is in decision recommender system.
Background technique
Current spatial perception mode relies solely on traditional physical sensors and carries out data perception, and such mode can not be more
Add other data accurately perceived in the space, such as: the data such as object resemblance, motion track, current perception are set
Standby central role, which still rests on, carries out action triggers for the equipment of rear end, is not docked to other related systems, also without
Method provides more proper service further for user.
There are following defects for current smart machine: current perception effect mainly provides triggering for rear end equipment
Condition does not have more advanced function；Current cognition technology does not have the data such as tracking, object surface to track also
Ability；The detection equipment used is more traditional, and limitation is bigger；Can not the privacy to aware space effectively protected
Shield；It will receive the limitation in relation to factor such as space, angle, position.Based on this, the present invention is devised based on spatial perception and inside
User's behavior learning of network signal is in decision recommender system, to solve the above problems.
Summary of the invention
The purpose of the present invention is to provide user's behavior learnings based on spatial perception and internal network signaling to push away in decision
System is recommended, is combined by physical sensors and WiFi signal perception, WiFi positioning, realizes a kind of novel perceptive mode, together
When by modeling to perception data, study and constantly training optimization, and by result with a kind of side for being more bonded user demand
Formula feedback to user, effectively solve can not perception problems comprehensive, across space (barrier), in comprehensive protection to the space
Privacy of user problem, collective data model can solve user the decision of related fields the problem of, effective solution tradition
Physical sensors can not perceptible body surface, motion track, body form the problems such as.
To achieve the above object, the invention provides the following technical scheme: the use based on spatial perception and internal network signaling
Family behavior learning is in decision recommender system, including phy-aware equipment, WiFi sensing module, data processing module, cloud service
Device and expansion interface, the phy-aware equipment respectively with expansion interface and the two-way electric connection of data processing module, the number
According to processing module respectively with WiFi sensing module and the two-way electric connection of cloud server.
Preferably, the specific steps are as follows:
The first step, by the environment space dependence phy-aware equipment and wireless communication signals to human body, dynamic
Object, object and other objects or equipment carry out shape, motion track, internal communication signaling etc. and are identified and perceived；
Second step passes through the different object structures such as surface, motion track, internal network devices control signaling to object
Construction Bank is characterized and is accustomed to feedback model, and constantly learns and strengthen, the accuracy of training pattern；
Third step is based on feedback model, provides user in environment after the instant data for collecting certain time segment
Or overseer's mode of learning recognition result and decision recommendation.
Preferably, the phy-aware equipment is physical sensors part, including but not limited to: temperature sensor, wet
Spend sensor, audio sensor, sonic sensor, gas sensor, photosensitive sensor, smoke sensor device, physical sensors portion
Divide the offer necessary data of predominantly building habit model and habit model learning, the information that physical sensors obtain can be by letter
Number conversion be transmitted to data processing module carry out calculation process.
Preferably, the WiFi sensing module is main functional modules, is responsible for perceiving by wireless WiFi information characteristic
The motion track of the domestic people of epipodium or object judges the attribute and elementary contour of the article, and by the data being collected by believing
Number conversion is sent to data processing module and carries out necessary calculating.
Preferably, the data processing module is mainly responsible for the calculating of the critical data of entire product, and by dependency number
According to being uploaded to, cloud server carries out building habit model or help model carries out study reinforcing.
It preferably, can be by data when the phy-aware equipment and WiFi sensing module detect necessary critical data
Simple process is first carried out in edge calculations equipment, and the data transmission to cloud server can then be carried out to building habit model
Or model is helped to carry out study reinforcing.
Compared with prior art, the beneficial effects of the present invention are: the present invention is identified by wireless network signal works as forefathers
Or surface, the motion track of object, behavioural characteristic and habit feedback model can be constructed by the data perception to space, and
User or supervised learning person's mode of learning recognition result are provided based on this model, and people or object in the space is assisted to provide fitting
The decision recommendation of the situation of presence is simultaneously executed the decision recommendation, more existing perceptive mode have can recognize people, object it is outer
Contouring and motion track in conjunction with perception data building behavioural characteristic and habit feedback model, and provide recognition result and phase
The decision recommendation of pass.
Detailed description of the invention
In order to illustrate the technical solution of the embodiments of the present invention more clearly, will be described below to embodiment required
Attached drawing is briefly described, it should be apparent that, drawings in the following description are only some embodiments of the invention, for ability
For the those of ordinary skill of domain, without creative efforts, it can also be obtained according to these attached drawings other attached
Figure.
Fig. 1 is present system functional diagram.
Fig. 2 is execution flow chart of the present invention.
Fig. 3 is the flow chart of data processing figure of present system rank.
In attached drawing, parts list represented by the reference numerals are as follows:
1- phy-aware equipment, 2-WiFi sensing module, 3- data processing module, 4- cloud server, 5- expansion interface.
Specific embodiment
Following will be combined with the drawings in the embodiments of the present invention, and technical solution in the embodiment of the present invention carries out clear, complete
Site preparation description, it is clear that described embodiments are only a part of the embodiments of the present invention, instead of all the embodiments.It is based on
Embodiment in the present invention, it is obtained by those of ordinary skill in the art without making creative efforts all other
Embodiment shall fall within the protection scope of the present invention.
Fig. 1-3 is please referred to, the present invention provides a kind of technical solution: being practised based on the user of spatial perception and internal network signaling
Used study is in decision recommender system, including phy-aware equipment 1, WiFi sensing module 2, data processing module 3, cloud service
Device 4 and expansion interface 5, phy-aware equipment 1 respectively with expansion interface 5 and the two-way electric connection of data processing module 3, at data
Manage module 3 respectively with WiFi sensing module 2 and the two-way electric connection of cloud server 4.
Wherein, the specific steps are as follows:
The first step, by the environment space dependence phy-aware equipment 1 and wireless communication signals to human body, dynamic
Object, object and other objects or equipment carry out shape, motion track, internal communication signaling etc. and are identified and perceived；
Second step passes through the different object structures such as surface, motion track, internal network devices control signaling to object
Construction Bank is characterized and is accustomed to feedback model, and constantly learns and strengthen, the accuracy of training pattern；
Third step is based on feedback model, provides user in environment after the instant data for collecting certain time segment
Or overseer's mode of learning recognition result and decision recommendation.
Phy-aware equipment 1 is physical sensors part, including but not limited to: temperature sensor, humidity sensor, sound
Video sensor, sonic sensor, gas sensor, photosensitive sensor, smoke sensor device, physical sensors part predominantly construct
It is accustomed to model and the offer necessary data of model learning is provided, the information that physical sensors obtain can be transmitted to by signal conversion
Data processing module 3 carries out calculation process.
WiFi sensing module 2 is main functional modules, and it is domestic to be responsible for perceiving epipodium by wireless WiFi information characteristic
The motion track of people or object judges the attribute and elementary contour of the article, and by the data being collected by signal conversion transmission
Necessary calculating is carried out to data processing module 3.
Data processing module 3 is mainly responsible for the calculating of the critical data of entire product, and related data is uploaded to cloud
End server 4 carries out building habit model or model is helped to carry out study reinforcing.
It, can be by data first in edge meter when phy-aware equipment 1 and WiFi sensing module 2 detect necessary critical data
It calculates and carries out simple process in equipment, the data transmission to cloud server 4 can then be carried out to building habit model or help mould
Type carries out study reinforcing.
One concrete application of the present embodiment are as follows: phy-aware equipment 1 can be transmitted to number by the information that sensor obtains
Calculation process is carried out according to processing module 3, and it is domestic that WiFi sensing module 2 is responsible for perceiving epipodium by wireless WiFi information characteristic
The motion track of people or object, judges the attribute and elementary contour of the article, and by the data transmission being collected into data processing mould
Block 3 carries out necessary calculating, and data processing module 3 is mainly responsible for the calculating of the critical data of entire product, and by dependency number
It carries out building habit model according to cloud server 4 is uploaded to or model is helped to be learnt, strengthen, it is complete by expansion interface 5
At the extension of other function.
Embodiment one can will be captured after phy-aware equipment 1 and WiFi sensing module 2 capture coherent signal
Information is transmitted to signal conversion module, further carries out signal conversion processes, and signal is completed after conversion can will treated letter
Breath is transmitted to data processing module 3, the further processing of data is carried out, by the data transmission to cloud service after the completion of processing
Device 4, cloud server 4 can carry out model construction or progress model learning and reinforcing, process according to the data information of receiving to be terminated.
Embodiment two can be by number when phy-aware equipment 1 and WiFi sensing module 2 detect necessary critical data
Simple process is carried out in edge calculations equipment according to elder generation, it then can be by the data transmission to cloud server 4, cloud server 4
Model construction/study/reinforcing etc. can be carried out to the data received, complete flow chart of data processing.
By taking intelligent washing machine as an example:
(1) it is perceived by related data, obtaining laundry washer liquid will be in a short time using finishing.
(2) it is analyzed by the habit model constructed to user data, obtains liquid detergent brand, the capacity of user's preferences
Deng and the shopping platform of preference etc..
(3) by model analysis as a result, automatic carry out the purchase that places an order for user, and at a reasonable time in section delivery
Door.
(4) it after receiving, reminds user to fill in time, completes entire aid decision process.
(5) habit model carries out relational learning according to this process, and advanced optimizes.
In the description of this specification, the description of reference term " one embodiment ", " example ", " specific example " etc. means
Particular features, structures, materials, or characteristics described in conjunction with this embodiment or example are contained at least one implementation of the invention
In example or example.In the present specification, schematic expression of the above terms may not refer to the same embodiment or example.
Moreover, particular features, structures, materials, or characteristics described can be in any one or more of the embodiments or examples to close
Suitable mode combines.
Present invention disclosed above preferred embodiment is only intended to help to illustrate the present invention.There is no detailed for preferred embodiment
All details are described, are not limited the invention to the specific embodiments described.Obviously, according to the content of this specification,
It can make many modifications and variations.These embodiments are chosen and specifically described to this specification, is in order to better explain the present invention
Principle and practical application, so that skilled artisan be enable to better understand and utilize the present invention.The present invention is only
It is limited by claims and its full scope and equivalent.
Claims (6)
1. user's behavior learning based on spatial perception and internal network signaling is in decision recommender system, including phy-aware equipment
(1), WiFi sensing module (2), data processing module (3), cloud server (4) and expansion interface (5), it is characterised in that: institute
State phy-aware equipment (1) respectively with expansion interface (5) and data processing module (3) two-way electric connection, the data processing
Module (3) respectively with WiFi sensing module (2) and cloud server (4) two-way electric connection.
2. user's behavior learning according to claim 1 based on spatial perception and internal network signaling is recommended in decision
System, which is characterized in that specific step is as follows:
The first step, by the environment space dependence phy-aware equipment (1) and wireless communication signals to human body, dynamic
Object, object and other objects or equipment carry out shape, motion track, internal communication signaling etc. and are identified and perceived；
Second step passes through the different objects building rows such as surface, motion track, internal network devices control signaling to object
It is characterized and is accustomed to feedback model, and constantly learns and strengthens, the accuracy of training pattern；
Third step is based on feedback model, provided in environment after the instant data for collecting certain time segment user or
Overseer's mode of learning recognition result and decision recommendation.
3. user's behavior learning according to claim 1 based on spatial perception and internal network signaling is recommended in decision
System, which is characterized in that the phy-aware equipment (1) is physical sensors part, including but not limited to: temperature sensor,
Humidity sensor, audio sensor, sonic sensor, gas sensor, photosensitive sensor, smoke sensor device, physical sensors
Part predominantly building habit model and the offer necessary data for being accustomed to model learning, the information that physical sensors obtain can pass through
Signal conversion is transmitted to data processing module (3) and carries out calculation process.
4. user's behavior learning according to claim 3 based on spatial perception and internal network signaling is recommended in decision
System, it is characterised in that: the WiFi sensing module (2) is main functional modules, is responsible for feeling by wireless WiFi information characteristic
The motion track for knowing the domestic people of epipodium or object judges the attribute and elementary contour of the article, and the data being collected into is passed through
Signal conversion is sent to data processing module (3) and carries out necessary calculating.
5. user's behavior learning according to claim 4 based on spatial perception and internal network signaling is recommended in decision
System, it is characterised in that: the data processing module (3) is mainly responsible for the calculating of the critical data of entire product, and will be related
Data are uploaded to cloud server (4) and carry out building habit model or model is helped to carry out study reinforcing.
6. user's behavior learning according to claim 1 based on spatial perception and internal network signaling is recommended in decision
System, it is characterised in that: when the phy-aware equipment (1) and WiFi sensing module (2) detect necessary critical data, can incite somebody to action
Data first carry out simple process in edge calculations equipment, can then construct the data transmission to cloud server (4)
Habit model helps model to carry out study reinforcing.
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| CN105912667A (en) * | 2016-04-12 | 2016-08-31 | 玉环看知信息科技有限公司 | Method and device for information recommendation and mobile terminal |
| WO2017219603A1 (en) * | 2016-06-20 | 2017-12-28 | 北京大学 | Method for identifying a wireless signal reflected by moving object |
| US9961079B1 (en) * | 2014-03-21 | 2018-05-01 | Symantec Corporation | Context aware intruder detection using WIFI MAC addresses |
-
2019
- 2019-03-27 CN CN201910238261.XA patent/CN110009454A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US9961079B1 (en) * | 2014-03-21 | 2018-05-01 | Symantec Corporation | Context aware intruder detection using WIFI MAC addresses |
| CN104111106A (en) * | 2014-07-01 | 2014-10-22 | 武汉领傲科技有限公司 | Internet of Things perception method and system based on article consumption and compositional variation |
| CN104468815A (en) * | 2014-12-22 | 2015-03-25 | 齐玉田 | Wireless sensing system and method of internet of things |
| CN105912667A (en) * | 2016-04-12 | 2016-08-31 | 玉环看知信息科技有限公司 | Method and device for information recommendation and mobile terminal |
| WO2017219603A1 (en) * | 2016-06-20 | 2017-12-28 | 北京大学 | Method for identifying a wireless signal reflected by moving object |
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