CN108408521A - A kind of big data analysis system and method based on elevator passenger daily behavior - Google Patents
A kind of big data analysis system and method based on elevator passenger daily behavior Download PDFInfo
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- CN108408521A CN108408521A CN201810039989.5A CN201810039989A CN108408521A CN 108408521 A CN108408521 A CN 108408521A CN 201810039989 A CN201810039989 A CN 201810039989A CN 108408521 A CN108408521 A CN 108408521A
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B66—HOISTING; LIFTING; HAULING
- B66B—ELEVATORS; ESCALATORS OR MOVING WALKWAYS
- B66B5/00—Applications of checking, fault-correcting, or safety devices in elevators
- B66B5/0006—Monitoring devices or performance analysers
- B66B5/0012—Devices monitoring the users of the elevator system
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- Maintenance And Inspection Apparatuses For Elevators (AREA)
Abstract
The present invention provides a kind of big data analysis system based on elevator passenger daily behavior, including data acquisition unit, data analysis unit, data comparing unit, anomaly analysis unit and big data platform, data acquisition unit is connected to data analysis unit data analysis unit and is connected to data comparing unit, abnormal data is sent to anomaly analysis unit by data comparing unit, and the attribute of anomaly analysis unit judges abnormal data simultaneously sends signal according to its attribute to corresponding mechanism.The present invention also provides a kind of big data analysis methods based on elevator passenger daily behavior.The monitoring of the present invention and judge that judgements from surface current attribute and present case develops to the judgement of potential situation, the support of advantageous data can be provided under the environment of times that big data develops, preferably using the value of big data platform for more mechanisms.
Description
Technical field
The present invention relates to big data fields, more particularly to the big data analysis technology based on elevator passenger daily behavior.
Background technology
Elevator is as a important building vehicles.Passenger, can be with many daily rows when taking elevator
For, and the daily behavior of passenger includes many information, can obtain its daily behavior rule, the abnormal behaviour beyond rule can be with
It is recorded and analyzed as improper data.Analysis is acquired to the daily behavior data of passenger, to for the big of corresponding passenger
Data analysis provides strong data support for intelligent and safe city, personal health monitoring, personal reference model etc. and ensures.
The detection of same domain at present is concentrated mainly on what happens inside lift car, such as Chinese patent application
201410408748.5, the monitoring system and monitoring method of abnormal conditions in a kind of lift car are provided, including be set to electricity
At least one 3D body-sensings camera in terraced car, 3D body-sensings camera send out the original sensing data flow acquired
Give signal processing apparatus；Signal processing apparatus judges the behavior dynamic of passenger, and whether exception or passenger are in danger
State；When signal processing apparatus judge passenger behavior dynamic abnormal or passenger it is in the hole, to emergency treatment device
Send indication signal.The present invention is based on 3D body-sensing camera works, the unexpected passenger of generation can not only rescued in time, but also can
The rescue difficulty of trapped person is reduced, while can reduce, prevent the generation of incident of violence between passenger in lift car.
The shortcomings that technical solution is that the technical solution is mainly according to the real-time of the 3D body-sensing cameras acquisition in car
Signal, wherein the behavior dynamic abnormal for the judgement passenger that should be particularly mentioned that or passenger are in the hole, to emergency treatment device
Indication signal is sent, this method can only judge current surface properties, can not extend.
Invention content
For the defects of background technology, the present invention provides a kind of big data analysis system based on elevator passenger daily behavior
System can detect the surface properties of passenger and compare the inherent nature of analysis passenger by big data, to be more mechanisms
Data are provided to support.
For this purpose, the present invention uses following technical scheme：A kind of big data analysis system based on elevator passenger daily behavior,
Including data acquisition unit, data analysis unit, data comparing unit, anomaly analysis unit and big data platform, data acquisition
Unit is mounted in lift car and acquires the information in lift car, data acquisition unit be connected to data analysis unit and to
It sends acquired information, and data analysis unit analyzes received information, and analysis result is sent to big data platform,
Data analysis unit is connected to data comparing unit and the data of analysis is sent to data comparing unit, and data comparing unit connects
It is connected to big data platform and therefrom obtains day regular data as foundation, data comparing unit is compared and counted by data analysis unit and greatly
It is compared according to the data of platform and judges whether abnormal data, abnormal data is sent to anomaly analysis by data comparing unit
Unit, the attribute of anomaly analysis unit judges abnormal data simultaneously send signal according to its attribute to corresponding mechanism.
Further, data acquisition unit includes common camera, depth camera, infrared detecting set and audio collecting device
In it is one or more, data acquisition unit acquires the image and audio-frequency information of passenger in lift car in real time.
Further, data analysis unit is real time data analysis unit, which includes general place
One or more in reason equipment CPU, ARM, DSP, GPU, FPGA, ASIC, real time data analysis unit acquires single according to data
The information analysis of member obtains the body surface attribute, human body attribute and voice attributes of passenger, to obtain the synthesized attribute of passenger.
Further, the normal data of passenger's attribute is stored in big data platform.
Further, data comparing unit includes one in general purpose processing device CPU, ARM, DSP, GPU, FPGA, ASIC
Kind is a variety of.
The present invention also provides a kind of big data analysis method based on elevator passenger daily behavior, this method is using above-mentioned
Big data analysis system simultaneously includes the following steps：
（1）Data acquisition unit acquires the data information of current passenger in lift car, which includes the voice of passenger
The image information of information and passenger；
（2）The data information of current passenger is sent to data analysis unit by data acquisition unit；
（3）Data analysis unit analyzes the data information of current passenger, obtains the attribute information of current passenger；
（4）The attribute information of current passenger is sent to data comparing unit by data analysis unit；
（5）Data comparing unit obtains the big data information of passenger's attribute from big data platform, and believes with the attribute of current passenger
Breath is compared, and judges whether abnormal data, if it does not exist, then step terminates, if it does, entering in next step；
（6）Abnormal data is sent to abnormal comparing unit by data comparing unit；
（7）Abnormal comparing unit pushes signal according to the attribute of abnormal data to different mechanisms.
Further, data analysis unit includes to the analysis of passenger's attribute：
A1, passenger's shell temperature and voice messaging are analyzed by the method for audio data analysis；
A2, the human body attribute that passenger is analyzed by the method for machine learning or pattern-recognition, including height, the age, gender,
Dress, hair style.
The beneficial effects of the invention are as follows：The present invention is improved for common defect of the monitoring without daily behavioral characteristic, and one
Aspect sends the data to data center, and obtain the daily attribute of passenger by center analysis by using data acquisition unit,
These attributes include but not limited to the gender of passenger, the age, temperature, facial characteristics, frequency, sound intensity etc., on the other hand, by from
Daily attribute data is obtained in big data platform, is compared with current data, if the daily attribute of passenger occurs currently
Mutation then may determine that the health status or life abnormality of passenger, to be monitored for intelligent and safe city, personal health,
The information such as personal reference model for the prior art that compares, monitoring of the invention and judge from surface current attribute and work as
The judgement of preceding situation develops to the judgement of potential situation, can preferably utilize big number under the environment of times that big data develops
According to the value of platform, provides advantageous data for more mechanisms and support.
Description of the drawings
Fig. 1 is the flow chart of the present invention.
Fig. 2 is the frame schematic diagram of the present invention.
Specific implementation mode
Technical scheme of the present invention is described in further details below in conjunction with attached drawing, it is noted that embodiment is only
It is to play the role of explanation, is not limitation of the invention.
Embodiment 1, a kind of big data analysis system based on elevator passenger daily behavior.
The analysis system of the present embodiment, based on the big data platform of passenger's attribute, including data acquisition unit, data analysis
Unit, data comparing unit, anomaly analysis unit and big data platform, data acquisition unit include common camera, depth phase
One or more in machine, infrared detecting set and audio collecting device, data acquisition unit acquires passenger in lift car in real time
Image and audio-frequency information；Data analysis unit is real time data analysis unit, which includes general place
One or more in reason equipment CPU, ARM, DSP, GPU, FPGA, ASIC, real time data analysis unit acquires single according to data
The information analysis of member obtains the body surface attribute, human body attribute and voice attributes of passenger, to obtain the synthesized attribute of passenger；Data
Comparing unit includes one or more in general purpose processing device CPU, ARM, DSP, GPU, FPGA, ASIC.
The normal data of passenger's attribute is stored in big data platform, the data source of big data platform is mainly a certain region
Interior each elevator or the collected information of monitoring carry out analysis via Data Analysis Platform and finally obtain a series of passenger's attribute
Information.
Data acquisition unit is mounted in lift car and acquires the information in lift car, and data acquisition unit is connected to
Data analysis unit is simultaneously sent to acquired information, and data analysis unit analyzes received information, and by analysis result
It is sent to big data platform, data analysis unit is connected to data comparing unit and that the data of analysis are sent to data is more single
Member, data comparing unit, which is connected to big data platform and therefrom obtains day regular data and be used as, compares foundation, and data comparing unit will
The data of data analysis unit and big data platform, which are compared, judges whether abnormal data, and data comparing unit will be abnormal
Data are sent to anomaly analysis unit, the attribute of anomaly analysis unit judges abnormal data and according to its attribute to corresponding mechanism
Send signal.
Embodiment 2, a kind of big data analysis method based on elevator passenger daily behavior.
Analysis system described in the analysis method Application Example 1 of the present embodiment, and include the following steps：
（1）Data acquisition unit acquires the data information of current passenger in lift car, which includes the voice of passenger
The image information of information and passenger；
（2）The data information of current passenger is sent to data analysis unit by data acquisition unit；
（3）Data analysis unit analyzes the data information of current passenger, obtains the attribute information of current passenger；
Data analysis unit includes to the analysis of passenger's attribute：
A1, passenger's shell temperature and voice messaging, the method for audio data analysis are analyzed by the method for audio data analysis
The including but not limited to means such as foreground difference, inter-frame difference, depth map analysis, discrete transform, voice messaging include speech frequency,
Voice sound intensity etc.；
A2, pass through machine learning or pattern-recognition（Including but not limited to neural network, SVM, grader, deep learning）Method
Analyze the human body attribute, including height, age, gender, dressing, hair style, facial characteristics etc. of passenger.
（4）The attribute information of current passenger is sent to data comparing unit by data analysis unit；
（5）Data comparing unit obtains the big data information of passenger's attribute from big data platform, and believes with the attribute of current passenger
Breath is compared, and judges whether abnormal data, if it does not exist, then step terminates, if it does, entering in next step；
（6）Abnormal data is sent to abnormal comparing unit by data comparing unit；
（7）Abnormal comparing unit pushes signal according to the attribute of abnormal data to different mechanisms.
Data comparing unit is that the current every attribute of passenger is compared with the attribute stored in its big data platform,
If the attribute value stored in the every attribute of passenger currently and its big data platform is in a certain range, it is judged as normally,
Step terminates, if it exceeds value range then notifies abnormal comparing unit, the effect of abnormal comparing unit is that attribute is inconsistent
Attribute in the current attribute and big data platform of passenger is compared in detail, such as data comparing unit only discovers whether to deposit
In inconsistent situation, if it does, indicate that exception, and be specifically which attribute abnormal, then be by abnormal comparing unit Lai
Judged, for example,
In some cases, the sign of passenger exists abnormal, such as the suddenly changes such as temperature anomaly or speech frequency, then passenger
There may be health exceptions, this is appropriate to the occasion to health center's transmission data and push, and notifies passenger by health center.
In some cases, passenger's dressing in a short time transformation is very big, and shell temperature, speech frequency etc. have differences,
This appropriate to the occasion mechanism of transmitting bank pays close attention to its nearest economic conditions；If economic conditions turn excellent, and without bad economic record, can take the circumstances into consideration
Improve reference scoring；If economy turns bad, and has bad reference to record, sustainable concern, and makes corresponding tune to its economic reference
It is whole.
In some cases, if it find that passenger's abnormal emotion fluctuation, and body surface temperature frequent occurrence within certain a period of time
Degree, speech frequency etc. have differences, and magnetic spy is detected there are many places metal stick-like object, this appropriate to the occasion notice intelligent and safe center
Pay close attention to its nearest trace, it is understood that there may be security risk.
Claims (8)
1. a kind of big data analysis system based on elevator passenger daily behavior, characterized in that including data acquisition unit, data
Analytic unit, data comparing unit, anomaly analysis unit and big data platform, data acquisition unit are mounted in lift car simultaneously
The information in lift car is acquired, data acquisition unit is connected to data analysis unit and is sent to acquired information, number
Received information is analyzed according to analytic unit, and analysis result is sent to big data platform, and data analysis unit is connected to number
It is sent to data comparing unit according to comparing unit and by the data of analysis, data comparing unit is connected to big data platform and therefrom
Day regular data is obtained as foundation is compared, the data of data analysis unit and big data platform are compared by data comparing unit
Judge whether that abnormal data is sent to anomaly analysis unit by abnormal data, data comparing unit, anomaly analysis unit is sentenced
The attribute of disconnected abnormal data simultaneously sends signal according to its attribute to corresponding mechanism.
2. a kind of big data analysis system based on elevator passenger daily behavior according to claim 1, characterized in that number
Include one or more in common camera, depth camera, infrared detecting set and audio collecting device, data according to collecting unit
Collecting unit acquires the image and audio-frequency information of passenger in lift car in real time.
3. a kind of big data analysis system based on elevator passenger daily behavior according to claim 1, characterized in that number
According to analytic unit be real time data analysis unit, the real time data analysis unit include general purpose processing device CPU, ARM, DSP,
One or more in GPU, FPGA, ASIC, real time data analysis unit must start a work shift according to the information analysis of data acquisition unit
Body surface attribute, human body attribute and the voice attributes of visitor, to obtain the synthesized attribute of passenger.
4. a kind of big data analysis system based on elevator passenger daily behavior according to claim 1, characterized in that big
The normal data of passenger's attribute is stored on data platform.
5. a kind of big data analysis system based on elevator passenger daily behavior according to claim 1, characterized in that number
Include one or more in general purpose processing device CPU, ARM, DSP, GPU, FPGA, ASIC according to comparing unit.
6. a kind of big data analysis system based on elevator passenger daily behavior according to claim 1, characterized in that different
Normal analytic unit receives the abnormal data that data comparing unit is sent, and judges the attribute of the abnormal data, and according to the attribute, institute is right
The different situations of the passenger answered push signal to different mechanisms.
7. a kind of big data analysis method based on elevator passenger daily behavior, characterized in that this method application claim 1-6
Any one of described in big data analysis system and include the following steps：
（1）Data acquisition unit acquires the data information of current passenger in lift car, which includes the voice of passenger
The image information of information and passenger；
（2）The data information of current passenger is sent to data analysis unit by data acquisition unit；
（3）Data analysis unit analyzes the data information of current passenger, obtains the attribute information of current passenger；
（4）The attribute information of current passenger is sent to data comparing unit by data analysis unit；
（5）Data comparing unit obtains the big data information of passenger's attribute from big data platform, and believes with the attribute of current passenger
Breath is compared, and judges whether abnormal data, if it does not exist, then step terminates, if it does, entering in next step；
（6）Abnormal data is sent to abnormal comparing unit by data comparing unit；
（7）Abnormal comparing unit pushes signal according to the attribute of abnormal data to different mechanisms.
8. a kind of big data analysis method based on elevator passenger daily behavior according to claim 7, characterized in that step
Suddenly（3）Middle data analysis unit includes to the analysis of passenger's attribute：
A1, passenger's shell temperature and voice messaging are analyzed by the method for audio data analysis；
A2, the human body attribute that passenger is analyzed by the method for machine learning or pattern-recognition, including height, the age, gender,
Dress, hair style.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109969896A (en) * | 2019-04-16 | 2019-07-05 | 杭州再灵云梯信息科技有限公司 | Elevator passenger daily behavior data analysis system |
| CN111646333A (en) * | 2020-05-26 | 2020-09-11 | 上海建工四建集团有限公司 | Elevator running state evaluation method and system based on hybrid data mining |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104030115A (en) * | 2013-03-06 | 2014-09-10 | 株式会社日立制作所 | Elevator |
| CN106379788A (en) * | 2016-12-07 | 2017-02-08 | 李天璞 | Elevator passenger identity recognition and people counting device and method |
| CN107522053A (en) * | 2017-07-11 | 2017-12-29 | 浙江新再灵科技股份有限公司 | A kind of elevator platform detecting system and method based on audio analysis |
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2018
- 2018-01-16 CN CN201810039989.5A patent/CN108408521A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104030115A (en) * | 2013-03-06 | 2014-09-10 | 株式会社日立制作所 | Elevator |
| CN106379788A (en) * | 2016-12-07 | 2017-02-08 | 李天璞 | Elevator passenger identity recognition and people counting device and method |
| CN107522053A (en) * | 2017-07-11 | 2017-12-29 | 浙江新再灵科技股份有限公司 | A kind of elevator platform detecting system and method based on audio analysis |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109969896A (en) * | 2019-04-16 | 2019-07-05 | 杭州再灵云梯信息科技有限公司 | Elevator passenger daily behavior data analysis system |
| CN111646333A (en) * | 2020-05-26 | 2020-09-11 | 上海建工四建集团有限公司 | Elevator running state evaluation method and system based on hybrid data mining |
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