CN104361361B - The method and system for judging to fall down by cloud computing and machine learning algorithm - Google Patents
The method and system for judging to fall down by cloud computing and machine learning algorithm Download PDFInfo
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Abstract
The invention discloses a kind of method and system for judging to fall down by cloud computing and machine learning algorithm, it is related to and falls down automatic detection field.Method and system provided by the invention, by being prejudged first to the acceleration of collection, filter out and substantial amounts of non-fall down data, then data are fallen down to anticipation using linear classification algorithm to screen, simultaneously, in Cloud Server, data are fallen down by machine learning anticipation, linear classification algorithm is updated, it is this by dual judgement, while in Cloud Server, constantly sample is learnt, so as to constantly correct the method and system of renewal to linear classification algorithm, the result for falling down judgement is not only greatly improved, also improves the speed for falling down judgement.
Description
Technical field
The present invention relates to falling down automatic detection field, more particularly to a kind of judge to fall by cloud computing and machine learning algorithm
Method and system.
Background technology
As Chinese society enters aging, care and concern of the whole society to old man gradually increase.In order to improve old age
The safety of people's trip, the research for the alarm technique of the elderly's falling-resistant are also more and more.
At present, detection device is fallen down, the body shape of user is mainly detected by acceleration transducer or gyroscope
And active state, and determine whether according to these data the generation of fall events.Fall down monitoring device when in use, according to
Certain angle is worn on user, and when there is fall events generation, acceleration and angle will change, so,
Fall down monitoring device and just judge whether user occurs fall events using the principle.
But the method fallen down is judged in the prior art, its condition of falling down is acceleration transducer or gyroscope collection
Acceleration and angle change, and the necessary condition that the change of acceleration and angle, which is user, falls down but is not user
The adequate condition fallen down, if that is, user falls down, the acceleration and angle value of acceleration transducer or gyroscope are inherently
Change, still, the acceleration and angle value of acceleration transducer or gyroscope change, and user but not necessarily occurs
Fall events.So in the prior art, the acceleration simply gathered according to acceleration transducer or gyroscope and the change of angle
Change, to judge fall events occur, can produce the situation of more erroneous judgement, accuracy rate is low.
The content of the invention
It is an object of the invention to provide a kind of method and system for judging to fall down by cloud computing and machine learning algorithm,
So as to solve foregoing problems present in prior art.
To achieve these goals, the technical solution adopted by the present invention is as follows：
A kind of method for judging to fall down by cloud computing and machine learning algorithm, comprises the following steps：
S1, acceleration transducer collection acceleration, and acceleration is transferred to processor；
S2, the processor receive the acceleration, and judge whether the acceleration exceedes the threshold value of setting, if institute
The threshold value that acceleration exceedes the setting is stated, then performs step S3；If the acceleration not less than the threshold value of the setting,
Return to S1；
S3, the processor downloads linear sorting algorithm from Cloud Server, and judges institute using the linear classification algorithm
State acceleration and whether meet and fall down feature, if met, fall down；If do not met, do not fall down；
S4, whether the processor is by the acceleration of the threshold value more than the setting all in S3 and corresponding fall
Result transmitted to the Cloud Server, and whether the Cloud Server is by learning the acceleration and corresponding falling down
As a result, the linear classification algorithm is updated.
Further, in S3, in addition to the step of alarm, if fallen down, alarm.
Preferably, the acceleration transducer is 3-axis acceleration sensor.
Specifically, S2 comprises the following steps：
S201, the processor receive the acceleration；
S202, calculate the resultant acceleration of the acceleration；
S203, judges whether the resultant acceleration exceedes the threshold value of setting.
Preferably, in S2, the threshold value is configured according to the attribute of people, and the attribute of the people includes sex, age, body
At least one of high and body weight.
Preferably, in S3, the feature of falling down obtains by the following method：
S301, gather the acceleration in a period of time and the corresponding result whether fallen down；
S302, it is marked to falling down the corresponding acceleration, the acceleration marked；
S303, the acceleration information of the mark is learnt, obtain described falling down feature.
Specifically, in S4, described transmit to Cloud Server is to pass through GPRS transmission to Cloud Server.
A kind of system for judging to fall down by cloud computing and machine learning algorithm, includes successively according to data transfer direction：
Acceleration transducer, processor, data transmission set and Cloud Server.
Preferably, the data transmission set is gsm module.
Specifically, the processor includes：
Data reception module：For receiving the acceleration of acceleration transducer transmission；
Fall down anticipation module：For calculating the acceleration, and judge whether the acceleration exceedes the threshold value of setting；
Fall down judge module：For downloading linear sorting algorithm from Cloud Server, and judge to add using linear classification algorithm
Whether speed, which meets, is fallen down feature, judges whether to fall down；
Data transmission module：For by the acceleration of all threshold values more than the setting and corresponding whether falling
Result is transmitted to Cloud Server.
The beneficial effects of the invention are as follows：By being prejudged first to the acceleration of collection, largely non-fall down is filtered out
Data, data then are fallen down to anticipation using linear classification algorithm and screened, meanwhile, in Cloud Server, pass through engineering
Practise anticipation and fall down data, update linear classification algorithm, it is this by dual judgement, while in Cloud Server, constantly to sample
This is learnt, and so as to the method that renewal is constantly corrected to linear classification algorithm, not only greatly improves the knot for falling down judgement
Fruit, also improve the speed for falling down judgement.
Brief description of the drawings
Fig. 1 is the method flow schematic diagram that the embodiment of the present invention one provides；
Fig. 2 is the system structure diagram that the embodiment of the present invention two provides；
Embodiment
In order to make the purpose , technical scheme and advantage of the present invention be clearer, below in conjunction with accompanying drawing, the present invention is entered
Row is further described.It should be appreciated that embodiment described herein is not used to only to explain the present invention
Limit the present invention.
Embodiment one
As shown in figure 1, a kind of method for judging to fall down by cloud computing and machine learning algorithm, comprises the following steps：
S1, acceleration transducer collection acceleration, and acceleration is transferred to processor；
S2, the processor receive the acceleration, and judge whether the acceleration exceedes the threshold value of setting, if institute
The threshold value that acceleration exceedes the setting is stated, then performs step S3；If the acceleration not less than the threshold value of the setting,
Return to S1；
S3, the processor downloads linear sorting algorithm from Cloud Server, and judges institute using the linear classification algorithm
State acceleration and whether meet and fall down feature, if met, fall down；If do not met, do not fall down；
S4, whether the processor is by the acceleration of the threshold value more than the setting all in S3 and corresponding fall
Result transmitted to the Cloud Server, and whether the Cloud Server is by learning the acceleration and corresponding falling down
As a result, the linear classification algorithm is updated.
With in the prior art simply by the change of acceleration information come the method that judges to fall down compared with, the embodiment of the present invention
In the method for offer：
First by judging whether acceleration exceedes the threshold value of setting, to carry out falling down anticipation, if the numerical value of acceleration
More than the threshold value of setting, then it is judged to fall down in advance, otherwise, is judged to not fall down in advance；
In order to improve the accuracy for falling down judgement, then, the acceleration of the threshold value to exceeding setting in anticipation, using from cloud
The linear classification algorithm downloaded in server, which judges whether to meet, falls down feature, if met, falls down, if do not met,
Do not fall down.
Wherein, as will be understood by the skilled person in the art, linear classification algorithm is one kind in machine learning algorithm.Together
When, in embodiments of the present invention, simply judge whether acceleration meets using linear classification algorithm in native processor and fall down
Feature, without learning sample, so, the calculating pressure of native processor is greatly alleviated, so, not only increases and is originally located in
The processing speed of device is managed, while calculating accuracy rate can also be improved.
In the embodiment of the present invention, the study and study for acceleration and the sample of the corresponding result whether fallen down are more
Sample after, update linear classification algorithm process, carried out in Cloud Server, utilize the powerful cloud computing of Cloud Server
Ability completes the machine learning of above-mentioned sample.Then native processor is reinformed to download linear point updated after machine learning
Class algorithm, whether the acceleration for judging to acquire, which meets, is fallen down feature, judges whether to fall down.Due to machine learning
Process is carried out in Cloud Server, make use of the ability of cloud computing, therefore, calculating speed faster so that processing locality
Also faster, the accuracy rate of calculating is also higher for the speed that the judgement of device is fallen down.
In the embodiment of the present invention, it is after being prejudged to the acceleration of collection, just carries out machine learning and judgement,
And during anticipation, the substantial amounts of data for not meeting the condition of falling down have been filtered out, have made the data for entering machine learning and judging
Amount is greatly reduced, and therefore, the sample of machine learning is more accurate, and the amendment to linear classification algorithm is more accurate, Jin Erli
With the linear classification algorithm fall down the result for judging to obtain also can be more accurate.
Therefore, the embodiment of the present invention is screened by anticipation, linear classification algorithm and Cloud Server machine learning is to linear
Sorting algorithm is constantly corrected, updated so that the accuracy for falling down judgement is greatly improved.
In the embodiment of the present invention, in S3, the step of can also including alarming, if fallen down, alarm.The function of alarm can
To help the person of falling down timely to be succoured.
In the embodiment of the present invention, the acceleration transducer can be 3-axis acceleration sensor.
As will be understood by the skilled person in the art, the multi-shaft acceleration transducer of non-three axle can also be used.
If using 3-axis acceleration sensor, S2 specifically comprises the following steps：
S201, the processor receive the acceleration；
S202, calculate the resultant acceleration of the acceleration；
S203, judges whether the resultant acceleration exceedes the threshold value of setting.
Wherein, the acceleration magnitude of three axles of 3-axis acceleration sensor collection is respectively：X, y, z, can be according to as follows
Formula calculates resultant acceleration：sqrt(x*x+y*y+z*z).By calculating the resultant acceleration of 3-axis acceleration, and compare conjunction and accelerate
Spend and prejudged the relation between the threshold value that sets.
As will be understood by the skilled person in the art, the resultant acceleration of 3-axis acceleration can not also be calculated, directly will be each
Axle acceleration is entered compared with the threshold value set by calculating resultant acceleration, and using resultant acceleration with the threshold value set
Row compares, and can further improve the accuracy for falling down judgement.
In the embodiment of the present invention, in S2, the threshold value is configured according to the attribute of people, and the attribute of the people is inclusive
Not, at least one of age, height and body weight.Given threshold.For example all identical masculinity and femininity, threshold value can for other attributes
Can be just different, concrete numerical value can be set according to the empirical value for falling down judgement.So, according to the experience for falling down judgement
Value, different threshold values is set to the people of different attribute, the accuracy of anticipation can be improved.
In the embodiment of the present invention, in S3, the feature of falling down can obtain by the following method：
S301, gather the acceleration in a period of time and the corresponding result whether fallen down；
S302, it is marked to falling down the corresponding acceleration, the acceleration marked；
S303, the acceleration information of the mark is learnt using the linear classification algorithm, obtain described fall down
Feature.
Wherein, situation about falling down includes：Directly fallen down in the case of standing；Tripped during on foot；Tripped during running；
Before face upward, swing back, side is faced upward.The rule of hash distribution is presented for these acceleration informations for falling down situation, in two-dimensional coordinate system
In it is considered that be distributed in around an oblique line, this rule obtained using linear classification Algorithm Learning is exactly to fall down feature.
In the embodiment of the present invention, falling down the initial value of feature may need manually to be intervened, and obtain, afterwards, this method
After operation, it is possible to constantly learn new sample by Cloud Server, linear classification algorithm is constantly modified and updated,
Native processor can is using constantly correcting and the linear classification algorithm of renewal is constantly modified and more to falling down feature
Newly, the sample size of study is bigger, and linear classification algorithm is more accurate, and it is more accurate to fall down feature, using linear classification algorithm and falls down
What feature obtained fall down result will be more accurate.
It is described to transmit to Cloud Server in S4 in the embodiment of the present invention, specifically, passing through GPRS transmission to Cloud Server.
Embodiment two
As shown in Fig. 2 it is by what cloud computing and machine learning algorithm judged to fall down the embodiments of the invention provide a kind of
System, includes successively according to data transfer direction：Acceleration transducer, processor, data transmission set and Cloud Server.
Wherein, the data transmission set can be gsm module.Gsm module, it is by GSM radio frequency chips, Base-Band Processing core
Piece, memory, power discharging device etc. are integrated on one piece of wiring board, at independent operating system, GSM radio frequency processings, base band
Manage and the functional module of standard interface is provided.
Gsm module, which has, sends SMS messaging, voice call, the institute that GPRS data transmission etc. is communicated based on GSM network
There is basic function.
In the embodiment of the present invention, the processor can include：
Data reception module：For receiving the acceleration of acceleration transducer transmission；
Fall down anticipation module：For calculating the acceleration, and judge whether the acceleration exceedes the threshold value of setting；
Fall down judge module：For downloading linear sorting algorithm from Cloud Server, and judge to add using linear classification algorithm
Whether speed, which meets, is fallen down feature, judges whether to fall down；
Data transmission module：For by the acceleration of all threshold values more than the setting and corresponding whether falling
Result is transmitted to Cloud Server.
By using above-mentioned technical proposal disclosed by the invention, following beneficial effect has been obtained：By first to collection
Acceleration prejudged, filter out it is substantial amounts of it is non-fall down data, data then are fallen down to anticipation using linear classification algorithm and entered
Row is screened, meanwhile, in Cloud Server, data are fallen down by machine learning anticipation, update linear classification algorithm, it is this by double
Major punishment is broken, while in Cloud Server, constantly sample is learnt, so as to constantly correct renewal to linear classification algorithm
Method, the result for falling down judgement is not only greatly improved, also improve the speed for falling down judgement.
Each embodiment in this specification is described by the way of progressive, what each embodiment stressed be with
The difference of other embodiment, between each embodiment identical similar part mutually referring to.
Those skilled in the art should be understood that the sequential for the method and step that above-described embodiment provides can be entered according to actual conditions
Row accommodation, also can concurrently it be carried out according to actual conditions.
All or part of step in the method that above-described embodiment is related to can by program come instruct the hardware of correlation come
Complete, described program can be stored in the storage medium that computer equipment can be read, for performing the various embodiments described above side
All or part of step described in method.The computer equipment, such as：Personal computer, server, the network equipment, intelligent sliding
Dynamic terminal, intelligent home device, wearable intelligent equipment, vehicle intelligent equipment etc.；Described storage medium, such as：RAM、
ROM, magnetic disc, tape, CD, flash memory, USB flash disk, mobile hard disk, storage card, memory stick, webserver storage, network cloud storage
Deng.
Finally, it is to be noted that, herein, such as first and second or the like relational terms be used merely to by
One entity or operation make a distinction with another entity or operation, and not necessarily require or imply these entities or operation
Between any this actual relation or order be present.Moreover, term " comprising ", "comprising" or its any other variant meaning
Covering including for nonexcludability, so that process, method, commodity or equipment including a series of elements not only include that
A little key elements, but also the other element including being not expressly set out, or also include for this process, method, commodity or
The intrinsic key element of equipment.In the absence of more restrictions, the key element limited by sentence "including a ...", is not arranged
Except other identical element in the process including the key element, method, commodity or equipment being also present.
Described above is only the preferred embodiment of the present invention, it is noted that for the ordinary skill people of the art
For member, under the premise without departing from the principles of the invention, some improvements and modifications can also be made, these improvements and modifications also should
Depending on protection scope of the present invention.
Claims (8)
- A kind of 1. method for judging to fall down by cloud computing and machine learning algorithm, it is characterised in that comprise the following steps：S1, acceleration transducer collection acceleration, and acceleration is transferred to processor；S2, the processor receive the acceleration, and judge whether the acceleration exceedes the threshold value of setting, if described add Speed exceedes the threshold value of the setting, then performs step S3；If the acceleration returns not less than the threshold value of the setting S1；S3, the processor downloads linear sorting algorithm from Cloud Server, and judges described add using the linear classification algorithm Whether speed, which meets, is fallen down feature, if met, is fallen down；If do not met, do not fall down；It is described fall down feature pass through it is as follows Method obtains：S301, gather the acceleration in a period of time and the corresponding result whether fallen down；S302, it is marked to falling down the corresponding acceleration, the acceleration marked；S303, the acceleration information of the mark is learnt, obtain described falling down feature；S4, whether the processor is by the acceleration of the threshold value more than the setting all in S3 and corresponding fall down As a result transmit to the Cloud Server, the Cloud Server is by learning the acceleration and the corresponding knot whether fallen down Fruit, update the linear classification algorithm.
- 2. the method according to claim 1 for judging to fall down by cloud computing and machine learning algorithm, it is characterised in that S3 In, in addition to the step of alarm, if fallen down, alarm.
- 3. the method according to claim 1 for judging to fall down by cloud computing and machine learning algorithm, it is characterised in that institute It is 3-axis acceleration sensor to state acceleration transducer.
- 4. the method according to claim 3 for judging to fall down by cloud computing and machine learning algorithm, it is characterised in that S2 Specifically comprise the following steps：S201, the processor receive the acceleration；S202, calculate the resultant acceleration of the acceleration；S203, judges whether the resultant acceleration exceedes the threshold value of setting.
- 5. the method according to claim 1 for judging to fall down by cloud computing and machine learning algorithm, it is characterised in that S2 In, the threshold value is configured according to the attribute of people, and the attribute of the people is included in sex, age, height and body weight at least It is a kind of.
- 6. the method according to claim 1 for judging to fall down by cloud computing and machine learning algorithm, it is characterised in that S4 In, it is described to transmit to Cloud Server, specifically, passing through GPRS transmission to Cloud Server.
- 7. a kind of system for judging to fall down by cloud computing and machine learning algorithm, it is characterised in that according to data transfer direction Include successively：Acceleration transducer, processor, data transmission set and Cloud Server；The processor includes：Data reception module：For receiving the acceleration of acceleration transducer transmission；Fall down anticipation module：For calculating the acceleration, and judge whether the acceleration exceedes the threshold value of setting；Fall down judge module：For downloading linear sorting algorithm from Cloud Server, and judge acceleration using linear classification algorithm Whether meet and fall down feature, judge whether to fall down, the feature of falling down obtains by the following method：S301, gather the acceleration in a period of time and the corresponding result whether fallen down；S302, it is marked to falling down the corresponding acceleration, the acceleration marked；S303, the acceleration information of the mark is learnt, obtain described falling down feature；Data transmission module：For by the acceleration of all threshold values more than the setting and corresponding whether falling down As a result transmit to Cloud Server, the Cloud Server is by learning the acceleration and the corresponding result whether fallen down, more The new linear classification algorithm.
- 8. the system according to claim 7 for judging to fall down by cloud computing and machine learning algorithm, it is characterised in that institute It is gsm module to state data transmission set.
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| CN104771177B (en) * | 2015-05-08 | 2017-05-10 | 重庆软汇科技股份有限公司 | Tumble detection system and method based on machine learning |
| CN104794463B (en) * | 2015-05-11 | 2018-12-14 | 华东理工大学 | The system and method for indoor human body fall detection is realized based on Kinect |
| CN107247957A (en) * | 2016-12-16 | 2017-10-13 | 广州中国科学院先进技术研究所 | A kind of intelligent agricultural product sorting technique and system based on deep learning and cloud computing |
| CN109035696A (en) * | 2018-06-21 | 2018-12-18 | 福州大学 | One kind falling down detection method based on acceleration transducer |
| CN112346762A (en) * | 2020-10-30 | 2021-02-09 | 深圳Tcl新技术有限公司 | Application program upgrading method, display device and computer readable storage medium |
| CN115474919A (en) * | 2022-10-10 | 2022-12-16 | 浙江大学 | An enuresis alarm based on electrical impedance detection and its alarm method |
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