CN108769383A - Fall data processing method and Related product - Google Patents
Fall data processing method and Related product Download PDFInfo
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- CN108769383A CN108769383A CN201810401901.XA CN201810401901A CN108769383A CN 108769383 A CN108769383 A CN 108769383A CN 201810401901 A CN201810401901 A CN 201810401901A CN 108769383 A CN108769383 A CN 108769383A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04M—TELEPHONIC COMMUNICATION
- H04M1/00—Substation equipment, e.g. for use by subscribers
- H04M1/72—Mobile telephones; Cordless telephones, i.e. devices for establishing wireless links to base stations without route selection
- H04M1/724—User interfaces specially adapted for cordless or mobile telephones
- H04M1/72448—User interfaces specially adapted for cordless or mobile telephones with means for adapting the functionality of the device according to specific conditions
- H04M1/72454—User interfaces specially adapted for cordless or mobile telephones with means for adapting the functionality of the device according to specific conditions according to context-related or environment-related conditions
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04M—TELEPHONIC COMMUNICATION
- H04M1/00—Substation equipment, e.g. for use by subscribers
- H04M1/72—Mobile telephones; Cordless telephones, i.e. devices for establishing wireless links to base stations without route selection
- H04M1/724—User interfaces specially adapted for cordless or mobile telephones
- H04M1/72448—User interfaces specially adapted for cordless or mobile telephones with means for adapting the functionality of the device according to specific conditions
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04M—TELEPHONIC COMMUNICATION
- H04M2250/00—Details of telephonic subscriber devices
- H04M2250/12—Details of telephonic subscriber devices including a sensor for measuring a physical value, e.g. temperature or motion
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- Human Computer Interaction (AREA)
- Computer Networks & Wireless Communication (AREA)
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- Environmental & Geological Engineering (AREA)
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Abstract
The embodiment of the present application discloses one kind and falling data processing method and Related product, and the method is applied to electronic device, the method includes：Obtain it is multiple fall data, the data of falling are divided into multiple setting regions；The data of falling of each setting regions are input to default neural network model corresponding with each setting regions and execute forward operation and exported as a result, being determined according to the output result and are not intended to fall data；Be not intended to fall the quantity of data described in extraction, according to the total quantity of electronic device determine each setting regions be not intended to fall probability；According to the fall protection strategy for being not intended to fall each setting regions described in determine the probability.The embodiment of the present application is conducive to reduce the generation for being not intended to fall event.
Description
Technical field
This application involves electronic technology fields, and in particular to one kind falling data processing method and Related product.
Background technology
In the prior art, mobile terminal (such as mobile phone, tablet computer) has become user's first choice and frequency of use highest
Electronic device, for mobile terminal, it is producer or the unavoidable problem of user that screen is fragile, after screen is broken,
The surplus value of electronic device is just had a greatly reduced quality, because the price that most of factory repair changes screen almost alreadys exceed terminal
The surplus value.And industry prevalence 2.5D glass is more prone to fall bad and broken screen, each mainstream producer all exists as screen at present
That spends a large amount of R&D costs research raising complete machine falls drop resistant ability.
The existing processing mode for falling data is complicated, can not be that the dropproof of later stage provides effective theories integration, shadow
Ring the Experience Degree of user.
Invention content
The embodiment of the present application provides one kind and falling data processing method and Related product, falls probability beyond the question, system
Fixed each setting regions falls strategy, falls probability to reduce each setting regions.
In a first aspect, the embodiment of the present application, which provides one kind, falling data processing method, including：
Obtain it is multiple fall data, the data of falling are divided into multiple setting regions；
The data of falling of each setting regions are input to default neural network mould corresponding with each setting regions
Type executes forward operation and is exported as a result, being not intended to fall data according to output result determination；
It is not intended to fall the quantity of data described in extraction, being not intended to for each setting regions is determined according to the total quantity of electronic device
Fall probability；
According to the fall protection strategy for being not intended to fall each setting regions described in determine the probability.
Second aspect, the embodiment of the present application provide a kind of electronic device falling data processing, and the electronic device includes：
Application processor AP and communication module, the communication module are connect by least one circuit with the AP；
The communication module, for receive other electronic devices transmission fall data；
The AP is divided into multiple setting regions for that will fall data；
The AP, for the data of falling of each setting regions to be input to preset corresponding with each setting regions
Neural network model executes forward operation and is exported as a result, being not intended to fall data, extraction institute according to output result determination
State the quantity for being not intended to fall data, according to the total quantity of electronic device determine each setting regions be not intended to fall probability, according to
The fall protection plan for being not intended to fall each setting regions described in determine the probability.
The third aspect, the embodiment of the present application provide a kind of electronic device, including one or more processors, one or more
Memory, one or more transceivers, and one or more programs, one or more of programs are stored in the storage
In device, and it is configured to be executed by one or more of processors, described program includes for executing as described in relation to the first aspect
Method in step instruction.
Fourth aspect, the embodiment of the present application provide a kind of computer readable storage medium, and storage is handed over for electronic data
The computer program changed, wherein the computer program makes computer execute method as described in relation to the first aspect.
5th aspect, the embodiment of the present application provide a kind of computer program product, and the computer program product includes depositing
The non-transient computer readable storage medium of computer program is stored up, the computer is operable to make computer to execute such as the
Method described in one side.
Implement the embodiment of the present application, has the advantages that：
As can be seen that received first in the embodiment of the present application it is multiple fall data, then to fall data be divided into it is multiple
Setting regions, by the data of falling of each setting regions of artificial intelligence process, determination is not intended to fall probability, according to being not intended to fall
The fall protection strategy of each setting regions of determine the probability carries out targetedly fall protection by executing the fall protection strategy
Business, reduction are not intended to fall probability, improve the experience of user.
Description of the drawings
In order to more clearly explain the technical solutions in the embodiments of the present application, make required in being described below to embodiment
Attached drawing is briefly described, it should be apparent that, the accompanying drawings in the following description is some embodiments of the present application, 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 a kind of structural schematic diagram of electronic device；
Fig. 2 is a kind of flow diagram falling data processing method provided by the embodiments of the present application；
Fig. 2A is a kind of schematic diagram of composition input data matrix provided by the embodiments of the present application；
Fig. 2 B are a kind of schematic diagrames being inserted into data in input data matrix provided by the embodiments of the present application；
Fig. 3 is a kind of flow diagram of determining fall protection strategy process provided by the embodiments of the present application；
Fig. 3 A are the schematic diagrames that distribution is fallen in a kind of determination provided by the embodiments of the present application；
Fig. 4 is a kind of structural schematic diagram of electronic device disclosed in the embodiment of the present application；
Fig. 5 is a kind of functional unit composition block diagram of electronic device disclosed in the embodiment of the present application；
Fig. 6 is a kind of structural schematic diagram of smart mobile phone disclosed in the embodiment of the present application.
Specific implementation mode
Below in conjunction with the attached drawing in the embodiment of the present application, technical solutions in the embodiments of the present application carries out clear, complete
Site preparation describes, it is clear that described embodiment is some embodiments of the present application, instead of all the embodiments.Based on this Shen
Please in embodiment, the every other implementation that those of ordinary skill in the art are obtained without creative efforts
Example, shall fall in the protection scope of this application.
Term " first ", " second ", " third " in the description and claims of this application and the attached drawing and "
Four " etc. be for distinguishing different objects, rather than for describing particular order.In addition, term " comprising " and " having " and it
Any deformation, it is intended that cover and non-exclusive include.Such as it contains the process of series of steps or unit, method, be
The step of system, product or equipment are not limited to list or unit, but further include the steps that optionally not listing or list
Member, or further include optionally for the intrinsic other steps of these processes, method, product or equipment or unit.
Referenced herein " embodiment " is it is meant that the special characteristic, result or the characteristic that describe can wrap in conjunction with the embodiments
It is contained at least one embodiment of the application.Each position in the description occur the phrase might not each mean it is identical
Embodiment, nor the independent or alternative embodiment with other embodiments mutual exclusion.Those skilled in the art explicitly and
Implicitly understand, embodiment described herein can be combined with other embodiments.
Electronic device in the application may include smart mobile phone (such as Android phone, iOS mobile phones, Windows
Phone mobile phones etc.), tablet computer, palm PC, laptop, mobile internet device (MID, Mobile Internet
Devices) or Wearable etc., above-mentioned electronic device are only citings, and non exhaustive, are filled including but not limited to above-mentioned electronics
It sets, for convenience of description, above-mentioned electronic device is known as user equipment (User equipment, UE) in following example.
Certainly in practical applications, above-mentioned user equipment is also not necessarily limited to above-mentioned realization form, such as can also include：Intelligent vehicle-carried end
End, computer equipment etc..
The electronic device mentioned in the embodiment of the present application can be above-mentioned terminal, or server and network side are set
It is standby.
Referring initially to Fig. 1, Fig. 1 is a kind of structural schematic diagram of electronic device 100 provided by the present application, above-mentioned electronic device
100 include：Shell 110, circuit board 120, battery 130, cover board 140, touching display screen 150, velocity sensor 160, gravity pass
(the English of sensor 170：Gravity Sensor, referred to as：G-sensor), the circuit board 120, institute are set on the shell 110
Battery 130 and the cover board 140 are stated, the circuit board 120 is additionally provided with the circuit for connecting the touching display screen 150；It is described
Circuit board 120 can also include：Application processor AP180.
Above-mentioned touching display screen is specifically as follows Thin Film Transistor-LCD (Thin Film Transistor-
Liquid Crystal Display, TFT-LCD), light emitting diode (Light Emitting Diode, LED) display screen, have
Machine light emitting diode (Organic Light-Emitting Diode, OLED) display screen etc..
Velocity sensor 160, for detecting in falling process, the velocity magnitude of electronic device, picking rate value.
Gravity sensor 170, the direction for detecting acceleration and size, be equivalent to detection electronic installation falls shape
State.The function of gravity sensor, which understands, gets up fairly simple, mainly perceives the variation of acceleration, for example, shake, fall, on
The various mobile variations such as liter, decline can be converted into electric signal by gravity sensor, then pass through the meter of application processor AP180
After point counting analysis, it will be able to determine the acceleration value of the electronic device.
Optionally, above-mentioned electronic device can also include：Geomagnetic sensor and gyroscope, the geomagnetic sensor and gyroscope
It is connect respectively with application processor AP180.On the electronic device, gravity sensor not only works independently, acceptable and earth magnetism
Sensor 171, gyroscope 172 cooperate together, provide more accurate and comprehensive action induction ability.
Gyroscope 172, also known as angular-rate sensor, rotational angular velocity when for measuring deflection, tilting.In electronic device
In, gravity sensor 170 can only detect axial line movement, be unable to measure or reconstruct complete 3D actions, do not detect and turn
Dynamic action.But gyroscope 172 then can do good measurement to the action for rotating, deflecting, and can detect in real time and fall angle,
Detection electronic installation falls posture, determines electronic device and collides the contact site of object.
Fall data processing method referring to Fig.2, Fig. 2 is one kind provided by the embodiments of the present application, this method is applied to electronics
Device, the method includes：
Step S201, acquisition is multiple falls data, and the data of falling are divided into multiple setting regions.
Wherein, multiple data of falling are that the electronic device that falls of all areas falls data, which passes through leads to
Letter module receive other electronic devices transmission fall data, to fall data carry out big data analysis when, if to falling number
According to global analysis is carried out, it can not analyze and fall feature when each region is fallen, therefore not having specific aim can will fall
It falls data and is divided into multiple setting regions, big data analysis is carried out to the data of falling of each setting regions, is carried out targetedly
Fall protection helps to reduce and falls probability, and the standard for dividing setting regions can be according to reporting the electronics for falling data to fill
The location information set divides.For example, by longitude and latitude, either province or height above sea level are divided, specifically, according to province
Can be a setting regions by the same province regional classification when part divides, individually handle province area falls data,
It determines the feature of falling in each province, carries out specific aim protection.
Optionally, gravity sensor can in real time detection electronic installation acceleration, obtain acceleration information, such as continuously deposit
It is g (acceleration of gravity) in acceleration value, it is determined that the electronic device, which is in, falls state, naturally it is also possible to by other means
Determine that electronic device whether in state is fallen, does not limit specific method of determination here.
Further, obtain fall data principle be based on gravity sensor can in real time detection electronic installation acceleration
Degree, obtain acceleration value, velocity sensor can in real time detection electronic installation speed, acquisition speed value, gyroscope can be real
When detection electronic installation fall angle, angle is fallen in acquisition, when falling, acquires the multigroup of falling process multiple moment
Fall angle, fall speed and fall acceleration, data will be fallen after acquisition and preserve or be uploaded to server, to divide
Data are fallen in analysis.
Optionally, when event is fallen in determination, by locating module, the current position letter of the electronic device is obtained
Breath, report fall data while, report the location information.
Step S202, the data of falling of each setting regions are input to default god corresponding with each setting regions
Through network model, forward operation is executed, is exported as a result, being not intended to fall data according to output result determination.
Optionally, it extracts each of each setting regions and falls falling p value of angle, falling the m of speed in data
A value and q value for falling acceleration will be less than the value of corresponding predetermined threshold value in described p value, m value and q value
Zero is taken, principle is：When falling process closes to an end, either falls intentionally or be not intended to fall, falling angle, falling at this time
Terminal-velocity degree and fall acceleration all close to zero, so when numerical value for judging to fall intentionally or being not intended to fall meaning not
Greatly, and at this time numerical value is generally floating number (and precision is more), when floating number is input to neural network model, needs
Advanced row format conversion, entire calculating process is cumbersome, so, the primary system one less than respective predetermined threshold value is taken zero, simplifies fortune
Calculation process improves arithmetic speed.
Wherein, p, m, q are the integer more than 2, and p, m, q can be differed.
Wherein, the predetermined threshold value for falling angle is specifically as follows 5 °, 7 °, 10 ° or other values；Fall the default threshold of speed
Value is specifically as follows 0.1m/s, 0.15m/s, 0.2m/s or other values；The predetermined threshold value for falling acceleration is specifically as follows
0.1m/s2、0.15m/s2、0.2m/s2Or other values.
By each of take after zero the zero fallen in data it is adjacent be arranged in same row or with a line composition it is initial defeated
Enter data matrix CI0*H0*W0, then, q original input data matrix for falling data composition by the q of each setting regions
CI0*H0*W0Further it is combined as input data matrix CI0′*H0′*W0', by the original input data Matrix C I0′*H0′*
W0Zero composition of ' addition input data matrix CI corresponding with the setting input data matrix of default neural network model1*H1*
W1, by the input data matrix CI1*H1*W1It is input to the default neural network model, wherein the CI0' it is initial defeated
Enter the depth value of data, H0' be original input data height value, W0' be original input data width value, CI1It is defeated to set
Enter the depth value of data matrix, H1To set the height value of input data matrix, W1To set the width value of input data matrix.
Wherein, the strategy for adding zero is specifically as follows interlacing zero-adding or every row zero-adding.
Zero it can be increased by taking the value for being less than corresponding predetermined threshold value in the p value, m value and q value
Zero in input data matrix can improve arithmetic speed, because being read in operation when neural network carries out operation
When a certain piece of input data matrix is all zero, does not then need operation and directly carry out convolution algorithm with one piece of input data matrix；
In addition, by by input data matrix input data matrix CI0′*H0′*W0Zero composition of ' addition and the default neural network mould
The corresponding input data matrix CI of setting input data matrix of type1*H1*W1, build and setting input data matrix size
(SIZE) corresponding input data matrix can improve the accuracy of operation result, similarly, also may be used by way of addition zero
To improve arithmetic speed.
Below according to Fig. 2A and Fig. 2 B, the concrete mode of composition input data matrix is introduced：It is assumed that in each setting regions
It passes 6 groups and falls data, every group is fallen in data and fall velocity amplitude comprising 18, fall angle value and fall acceleration value, is such as schemed
Shown in 2A, left panels fall data for one group to carry out obtaining data matrix after taking zero, and wherein grey parts are that the group is fallen
Zero in data, right graphic be by the group fall 9 zeros in data keep left carry out same column arrangement after obtain one it is defeated
Enter data matrix CI0*H0*W0.Then fall data (it is assumed that every group is fallen data and all obtain 9 zeros) according to such as Fig. 2A institutes by 6 groups
After the mode shown carries out the position for taking zero-sum to rearrange zero, input data matrix CI is obtained0′*H0′*W0', the input data
Matrix C I0′*H0′*W0' left panels as shown in Figure 2 B, wherein grey parts shown in Fig. 2 B are that zero further obtains
The size of the setting input data matrix CI*H*W of the neural network model is taken, if CI=CI ', W=W ', H=2H0', then it needs
To input data matrix CI0′*H0′*W0' interpolation data, wherein this is sentenced in the way of row addition zero to input data matrix
CI0′*H0′*W06 row null value datas of ' addition obtain input data matrix CI1*H1*W1, it is of course also possible to take the flat of adjacent rows
Mean value is added data, and the application does not limit the mode of interpolation data.
As it can be seen that by way of composition input data matrix as shown in Figure 2 A and 2B, if the size of convolution kernel is 3*
3, since the grey parts shown by Fig. 2 B are all zero, convolution algorithm is needed not participate in, operation time is saved, improves fortune
Calculate speed.
Optionally, in the operation of neural network, that is, artificial intelligence, trained artificial intelligence model is i.e. by default
The input data defined obtains weight data by trained operation, and trained artificial intelligence model is the convolution of determination
Core, i.e. 3*3, for convolution kernel, the specification with 3*3 and 5*5, certainly in practical applications, above-mentioned weights may be used also
Think that other specifications, the application are not intended to limit the concrete form of above-mentioned specification.
When for convolution algorithm, being for convolution kernel 3*3 can not directly and CI1*H1*W1Convolution algorithm is directly carried out,
The mode of operation can be convolution kernel, that is, 3*3 to be cut into a basic granularity, then by basic granularity and input data CI1*
H1*W1Convolution algorithm is executed, i.e., is moved on the input data with basic granularity, is successively carried out convolution algorithm, obtain operation result.
Further, the corresponding threshold interval of the operation result for falling data of the setting regions is obtained, determination falls into nothing
Meaning falls the quantity of the data in section, that is, is not intended to the number fallen.
Step S203, it is not intended to fall the quantity of data described in extraction, each setting is determined according to the total quantity of electronic device
Being not intended to of region falls probability.
Optionally, the total quantity that user in the setting regions uses electronic device is counted first, and specific embodiment can
Think：Obtain the international mobile equipment identification number IMEI (International reported when the setting regions endpoint registration
Mobile Equipment Identity, referred to as：IMEI total quantity), using the total quantity of IMEI as the sum of electronic device
Amount, alternatively, obtain the number of electronic devices of access network, to access the number of electronic devices of network as using in the setting regions
Family uses the total quantity of electronic device, certain the application not to limit the side for the total quantity for determining the setting regions electronic device
Formula.
Further, the number for being not intended to fall obtained based on above-mentioned steps S202, can obtain the nothing of the setting regions
Meaning fall probability=be not intended to drop number/electronic device total quantity.
Step S204, it is not intended to fall the fall protection strategy of each setting regions described in determine the probability according to.
Optionally, probability is fallen based on being not intended in above-mentioned steps S203, determines the fall protection plan of each setting regions
Slightly, specifically, it is not intended to fall probability according to each setting regions, formulates and be not intended to fall the corresponding prompting plan of probability with this
Slightly, alternatively, Preservation tactics.
As can be seen that in the embodiment of the present application, the data of falling reported being divided according to region, are divided into multiple
Setting regions, and handle each setting regions respectively falls data, and being not intended to for each setting regions is determined by artificial intelligence
Fall data, obtain each setting regions is not intended to fall probability, and formulates each setting regions according to being not intended to fall probability
Fall protection strategy, carry out for service, promptings targetedly fallen to each setting regions, reduces and each sets area
Domain is not intended to fall probability, improves user experience.
It is a kind of method of determining fall protection strategy provided by the embodiments of the present application, this method application refering to Fig. 3, Fig. 3
In electronic device, described method includes following steps：
Step S301, obtain each setting regions is not intended to fall probability, determines that being not intended to fall the first of maximum probability sets
Determine region.
Step S302, the location information of first setting regions being not intended to fall in data, the location information are extracted
Electronic device current location information when to fall.
Wherein, electronic device report fall data when, by locating module by the falling position information of the electronic device
It reports together.
Step S303, falling position is marked in the map of the first setting regions according to the positional information, obtains label
Number is more than the falling position of first threshold, highlights falling position generation and falls distribution map.
As shown in Figure 3A, Fig. 3 A show the mode that falling position is marked in the map of the first setting regions, and will mark
Note is shown in a manner of block diagram, and falling point for tri- positions falling position A, B and C is shown by way of block diagram
Cloth, block diagram height reflection label number (drop number) number, wherein the label number of falling position A be more than first
Threshold value is dashed forward the corresponding block diagram color marks of falling position A are black (color usually most paid attention to human eye to mark)
Go out the falling position that display label number is more than first threshold.Alternatively, showing the label of falling position A by the form of picture
Number, the corresponding a certain range of label number of each picture, certainly, the application does not limit the mode that display marks number.
Optionally, this falls area and is bound with map software, and highlighted fall can be consulted by map software
The 3D of position schemes.
Wherein, which is specifically as follows 50,60,70,80 or other values.
Step S304, be such as located at first setting regions, show first setting regions be not intended to fall probability, carry
Show that the first area is that high probability falls region, falls distribution map described in push.
Optionally, when user comes first setting regions for the first time, due to not knowing about the state of falling of this area, very may be used
It can generate and fall event.When detect the user for the first time be located at first setting regions when, carry out Push Service, show this first
Setting regions is not intended to fall probability, and it is that high probability falls region, and will fall map and be pushed to use to prompt first setting regions
Family, so that user observes specific falling position.
Step S305, such as it is located at highlighted falling position, opens Push Service, the position is reminded to fall for high probability
Position starts fall protection.
Optionally, when user, which is located at label number, is more than the position of first threshold, fall protection is automatically turned on.
Further, it since the result under big data analysis to some users and is not suitable for, needs to carry out each user
Specific aim is analyzed.When user is located at first setting regions, if detecting consumer electronic device for the first time in the first area
Positioned at the above-mentioned position that highlights when falling, then largely, determine that the user can send out highlighting position
Event is fallen in life, when user, which is again positioned at, highlights position, automatically turns on fall protection, falls guarantor relative to direct unlatching
Shield is more targeted, opens fall protection according to the custom of each user, and save power consumption.
Further, it obtains the multiple of multiple setting regions to be not intended to fall probability, that formulates each setting regions falls guarantor
Shield strategy, fall protection strategy is similar with the above-mentioned fall protection strategy of first setting regions is formulated, and makes each setting
The prompting Preservation tactics in region, herein no longer narration in detail.
As can be seen that in embodiments herein, be not intended to fall probability by each setting regions of determination, formulate with
It is not intended to fall the corresponding fall protection strategy of probability, each setting regions is carried out targetedly to remind strategy, is advantageously reduced
Each setting regions is not intended to fall probability, improves user experience；Moreover, when maximum probability determines that user is more in drop number
When position is fallen, fall protection is just opened, compared with traditional always on fall protection, reduces power consumption, and can
Fall protection is targetedly opened, user experience is improved.
In one example, the method further includes：
Obtain the multiple setting regions falls examining report, determines falling as a result, described fall for each setting regions
It is the damage caused by the electronic device after electronic device collision to fall result；
It determines to fall in the multiple setting regions and loses the setting regions that data probability is more than second threshold in result, when
When the setting regions falls event, automatically backup data, it is to be understood that the data that automated back-up is arranged are memory
It is smaller and to the vital data of user, such as the information stored in phone contacts' information, backup record.
It is more than setting for third threshold value further, it is determined that falling screen in result in the multiple setting regions and being crushed probability
Region is determined, when the setting regions falls event, by the head end for falling center of gravity and moving to the electronic device of electronic device
Or position, the concrete mode that center of gravity is fallen in movement are：Lead can be loaded in fall protection system, moved by mobile lead
It is dynamic to fall center of gravity.
It is consistent with above-mentioned Fig. 2, embodiment shown in Fig. 3, referring to Fig. 4, Fig. 4 is one kind provided by the embodiments of the present application
The structural schematic diagram of electronic device 400, the electronic device 400 include touching display screen, gravity sensor, velocity sensor,
Gyroscope, as shown in figure 4, the terminal 400 includes processor, memory, communication interface and one or more programs, wherein
Said one or multiple programs are different from said one or multiple application programs, and said one or multiple programs are stored in
It states in memory, and is configured to be executed by above-mentioned processor, above procedure includes the instruction for executing following steps；
Obtain it is multiple fall data, the data of falling are divided into multiple setting regions；
The data of falling of each setting regions are input to default neural network mould corresponding with each setting regions
Type executes forward operation and is exported as a result, being not intended to fall data according to output result determination；
It is not intended to fall the quantity of data described in extraction, being not intended to for each setting regions is determined according to the total quantity of electronic device
Fall probability；
According to the fall protection strategy for being not intended to fall each setting regions described in determine the probability.
In a possible example, it is input to and each setting regions by the data of falling of each setting regions
In terms of corresponding default neural network model, the instruction in above procedure is specifically used for executing following operation：Extract the setting
Region falls p value for falling angle in data, falls m value of speed and fall q value of acceleration, by the p
Value in value, m value and q value less than corresponding predetermined threshold value takes zero, will take the zero phase fallen in data after zero
Adjacent is arranged in same row or with a line composition original input data Matrix C I0*H0*W0, by the original input data matrix
CI0*H0*W0Zero composition of addition input data matrix corresponding with the setting input data matrix of default neural network model
CI1*H1*W1, by the input data matrix CI1*H1*W1It is input to the default neural network model, wherein the CI0For
The depth value of original input data, H0For the height value of original input data, W0For the width value of original input data, CI1To set
Determine the depth value of input data matrix, H1To set the height value of input data matrix, W1To set the width of input data matrix
Value.
In a possible example, the instruction in above procedure is additionally operable to execute following operation：
Obtain the multiple setting regions falls examining report, determines that each setting regions loses data probability；
It determines and loses the setting regions that data probability is more than second threshold in the multiple setting regions, in the setting regions
When falling event, automatically backup data.
One kind of the electronic device 500 for falling data processing involved in above-described embodiment is shown refering to Fig. 5, Fig. 5
Possible functional unit forms block diagram, and electronic device 500 includes obtaining application processor AP510, communication module 520, the communication
Module is connect at least through a circuit 530 with AP510；
Communication module 520, for receive other electronic devices transmission fall data；
AP510, for the data of falling to be divided into multiple setting regions；
AP510, for the data of falling of each setting regions to be input to preset corresponding with each setting regions
Neural network model executes forward operation and is exported as a result, being not intended to fall data, extraction institute according to output result determination
State the quantity for being not intended to fall data, according to the total quantity of electronic device determine each setting regions be not intended to fall probability, according to
The fall protection plan for being not intended to fall each setting regions described in determine the probability.
In a possible example, it is input to and each setting regions pair by the data of falling of each setting regions
In terms of the default neural network model answered, AP510 is specifically used for the extraction setting regions and falls the p for falling angle in data
A value, m value for falling speed and q value for falling acceleration are respectively right by being less than in described p value, m value and q value
The value for the predetermined threshold value answered takes zero, by take the zero fallen in data after zero it is adjacent be arranged in same row or with a line group
At original input data Matrix C I0*H0*W0, by the original input data Matrix C I0*H0*W0Zero composition of addition is preset with described
The corresponding input data matrix CI of setting input data matrix of neural network model1*H1*W1, by the input data matrix
CI1*H1*W1It is input to the default neural network model, wherein the CI0For the depth value of original input data, H0It is initial
The height value of input data, W0For the width value of original input data, CI1To set the depth value of input data matrix, H1To set
Determine the height value of input data matrix, W1To set the width value of input data matrix.
In a possible example, fall guarantor what root was not intended to fall according to each setting regions described in determine the probability
Shield strategy aspect, AP510 is specific to determine the first setting regions for being not intended to fall maximum probability, extracts first setting regions
Be not intended to fall the location information in data, according to the positional information in the map of the first setting regions label fall position
It sets, obtains the falling position that label number is more than first threshold, highlight falling position generation and fall distribution map, such as position
In first setting regions, show first setting regions be not intended to fall probability, it is high general to prompt the first area
Rate falls region, falls distribution map described in push.
In a possible example, fall guarantor what root was not intended to fall according to each setting regions described in determine the probability
Shield strategy aspect, AP510 are specifically used for, as being located at highlighted falling position, opening Push Service, it is height to remind the position
Probability falling position starts fall protection.
In a possible example, AP510 is additionally operable to obtain the examining report that falls of the multiple setting regions, determines
Each setting regions loses data probability, determines and loses the setting that data probability is more than second threshold in the multiple setting regions
Region, when the setting regions falls event, automatically backup data.
It is shown and the part-structure of the relevant mobile phone of electronic device provided by the embodiments of the present application refering to Fig. 6, Fig. 6
Block diagram.With reference to figure 6, mobile phone includes：Radio frequency (Radio Frequency, referred to as：RF) circuit 710, memory 720, input unit
730, the components such as sensor 750, voicefrequency circuit 760, WIFI module 770, application processor 780 and power supply 790.This field
Technical staff is appreciated that handset structure shown in Fig. 6 does not constitute the restriction to mobile phone, may include than illustrate it is more or
Less component either combines certain components or different components arrangement.
Each component parts of mobile phone is specifically introduced with reference to Fig. 6：
Input unit 730 can be used for receiving the number or character information of input, and generate with the user setting of mobile phone with
And the related key signals input of function control.Specifically, input unit 730 may include touching display screen 733, fingerprint identification device
731, face identification device 734, iris identification device 735 and other input equipments 732.Specifically, other input equipments 732
It can include but is not limited to physical button, function key (such as volume control button, switch key etc.), trace ball, mouse, operation
It is one or more in bar etc..
Optionally, which further includes communication module, which is used to receive falling for other electronic devices transmission
Data.
Sensor 750 may include gravity sensor 751, velocity sensor 752, gyroscope 753, wherein gravity sensitive
Device 751 falls acceleration for acquiring, the acceleration that falls is transmitted to application processor 780；
Velocity sensor 752 falls speed for acquiring, the speed of falling is transmitted to application processor 780；
Gyroscope 753 falls angle for acquiring, the angle of falling is transmitted to application processor 780；
Wherein, application processor 780 fall data for receiving, the data of falling are divided into multiple setting regions,
The data of falling of each setting regions are input to default neural network model corresponding with each setting regions, are executed just
To operation, is exported and be not intended to fall data as a result, being determined according to the output result, be not intended to fall the number of data described in extraction
Amount, determine each setting regions be not intended to fall probability, be not intended to fall each setting regions described in determine the probability according to described
Fall protection plan.
Optionally, the data of falling of each setting regions are being input to default god corresponding with each setting regions
Through in terms of network model, application processor 780 falls the p for falling angle in data specifically for extracting the setting regions
A value, m value for falling speed and q value for falling acceleration are respectively right by being less than in described p value, m value and q value
The value for the predetermined threshold value answered takes zero, by take fall after zero zero in data it is adjacent be arranged in same row or with a line form just
Beginning input data matrix CI0*H0*W0, by the original input data Matrix C I0*H0*W0Zero composition of addition and the default nerve
The corresponding input data matrix CI of setting input data matrix of network model1*H1*W1, by the input data matrix CI1*H1*
W1It is input to the default neural network model, wherein the CI0For the depth value of original input data, H0For initial input number
According to height value, W0For the width value of original input data, CI1To set the depth value of input data matrix, H1It is inputted for setting
The height value of data matrix, W1To set the width value of input data matrix.
Optionally, in terms of being not intended to fall the fall protection strategy of each setting regions described in determine the probability according to,
Application processor 780 extracts first setting regions specifically for determining the first setting regions for being not intended to fall maximum probability
Be not intended to fall the location information in data, according to the positional information determine falling position, according to the falling position generate
Fall distribution map, it is such as first in the falling position fallen and highlight drop number more than first threshold in distribution map
It is secondary to be located at first setting regions, show first setting regions be not intended to fall probability, prompt the first area to be
High probability falls region, falls distribution map described in push.
Optionally, application processor 780 are additionally operable to be located at first setting regions for the first time as non-, be set described first
Determine region to occur when for the first time falling, determine the falling position fallen for the first time, falls protrusion in distribution map as described in being located at
The falling position of display starts fall protection when being again positioned at the highlighted falling position.
Optionally, application processor 780 are additionally operable to obtain the examining report that falls of the multiple setting regions, determine every
A setting regions loses data probability, determines and loses the setting area that data probability is more than second threshold in the multiple setting regions
Domain, when the setting regions falls event, automatically backup data.
Application processor 780 is the control centre of mobile phone, utilizes each portion of various interfaces and connection whole mobile phone
Point, by running or execute the software program and/or module that are stored in memory 720, and calls and be stored in memory 720
Interior data execute the various functions and processing data of mobile phone, to carry out integral monitoring to mobile phone.Optionally, using processing
Device 780 may include one or more processing units.
In addition, memory 720 may include high-speed random access memory, can also include nonvolatile memory, example
Such as at least one disk memory, flush memory device or other volatile solid-state parts.
RF circuits 710 can be used for sending and receiving for information.In general, RF circuits 710 include but not limited to antenna, at least one
A amplifier, transceiver, coupler, low-noise amplifier (Low Noise Amplifier, LNA), duplexer etc..In addition,
RF circuits 710 can also be communicated with network and other equipment by radio communication.Above-mentioned wireless communication can use any communication
Standard or agreement, including but not limited to global system for mobile communications (Global System of Mobile
Communication, referred to as：GSM), general packet radio service (General Packet Radio Service, abbreviation：
GPRS), CDMA (Code Division Multiple Access, abbreviation：CDMA), wideband code division multiple access (Wideband
Code Division Multiple Access, referred to as：WCDMA), long term evolution (Long Term Evolution, abbreviation：
LTE), Email, short message service (Short Messaging Service, abbreviation：SMS) etc..
Mobile phone may also include at least one sensor 750, such as optical sensor, motion sensor and other sensors.
Specifically, optical sensor may include ambient light sensor and proximity sensor, wherein ambient light sensor can be according to ambient light
Light and shade adjust the brightness of touching display screen, proximity sensor can when mobile phone is moved in one's ear, close touching display screen and/
Or backlight.As a kind of motion sensor, accelerometer sensor can detect in all directions (generally three axis) acceleration
Size can detect that size and the direction of gravity when static, can be used to identify mobile phone posture application (such as horizontal/vertical screen switching,
Dependent game, magnetometer pose calibrating), Vibration identification correlation function (such as pedometer, tap) etc.；It can also configure as mobile phone
The other sensors such as gyroscope, barometer, hygrometer, thermometer, infrared sensor, details are not described herein.
Voicefrequency circuit 760, loud speaker 761, microphone 762 can provide the audio interface between user and mobile phone.Audio-frequency electric
The transformed electric signal of the audio data received can be transferred to loud speaker 761 by road 760, and sound is converted to by loud speaker 761
Signal plays；On the other hand, the voice signal of collection is converted to electric signal by microphone 762, is turned after being received by voicefrequency circuit 760
It is changed to audio data, then audio data is played after application processor 780 handles, it is such as another to be sent to through RF circuits 710
Mobile phone, or audio data is played to memory 720 to be further processed.
WIFI belongs to short range wireless transmission technology, and mobile phone can help user's transceiver electronics postal by WIFI module 770
Part, browsing webpage and access streaming video etc., it has provided wireless broadband internet to the user and has accessed.Although Fig. 6 is shown
WIFI module 770, but it is understood that, and it is not belonging to must be configured into for mobile phone, it can not change as needed completely
Become in the range of the essence of application and omits.
Mobile phone further includes the power supply 790 (such as battery) powered to all parts, and optionally, power supply can pass through power supply pipe
Reason system and application processor 780 are logically contiguous, to realize management charging, electric discharge and power consumption by power-supply management system
The functions such as management.
Although being not shown, mobile phone can also be including camera, bluetooth module, light compensating apparatus, light sensor etc., herein not
It repeats again.
The embodiment of the present application also provides a kind of computer storage media, wherein computer storage media storage is for electricity
The computer program that subdata exchanges, it is any as described in above method embodiment which so that computer is executed
One kind falling some or all of data processing method step.
The embodiment of the present application also provides a kind of computer program product, and the computer program product includes storing calculating
The non-transient computer readable storage medium of machine program, the computer program are operable to that computer is made to execute such as above-mentioned side
Any type described in method embodiment falls some or all of data processing method step.
It should be noted that for each method embodiment above-mentioned, for simple description, therefore it is all expressed as a series of
Combination of actions, but those skilled in the art should understand that, the application is not limited by the described action sequence because
According to the application, certain steps can be performed in other orders or simultaneously.Secondly, those skilled in the art should also know
It knows, embodiment described in this description belongs to alternative embodiment, involved action and module not necessarily the application
It is necessary.
In the above-described embodiments, it all emphasizes particularly on different fields to the description of each embodiment, there is no the portion being described in detail in some embodiment
Point, it may refer to the associated description of other embodiment.
In several embodiments provided herein, it should be understood that disclosed device, it can be by another way
It realizes.For example, the apparatus embodiments described above are merely exemplary, for example, the unit division, it is only a kind of
Division of logic function, formula that in actual implementation, there may be another division manner, such as multiple units or component can combine or can
To be integrated into another system, or some features can be ignored or not executed.Another point, shown or discussed is mutual
Coupling, direct-coupling or communication connection can be by some interfaces, the INDIRECT COUPLING or communication connection of device or unit,
Can be electrical or other forms.
The unit illustrated as separating component may or may not be physically separated, aobvious as unit
The component shown may or may not be physical unit, you can be located at a place, or may be distributed over multiple
In network element.Some or all of unit therein can be selected according to the actual needs to realize the mesh of this embodiment scheme
's.
In addition, each functional unit in each embodiment of the application can be integrated in a processing unit, it can also
It is that each unit physically exists alone, it can also be during two or more units be integrated in one unit.Above-mentioned integrated list
The form that hardware had both may be used in member is realized, can also be realized in the form of software program module.
If the integrated unit is realized in the form of software program module and sells or use as independent product
When, it can be stored in a computer-readable access to memory.Based on this understanding, the technical solution of the application substantially or
Person says that all or part of the part that contributes to existing technology or the technical solution can body in the form of software products
Reveal and, which is stored in a memory, including some instructions are used so that a computer equipment
(can be personal computer, server or network equipment etc.) executes all or part of each embodiment the method for the application
Step.And memory above-mentioned includes：USB flash disk, read-only memory (ROM, Read-Only Memory), random access memory
The various media that can store program code such as (RAM, Random Access Memory), mobile hard disk, magnetic disc or CD.
One of ordinary skill in the art will appreciate that all or part of step in the various methods of above-described embodiment is can
It is completed with instructing relevant hardware by program, which can be stored in a computer-readable memory, memory
May include：Flash disk, read-only memory (English：Read-Only Memory, referred to as：ROM), random access device (English：
Random Access Memory, referred to as：RAM), disk or CD etc..
The embodiment of the present application is described in detail above, specific case used herein to the principle of the application and
Embodiment is expounded, the description of the example is only used to help understand the method for the present application and its core ideas；
Meanwhile for those of ordinary skill in the art, according to the thought of the application, can in specific embodiments and applications
There is change place, in conclusion the contents of this specification should not be construed as limiting the present application.
Claims (11)
1. one kind falling data processing method, which is characterized in that the method includes：
Obtain it is multiple fall data, the data of falling are divided into multiple setting regions；
The data of falling of each setting regions are sequentially inputted to default neural network mould corresponding with each setting regions
Type executes forward operation and is exported as a result, determining each setting regions according to the output result of each setting regions
Be not intended to fall data；
It is not intended to fall the quantity of data described in extraction, determines that each setting regions is not intended to fall according to the total quantity of electronic device
Probability；
According to the fall protection strategy for being not intended to fall each setting regions described in determine the probability.
2. according to the method described in claim 1, it is characterized in that, it is described by each setting regions fall data be input to
The corresponding default neural network model of each setting regions, including：
The setting regions is extracted to fall p value for falling angle in data, fall m value of speed and fall acceleration
The value for being less than corresponding predetermined threshold value in the p value, m value and q value is taken zero, will take falling after zero by q value
Zero in data it is adjacent be arranged in same row or with a line composition original input data Matrix C I0*H0*W0, will be described first
Beginning input data matrix CI0*H0*W0Zero composition of addition is corresponding with the setting input data matrix of default neural network model
Input data matrix CI1*H1*W1, by the input data matrix CI1*H1*W1It is input to the default neural network model,
Wherein, the CI0For the depth value of original input data, H0For the height value of original input data, W0For original input data
Width value, CI1To set the depth value of input data matrix, H1To set the height value of input data matrix, W1It is inputted for setting
The width value of data matrix.
3. method according to claim 1 or 2, which is characterized in that the data of falling include electronic device when falling
Current location information is not intended to fall the fall protection strategy of each setting regions described in determine the probability, packet described in the basis
It includes：
Determine that the first setting regions for being not intended to fall maximum probability, extraction first setting regions are not intended to fall in data
Location information marks falling position in the map of the first setting regions according to the positional information, obtains label number and is more than
The falling position of first threshold highlights falling position generation and falls distribution map；
Such as it is located at first setting regions, show first setting regions is not intended to fall probability, prompts firstth area
Domain is that high probability falls region, falls distribution map described in push.
4. according to the method described in claim 3, it is characterized in that, the method further includes：
Such as it is located at highlighted falling position, opens Push Service, it is high probability falling position to remind the position, and startup is fallen
Protection.
5. according to the method described in claim 1, it is characterized in that, the method further includes：
Obtain the multiple setting regions falls examining report, determines that each setting regions loses data probability；
It determines and loses the setting regions that data probability is more than second threshold in the multiple setting regions, occur in the setting regions
When falling event, automatically backup data.
6. a kind of electronic device falling data processing, which is characterized in that the electronic device includes：Application processor AP and logical
Believe that module, the communication module are connect by least one circuit with the AP；
The communication module, for receive other electronic devices transmission fall data；
The AP is divided into multiple setting regions for that will fall data；
The AP, for the data of falling of each setting regions to be input to default nerve corresponding with each setting regions
Network model execution forward operation is exported to be not intended to fall data as a result, being determined according to the output result, extracts the nothing
Meaning falls the quantity of data, according to the total quantity of electronic device determine each setting regions be not intended to fall probability, according to described
It is not intended to fall the fall protection plan of each setting regions described in determine the probability.
7. electronic device according to claim 6, which is characterized in that
The AP, m for falling the p value for falling angle in data specifically for the extraction setting regions, falling speed
It is worth and falls q value of acceleration, the value that corresponding predetermined threshold value is less than in the p value, m value and q value is taken
Zero, by take the zero fallen in data after zero it is adjacent be arranged in same row or with a line form original input data matrix
CI0*H0*W0, by the original input data Matrix C I0*H0*W0The setting of addition zero composition and the default neural network model
The corresponding input data matrix CI of input data matrix1*H1*W1, by the input data matrix CI1*H1*W1It is input to described pre-
If neural network model, wherein the CI0For the depth value of original input data, H0For the height value of original input data, W0
For the width value of original input data, CI1To set the depth value of input data matrix, H1To set the height of input data matrix
Angle value, W1To set the width value of input data matrix.
8. the electronic device described according to claim 6 or 7, which is characterized in that the data of falling include electronics when falling
The current location information of device, the AP are not intended to fall the first setting regions of maximum probability, described in extraction specifically for determining
The location information of first setting regions being not intended to fall in data, marks falling position in the map of the first setting regions, obtains
It takes label number to be more than the falling position of first threshold, highlights falling position generation and fall distribution map, as being located at institute
State the first setting regions, show first setting regions be not intended to fall probability, prompt the first area to fall for high probability
It settles in an area domain, falls distribution map described in push.
9. a kind of electronic device, which is characterized in that including processor, memory, communication interface and one or more program,
In, one or more of programs are stored in the memory, and are configured to be executed by the processor, described program
It include the instruction that the step in any one of 1-5 methods is required for perform claim.
10. a kind of computer readable storage medium, which is characterized in that the computer-readable recording medium storage is used for electron number
According to the computer program of exchange, wherein it is as described in any one in claim 1-5 that the computer program so that computer executes
Method, the computer include electronic device.
11. a kind of computer program product, which is characterized in that the computer program product includes storing computer program
Non-transient computer readable storage medium, the computer program are operable to that computer is made to execute such as claim 1-5
Method described in one.
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| CN201810401901.XA CN108769383B (en) | 2018-04-28 | 2018-04-28 | Fall data processing method and related product |
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| JP2000241442A (en) * | 1999-02-22 | 2000-09-08 | Sharp Corp | Protective mechanism and portable device for drop detection mechanism and magnetic disk device |
| WO2016100639A1 (en) * | 2014-12-19 | 2016-06-23 | Corning Incorporated | Protection mechanisms for cover glass of handheld device during drop event |
| CN205336332U (en) * | 2015-12-08 | 2016-06-22 | 深圳天珑无线科技有限公司 | Mobile phone |
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