CN108600488A - A kind of novel protection handset set based on artificial intelligence - Google Patents
A kind of novel protection handset set based on artificial intelligence Download PDFInfo
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- CN108600488A CN108600488A CN201810737403.2A CN201810737403A CN108600488A CN 108600488 A CN108600488 A CN 108600488A CN 201810737403 A CN201810737403 A CN 201810737403A CN 108600488 A CN108600488 A CN 108600488A
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- iic bus
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- 238000013473 artificial intelligence Methods 0.000 title claims abstract description 10
- 238000013528 artificial neural network Methods 0.000 claims abstract description 26
- 238000012545 processing Methods 0.000 claims abstract description 12
- 230000004069 differentiation Effects 0.000 claims abstract description 8
- 238000000034 method Methods 0.000 claims description 16
- 230000008569 process Effects 0.000 claims description 13
- WHXSMMKQMYFTQS-UHFFFAOYSA-N Lithium Chemical compound [Li] WHXSMMKQMYFTQS-UHFFFAOYSA-N 0.000 claims description 11
- 229910052744 lithium Inorganic materials 0.000 claims description 11
- 238000012937 correction Methods 0.000 claims description 9
- 238000001514 detection method Methods 0.000 claims description 9
- 238000005259 measurement Methods 0.000 claims description 9
- 238000007599 discharging Methods 0.000 claims description 6
- 230000005611 electricity Effects 0.000 claims description 3
- 230000008676 import Effects 0.000 claims description 3
- 238000007781 pre-processing Methods 0.000 claims description 3
- 238000012549 training Methods 0.000 claims description 3
- 238000006116 polymerization reaction Methods 0.000 claims 1
- 238000012544 monitoring process Methods 0.000 abstract description 7
- 230000003044 adaptive effect Effects 0.000 abstract description 3
- 230000004888 barrier function Effects 0.000 description 5
- 230000001133 acceleration Effects 0.000 description 3
- 230000035772 mutation Effects 0.000 description 3
- 230000003139 buffering effect Effects 0.000 description 2
- 238000004891 communication Methods 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 238000002360 preparation method Methods 0.000 description 2
- 239000012491 analyte Substances 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 238000007689 inspection Methods 0.000 description 1
- 238000013507 mapping Methods 0.000 description 1
- 238000004377 microelectronic Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000002093 peripheral effect Effects 0.000 description 1
- 230000000717 retained effect Effects 0.000 description 1
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04M—TELEPHONIC COMMUNICATION
- H04M1/00—Substation equipment, e.g. for use by subscribers
- H04M1/02—Constructional features of telephone sets
- H04M1/18—Telephone sets specially adapted for use in ships, mines, or other places exposed to adverse environment
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
- G01S17/02—Systems using the reflection of electromagnetic waves other than radio waves
- G01S17/06—Systems determining position data of a target
- G01S17/08—Systems determining position data of a target for measuring distance only
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
- G01S17/88—Lidar systems specially adapted for specific applications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
- G01S17/88—Lidar systems specially adapted for specific applications
- G01S17/93—Lidar systems specially adapted for specific applications for anti-collision purposes
-
- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
- G08B21/18—Status alarms
- G08B21/24—Reminder alarms, e.g. anti-loss alarms
-
- H04B5/72—
Abstract
The present invention is a kind of novel protection handset set based on artificial intelligence, compared with prior art, hardware neural network accelerator is used to carry out data processing to testee and repeatedly differentiate, monitoring to extreme terrain, accurate data are obtained, it is adaptive by it, self-organizing, the characteristics such as self-learning capability, more accurate hazard region has been obtained to judge, and the bluetooth in cell-phone cover is used to send out vibration and warning reminding user to the bluetooth equipment of pairing, application range of the present invention is wider, suitable for monitoring field, advantageous data are provided for extreme terrain differentiation to support.
Description
Technical field
The invention belongs to data monitoring field, more particularly to a kind of novel protection handset set based on artificial intelligence.
Background technology
With popularizing for smart mobile phone, more energy are placed on mobile phone by people, more next even when on foot
More people becomes " race of bowing ", it is various because see the mobile phone forget to see road caused by safety accident it is more and more, cause
Casualties and economic loss.
At present the barrier of mainstream, be mainly bounce technique apart from detection technique, main operational principle is：Distance-measuring equipment is logical
It crosses ultrasonic transmitter or black light light emitting diode sends out ultrasonic wave or black light to the body surface of detection, then visit
Ultrasonic receiver or light-sensitive element inside measurement equipment are received from the reflected ultrasonic wave of searching surface or black light, so
Time difference between calculating transmitting afterwards and receiving, the distance to obtain residing for detecting object surface.
Range sensor based on reflection hair is widely used, and main application scenarios are mostly industrial machinery, traffic safety guarantor
Hinder instrument, surveying and mapping tool, aircraft and robot field.
The portable device with external physical environment data monitoring has much at present, such as：Smart mobile phone, smart mobile phone
As embedded device, a large amount of sensor is contained in inside, and acceleration transducer and gyro sensor therein acquire mobile phone
The exercise data of holder simultaneously carries out moving state identification and record, but this equipment can not detect pavement behavior effectively
Sensor, catastrophe risk landform can not be detected, while mobile phone itself needs to run operating system and application program,
The process resource that interior of mobile phone processor can be occupied will produce big for the higher earth bulging analyte detection of requirement of real time
The delay of amount, while the speed of service of slow mobile phone can be also dragged, bring very unfavorable shadow for the reliability of entire data acquisition
It rings.How situation differentiation process to be optimized using artificial neural network, how more quickly and accurately to jeopardously
It is the main problem of the invention solved that shape, which differentiate,.
Invention content
In order to solve the above-mentioned technical problem, the present invention is a kind of novel protection handset set based on artificial intelligence, skill
Art scheme is：
Including cell-phone cover, raise one's voice equipped with iic bus time-of-flight sensor, poly-lithium battery, vibrator, alarm in cell-phone cover
Device and controller module, the controller module send and receive the number of iic bus time-of-flight sensor by iic bus
According to, and provide power supply by poly-lithium battery；
Iic bus time-of-flight sensor, using Vl53l0X sensors, for being sent out to testee with strobing frequency
Infrared laser beam, and receive the light beam returned by body surface diffusing reflection, by calculate light send out and receive light it
Between time difference calculate at a distance from testee；
The controller module uses Intel Curie's modules, has been internally integrated an Intel quark x1000 processing
Device, hardware neural network accelerator, bluetooth BLE4.0 base band, power management, six axle sensors and periphery I/O circuits, China and foreign countries
It includes timer, universal input/output to enclose I/O circuits（GPIO）, AD converter, IC bus（IIC）Interface module, reality
When clock chip（RTC）Module, initialization and digital independent, charging and discharging lithium battery pipe of the controller module for sensor
Reason, data processing and warning information are sent；
The vibrator and alarm speaker pass through universal input/output（GPIO）Driving.
Further, the poly-lithium battery controls the charging/discharging function of mobile phone by power management.
Further, the bluetooth BLE4.0 base band can be connect with the equipment with bluetooth.
Using the intelligent protection cell-phone cover of claim 1, operating process is as follows：
Step 1 initializes iic bus time-of-flight sensor；
To the hardware neural network accelerator initialization in master controller module, and import pavement behavior recognition training data；
Step 2, gathered data, master controller module are measured by driving iic bus to read iic bus time-of-flight sensor
The data arrived；
Step 3, master controller module by the measurement data received be transmitted to iic bus time-of-flight sensor carry out data it is pre-
Processing；
Preprocessed data is carried out pattern discrimination by step 4, hardware neural network accelerator, i.e., whether there is or not road surface hazard regions；
Step 5, according to the differentiation of hardware neural network accelerator as a result, when without road surface hazard region, by data return to step
Two, and carry out next pavement behavior detection；Otherwise, vibrator and alarm speaker will be driven to notify user by bluetooth.
Further, in step 4 hardware neural network accelerator by preprocessed data carry out attitude algorithm data correction and
Two step of data buffer zone, preprocessed data first pass through attitude algorithm data correction and enter data buffer zone, and data buffer zone is filled out
Hardware neural network accelerator will be imported after full to handle.
Further, the attitude algorithm data correction measures mobile phone shell and quilt using six axle sensors in main control module
It surveys the inclination angle of object and holds the status data taken, data are compared with the measurement data in step 2, and amendment step two
In data.
Beneficial effects of the present invention are：The present invention is a kind of novel protection handset set based on artificial intelligence, and existing
Technology is compared, and is used hardware neural network accelerator and is carried out data processing to testee and differentiate repeatedly, to extreme terrain
Monitoring, obtained accurate data, by characteristics such as its adaptive, self-organizing, self-learning capabilities, it is more accurate to have obtained
Hazard region judge, and the bluetooth in cell-phone cover has been used to send out vibration and warning reminding user to the bluetooth equipment of pairing,
Application range of the present invention is wider, is suitable for monitoring field, and providing advantageous data for extreme terrain differentiation supports.
Description of the drawings
Fig. 1 is circuit theory schematic diagram of the present invention;
Fig. 2 is operating process flow chart of the present invention;
Fig. 3 is data prediction flow chart of the present invention.
Specific implementation mode
The present invention is a kind of novel protection handset set based on artificial intelligence, including cell-phone cover, and IIC is equipped in cell-phone cover
Bus time-of-flight sensor, poly-lithium battery, vibrator, alarm speaker and controller module.
Iic bus time-of-flight sensor：That is range sensor is produced using ST Microelectronics
VL53L0X sensors, can reach 2000 millimeters of measurement range, after the completion of sensor initializing, it will be sent out to testee
Go out to carry the infrared laser beam of certain strobing frequency, and receive the light beam returned by body surface diffusing reflection, by calculating light
Line, which sends out and receive the time difference between light, can calculate the distance of testee.
Poly-lithium battery：Whole mobile phone covers the main power supply of product, while can also be carried out to being sleeved on mobile phone therein
Charging, you can to realize charger baby function, the mistake of its charging and discharging is controlled by the power management module built in master control module
Journey.In order to ensure the reliable operating of system, whole electricity will not be used for charger baby function by power management module, but be retained
A part of electricity supplies the various components inside of sensor and main control module.
Master controller module：It is responsible for initialization and digital independent, the charging and discharging lithium battery of iic bus time-of-flight sensor
Management, data processing and warning information are sent.The present invention uses Intel Curie's modules, has been internally integrated an Intel
Quark x1000 processors, hardware neural network accelerator, bluetooth BLE4.0 super low-power consumptions base band, power management, acceleration and
The function modules such as angular-rate sensor, periphery I/O circuits, wherein periphery I/O circuits include timer, universal input/output
（GPIO）, AD converter, IC bus（IIC）Interface module, real-time timepiece chip（RTC）Module, entire module have
High-effect, multi-functional, the advantages that integrated level is high, compact, simple peripheral circuit, the volume of product can be reduced significantly.
As shown in Fig. 2, operating process of the present invention is as follows：
Initialization：Iic bus time-of-flight sensor is initialized, the preparation of gathered data is carried out；Initialize master control mould
Pavement behavior recognition training data are imported wherein, carry out the preparation of data processing by the internal hardware neural network accelerator of block.
Data acquire：Master controller module is by driving iic bus to read the data that sensor measurement arrives.
Data prediction：The data being collected into from iic bus time-of-flight sensor are pre-processed, convenient for hardware god
Data are differentiated through network accelerator.
Hardware Processing with Neural Network：Pretreated data are subjected to pattern discrimination, pavement behavior is generated and differentiates result.
Handling result judges：Judge that the differentiation of hardware neural network accelerator as a result, if normal road surface, then returns to number
According to gatherer process, carries out pavement behavior next time and detects, control bluetooth baseband is otherwise sent into warning message to the mobile phone of user,
And control included vibrator and send out vibration alarming, after user releases alarm, turn again to normal acquisition process.
As shown in figure 3, process of data preprocessing explanation of the present invention：
This product is using the hardware neural network accelerator of master controller module internal come to iic bus time-of-flight sensor number
According to being identified, judge, but since the hardware neural network accelerator of master controller module internal can only be to having certain length
Data handled, while user is when adept machine, and it is completely random variation to hold by angle and mode, can be caused
The data that iic bus time-of-flight sensor detects generate great deviation.So needing to being passed from the iic bus flight time
The initial data that sensor obtains is pre-processed.
Processing procedure is divided into two steps：Attitude algorithm data correction process and data buffering process.Wherein, attitude algorithm
Data correction process measures what the inclination angle of mobile phone and testee and holding was taken first with six axle sensors inside main control module
State, then according to the angle measured, the initial data measured to iic bus time-of-flight sensor is modified.
The initial data read from iic bus time-of-flight sensor, first passes around attitude algorithm data correction, then
It is stored in data buffer zone, after the completion of all data cells of buffering area are all refreshed, is sent into hardware neural network accelerator
It is handled.
The present invention using the time-of-flight sensor based on black light as detection sensor, by measure light transmitting with
The time difference of return calculates the distance between barrier.In view of a variety of different road conditions, convenient for more efficient inspection
The barrier and hollow landform in front of user are surveyed, using the solution of " derivative method ", i.e. detection sensor returned data is
The mutation of no generation to a certain extent, to judge the condition of road surface in front of user.It is carried out using artificial neural network more accurate
True quick obstacle recognition, and " pattern matcher " neural network computing in intel (R) Curie (TM) module will be utilized to add
Fast module；The acceleration and angular speed sensor in intel (R) Curie (TM) module be will also use to detect the holding by shape of product
State, for eliminate due to user holds the state by inclination angle and caused by detecting error；And pass through intel (R) Curie (TM) module
Interior Bluetooth communication module carries out the communication with mobile phone, increases the mode to user reminding.
When user begins to use this product, iic bus time-of-flight sensor will be come with certain frequency to user's walking
Direction emits the laser beam of black light, and segment beam will be reflected into the reception window of sensor, passed through by the object in front
The light intensity and reflection interval of reflected light are detected, iic bus time-of-flight sensor can calculate object and use
The distance at family, and pass data back master control module.When the hazard regions such as hollow or barrier occurs in user's road ahead, pass
A degree of mutation can occur for the data of sensor, and at this very moment, this mutation will be regarded as unsafe condition by main control module,
And information will be prompted to by vibrator, alarm speaker and bluetooth module and pass to user.
Since actual user's occupation mode is full of many uncertain factors, cause the angular way that user holds by equipment each
It is different, and then measurement data is caused inaccurate phenomenons occur, thus we are by six axle sensor moulds in master control module
Block is held user the posture taken and is resolved, and compensated to measurement data, to adapt to various use occasions.
In order to more quickly, more accurately carry out the detection of the hazard regions such as barrier, hollow, we will utilize people
Artificial neural networks optimize differentiation process, i.e., carry out data using the hardware neural network accelerator in master control module
Processing, by characteristics such as its adaptive, self-organizing, self-learning capabilities, master control module, which will be continued to optimize, differentiates detection
As a result, can simultaneously make more quickly and accurately hazard region differentiation, application range of the present invention is wider, is suitable for monitoring field, is
Extreme terrain differentiates that providing advantageous data supports.
As it will be easily appreciated by one skilled in the art that the foregoing is merely illustrative of the preferred embodiments of the present invention, not to
The limitation present invention, all within the spirits and principles of the present invention made by all any modification, equivalent and improvement etc., should all include
Within protection scope of the present invention.
Claims (6)
1. a kind of novel protection handset set based on artificial intelligence, including cell-phone cover, which is characterized in that set in the cell-phone cover
There are iic bus time-of-flight sensor, poly-lithium battery, vibrator, alarm speaker and controller module, the controller
Module sends and receivees the data of iic bus time-of-flight sensor by iic bus, and provides electricity by poly-lithium battery
Source；
Iic bus time-of-flight sensor, using Vl53l0X sensors, for being sent out to testee with strobing frequency
Infrared laser beam, and receive the light beam returned by body surface diffusing reflection, by calculate light send out and receive light it
Between time difference calculate at a distance from testee；
The controller module uses Intel Curie's modules, has been internally integrated an Intel quark x1000 processing
Device, hardware neural network accelerator, bluetooth BLE4.0 base band, power management, six axle sensors and periphery I/O circuits, China and foreign countries
It includes timer, universal input/output to enclose I/O circuits（GPIO）, AD converter, IC bus（IIC）Interface module, reality
When clock chip（RTC）Module, initialization and digital independent, charging and discharging lithium battery pipe of the controller module for sensor
Reason, data processing and warning information are sent；
The vibrator and alarm speaker pass through universal input/output（GPIO）Driving.
2. a kind of novel protection handset set based on artificial intelligence as described in claim 1, which is characterized in that the polymerization
Object lithium battery controls the charging/discharging function of mobile phone by power management.
3. a kind of novel protection handset set based on artificial intelligence as described in claim 1, which is characterized in that the bluetooth
BLE4.0 base band can be connect with the equipment with bluetooth.
4. using the cell-phone cover of claim 1, operating process is as follows：
Step 1 initializes iic bus time-of-flight sensor；
To the hardware neural network accelerator initialization in master controller module, and import pavement behavior recognition training data；
Step 2, gathered data, master controller module are measured by driving iic bus to read iic bus time-of-flight sensor
The data arrived；
Step 3, master controller module by the measurement data received be transmitted to iic bus time-of-flight sensor carry out data it is pre-
Processing；
Preprocessed data is carried out pattern discrimination by step 4, hardware neural network accelerator, i.e., whether there is or not road surface hazard regions；
Step 5, according to the differentiation of hardware neural network accelerator as a result, when without road surface hazard region, by data return to step
Two, and carry out next pavement behavior detection；Otherwise, vibrator and alarm speaker will be driven to notify user by bluetooth.
5. operating process as claimed in claim 4, which is characterized in that hardware neural network accelerator will be pre- in the step 4
Processing data carry out attitude algorithm data correction and two step of data buffer zone, preprocessed data first pass through attitude algorithm data correction
Into data buffer zone, data buffer zone will import hardware neural network accelerator after being filled and handle.
6. operating process as claimed in claim 5, which is characterized in that the attitude algorithm data correction is using in main control module
Six axle sensors measure the inclination angle of mobile phone shell and testee and hold the status data taken, by the measurement in data and step 2
Data are compared, and the data in amendment step two.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810737403.2A CN108600488A (en) | 2018-07-06 | 2018-07-06 | A kind of novel protection handset set based on artificial intelligence |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
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| CN201810737403.2A CN108600488A (en) | 2018-07-06 | 2018-07-06 | A kind of novel protection handset set based on artificial intelligence |
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| CN108600488A true CN108600488A (en) | 2018-09-28 |
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| CN201810737403.2A Pending CN108600488A (en) | 2018-07-06 | 2018-07-06 | A kind of novel protection handset set based on artificial intelligence |
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