CN108550236A - fire monitoring method and device - Google Patents
fire monitoring method and device Download PDFInfo
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- CN108550236A CN108550236A CN201810205411.2A CN201810205411A CN108550236A CN 108550236 A CN108550236 A CN 108550236A CN 201810205411 A CN201810205411 A CN 201810205411A CN 108550236 A CN108550236 A CN 108550236A
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- fire behavior
- mobile terminal
- infrared
- fire
- environment
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B17/00—Fire alarms; Alarms responsive to explosion
- G08B17/06—Electric actuation of the alarm, e.g. using a thermally-operated switch
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/10—Image acquisition
- G06V10/12—Details of acquisition arrangements; Constructional details thereof
- G06V10/14—Optical characteristics of the device performing the acquisition or on the illumination arrangements
- G06V10/143—Sensing or illuminating at different wavelengths
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/10—Terrestrial scenes
Abstract
The invention discloses a kind of fire monitoring method and device, this method includes：When meeting default fire monitoring trigger condition, the infrared data that mobile terminal is presently in environment is obtained；Extraction and the relevant infrared signature of fire behavior from infrared data；According to infrared signature and default fire behavior prediction model, prediction mobile terminal is presently in the fire behavior of environment；When predicting mobile terminal and being presently in environment and have fire behavior, the safe early warning of preset kind is triggered.It can be seen that, technical solution of the present invention, specific machine learning algorithm and training sample can be used to train the model for predicting fire behavior, when needing to predict fire behavior, mobile terminal can obtain the infrared data for being presently in environment, extraction and the relevant infrared signature of fire behavior from infrared data, and the model according to the infrared signature and for predicting fire behavior, prediction mobile terminal is presently in the fire behavior of environment, when predicting generation fire behavior, it exports fire behavior to remind, so that user can make counter-measure in time.
Description
Technical field
The present embodiments relate to field of computer technology more particularly to a kind of fire monitoring method and devices.
Background technology
In recent years, universal with mobile terminals such as mobile phone, tablet computers, mobile terminal is in people's lives increasingly
It is important, on the one hand, since mobile terminal is convenient for carrying, user can at one's side, another aspect be whole due to moving for band whenever and wherever possible
Hold feature-rich, user can enjoy diversified network service by mobile terminal.At the same time, with living standard
It improves, user is also higher and higher for the attention rate of local environment safety, how by mobile terminal to determine the mobile terminal
The fire behavior situation of user's local environment, it has also become those skilled in the art's technical problem urgently to be resolved hurrily.
Invention content
The embodiment of the present invention provides a kind of fire monitoring method and device, and to solve, mobile terminal cannot be true in the prior art
The technical issues of determining local environment fire behavior situation.
In order to solve the above technical problems, what the embodiment of the present invention was realized in：
In a first aspect, the embodiment of the present invention additionally provides a kind of fire monitoring method, it is applied to mobile terminal, the method
Including：
When meeting default fire monitoring trigger condition, the infrared data that the mobile terminal is presently in environment is obtained；
Extraction and the relevant infrared signature of fire behavior from the infrared data；
According to the infrared signature and default fire behavior prediction model, predict that the mobile terminal is presently in the fire of environment
Feelings；
When predicting the mobile terminal and being presently in environment and have fire behavior, the safe early warning of preset kind is triggered；
Wherein, the default fire behavior prediction model is related to fire behavior to training sample using specific machine learning algorithm
Infrared signature be trained obtained model, the default fire behavior prediction model is for establishing between infrared signature and fire behavior
Mapping relations.
Second aspect, the embodiment of the present invention additionally provide a kind of fire monitoring device, are applied to mobile terminal, described device
Including：
Acquiring unit, under conditions of meeting default fire monitoring trigger condition, it is current to obtain the mobile terminal
The infrared data of local environment；
Extraction unit, for the extraction from the infrared data and the relevant infrared signature of fire behavior；
Predicting unit, for according to the infrared signature and default fire behavior prediction model, predicting that the mobile terminal is current
The fire behavior of local environment；
Prewarning unit, in the case where predicting the mobile terminal and being presently in environment and have fire behavior, triggering to be default
The safe early warning of type；
Wherein, the default fire behavior prediction model is related to fire behavior to training sample using specific machine learning algorithm
Infrared signature be trained obtained model, the default fire behavior prediction model is for establishing between infrared signature and fire behavior
Mapping relations.
The third aspect, the embodiment of the present invention additionally provide a kind of mobile terminal, including processor, memory and are stored in institute
The fire monitoring program that can be run on memory and on the processor is stated, the fire monitoring program is held by the processor
The step of above-mentioned fire monitoring method is realized when row.
Fourth aspect, the embodiment of the present invention additionally provide a kind of computer readable storage medium, described computer-readable to deposit
Fire monitoring program is stored on storage media, the fire monitoring program realizes above-mentioned fire monitoring method when being executed by processor
Step.
In embodiments of the present invention, specific machine learning algorithm and training sample training can be used for predicting fire behavior
Model, when needing to predict the fire behavior of mobile terminal local environment, which, which can obtain, is presently in the infrared of environment
Data, extraction and the relevant infrared signature of fire behavior from the infrared data, and according to the infrared signature and model, predict mobile whole
End is presently in the fire behavior of environment, and when predicting generation fire behavior, output fire behavior is reminded, so that user can make reply in time
Measure.Due to the relevant infrared signature of fire behavior, can largely reflect the possibility that fire behavior occurs, therefore this hair
Bright embodiment can relatively accurately predict the fire behavior of mobile terminal local environment.In addition, doing fire behavior prison using mobile terminal
It surveys, also improves the utilization ratio of the built-in infrared equipment of mobile terminal, while there is convenience, real-time, depth, which incorporates, to be used
Each scene in the life of family, can provide comprehensive security protection.
Description of the drawings
Attached drawing described herein is used to provide further understanding of the present invention, and constitutes the part of the present invention, this hair
Bright illustrative embodiments and their description are not constituted improper limitations of the present invention for explaining the present invention.In the accompanying drawings：
Fig. 1 is the flow chart of the fire monitoring method of one embodiment of the present of invention；
Fig. 2 is the flow chart of the fire behavior prediction model training method of one embodiment of the present of invention；
Fig. 3 is the structural schematic diagram of the fire monitoring device of one embodiment of the present of invention；
Fig. 4 is a kind of hardware architecture diagram for the mobile terminal for realizing each embodiment of the present invention.
Specific implementation mode
To make the object, technical solutions and advantages of the present invention clearer, below in conjunction with the specific embodiment of the invention and
Technical solution of the present invention is clearly and completely described in corresponding attached drawing.Obviously, described embodiment is only the present invention one
Section Example, instead of all the embodiments.Based on the embodiments of the present invention, those of ordinary skill in the art are not doing
Go out the every other embodiment obtained under the premise of creative work, shall fall within the protection scope of the present invention.
An embodiment of the present invention provides a kind of fire monitoring method and devices.
A kind of fire monitoring method provided in an embodiment of the present invention is introduced first below.
It should be noted that method provided in an embodiment of the present invention is suitable for mobile terminal, in practical applications, the movement
Terminal may include：Mobile phone, tablet computer, smartwatch, Intelligent bracelet, personal digital assistant etc., the embodiment of the present invention pair
This is not construed as limiting.
Fig. 1 is the flow chart of the fire monitoring method of one embodiment of the present of invention, as shown in Figure 1, this method can wrap
Include following steps：
In a step 101, it when meeting default fire monitoring trigger condition, obtains mobile terminal and is presently in the red of environment
Outer data.
Infrared ray is electromagnetic wave of the wavelength between microwave and visible light, wavelength between 1 millimeter to 760 nanometers, than
The non-visible light of feux rouges length.Object higher than absolute zero (- 273.15 DEG C) can generate infrared ray.
The temperature of the infra-red intensity and object itself externally given off in view of object is related, and temperature is higher, radiation
Energy is bigger, conversely, the energy of radiation is smaller, therefore, the distribution of environment mid-infrared light line substantially reflects the temperature of environment
Distribution, and temperature is closely related with fire behavior.Based on the above situation, in the embodiment of the present invention, by built-in in mobile terminal
Infrared detection module, fingerprint identification module detects the infrared ray in the mobile terminal surrounding enviroment, these infrared rays are sent out by object itself, according to object
Temperature is different, and the intensity of the infrared ray sent out is also different.
In the embodiment of the present invention, default fire monitoring trigger condition may include：Receive the fire monitoring of user's triggering
It instructs, reach preset fire behavior detection time, mobile terminal position belongs to the position of preset kind or enters movement
The AD HOC of terminal.
For example, when resting or be outgoing, the fire monitoring instruction that user can trigger manually, when receiving user
When the fire monitoring instruction of triggering, acquisition for mobile terminal is presently in the infrared data of environment, that is, opens infrared acquisition；Alternatively,
User can set timed task, when the system time of mobile terminal reaches preset fire behavior detection time, the movement
Terminal obtains the infrared data for being presently in environment；Alternatively, when detecting that present position is the position of the preset kinds such as hotel
When setting, acquisition for mobile terminal is presently in the infrared data of environment；Alternatively, when entering the AD HOCs such as child mode, it is mobile
Terminal obtains the infrared data for being presently in environment.
In a step 102, extraction and the relevant infrared signature of fire behavior from infrared data.
In the embodiment of the present invention, it can will be divided into static nature and behavioral characteristics with the relevant infrared signature of fire behavior, it is static
Feature includes infrared light intensity and infrared region distribution etc., and behavioral characteristics include infrared light intensity variation and infrared region variation
Deng.
Based on this situation, may include following at least one with the relevant infrared signature of fire behavior in the embodiment of the present invention：It is red
Outer light intensity, infrared region distribution, the variation of infrared light intensity and infrared region variation.
In step 103, according to infrared signature and default fire behavior prediction model, prediction mobile terminal is presently in environment
Fire behavior.
In the embodiment of the present invention, default fire behavior prediction model is using specific machine learning algorithm to training sample and fire
The relevant infrared signature of feelings is trained obtained model, and the default fire behavior prediction model is for establishing infrared signature and fire behavior
Between mapping relations.
In the embodiment of the present invention, when using fire behavior prediction model prediction fire behavior is preset, the defeated of fire behavior prediction model is preset
Enter the infrared signature that environment is presently in for mobile terminal, the output of default fire behavior prediction model is that mobile terminal is presently in ring
The probability value of fire behavior occurs for border, it is generally the case that mobile terminal is presently in the probability value of environment generation fire behavior closer to 1, says
The possibility that fire occurs for bright mobile terminal local environment is bigger, and the probability value that mobile terminal is presently in environment generation fire behavior is got over
Close to 0, illustrate that the possibility of mobile terminal local environment generation fire is smaller.In the case, above-mentioned steps 103 specifically can be with
Include the following steps：It is presently in the infrared signature of environment and default fire behavior prediction model according to mobile terminal, determines the movement
Terminal is presently in the probability value that fire behavior occurs for environment；When the probability value is more than predetermined threshold value, determine that the mobile terminal is current
Local environment has fire behavior.
In order to make it easy to understand, in conjunction with fire behavior prediction model training method shown in Fig. 2 flow chart to the embodiment of the present invention
In fire behavior prediction process be introduced.Fig. 2 is the flow of the fire behavior prediction model training method of one embodiment of the present of invention
Figure, as shown in Fig. 2, this method may comprise steps of：
In step 201, training sample set is obtained, wherein training sample concentration includes the training for training pattern
Sample, the training sample include and the relevant infrared signature of fire behavior.
In the embodiment of the present invention, training sample includes positive sample and negative sample, and positive sample includes：Under fire condition in environment
The corresponding infrared signature of infrared data, negative sample includes：The corresponding infrared spy of infrared data under non-fire condition in environment
Sign.
May include following at least one with the relevant infrared signature of fire behavior in the embodiment of the present invention：It is infrared light intensity, infrared
Optical range distribution, the variation of infrared light intensity and infrared region variation.
In view of the infrared signature of reference is more, the forecast result of model trained is better, it is preferred that relevant with fire behavior
Infrared signature includes：Infrared light intensity, infrared region distribution, the variation of infrared light intensity and infrared region variation.
In step 202, according to specific machine learning algorithm to the training sample and the relevant infrared signature of fire behavior into
Row training, obtains fire behavior prediction model, wherein the fire behavior prediction model is for establishing between the infrared signature of environment and fire behavior
Mapping relations.
In the embodiment of the present invention, specific machine learning algorithm can be neural network algorithm.
When being trained with the relevant infrared signature of fire behavior to the training sample using neural network algorithm, with training
Sample includes positive sample and negative sample, and positive sample includes：The corresponding infrared signature of infrared data under fire condition in environment is born
Sample includes：For the corresponding infrared signature of infrared data under non-fire condition in environment, calculated using existing neural network
Positive sample is quantified with the relevant infrared signature of fire behavior respectively and (can specifically be quantified as the numerical value between 0~1) by method,
Negative sample and the relevant infrared signature of fire behavior are quantified；It is for positive sample, positive sample is relevant infrared with fire behavior
Input of the numerical value as neural network algorithm after characteristic quantification, 1 is set as by the output valve of neural network algorithm；For bearing sample
This, using negative sample with the numerical value after the relevant infrared signature quantization of fire behavior as the input of neural network algorithm, by nerve net
The output valve of network algorithm is set as 0；By above-mentioned operation, the parameter of neural network is constantly adjusted, best parameter is finally obtained,
To obtain the function being made of aforementioned best parameter, i.e. fire behavior prediction model.
When using fire behavior prediction model (function), mobile terminal is presently in the relevant infrared with fire behavior of environment
Feature is quantified and (each infrared signature is quantized), and the numerical value after each infrared signature is quantified is brought into aforementioned functions
In, the result of calculation of the function is that the mobile terminal is presently in the probability value that fire behavior occurs for environment；If mobile terminal is current
The probability value that fire behavior occurs for local environment reaches predetermined threshold value (such as 0.7), it is determined that the mobile terminal is presently in environment
There is fire behavior, if the probability value that mobile terminal is presently in environment generation fire behavior is not up to predetermined threshold value, it is determined that described mobile whole
End, which is presently in environment, does not have fire behavior.
It should be noted that predetermined threshold value is related to the balance of both recall rate and precision ratio, the predetermined threshold value can by with
Family sets itself is adjusted according to the using effect in the training result and actual environment of model, can also pass through algorithm meter
It obtains, the embodiment of the present invention is not construed as limiting this.
In addition, in the embodiment of the present invention, specific machine learning algorithm can also logistic regression algorithm, model training process
Similar with the model training process based on neural network algorithm, details are not described herein.
In view of machine learning algorithm demonstrates its validity in multiple area of pattern recognition such as image, text, because
This, in the embodiment of the present invention, fire monitoring is carried out using machine learning algorithm, with versatile, accuracy rate is high, easy to use
The characteristics of, there is higher practical value.
At step 104, when predicting mobile terminal and being presently in environment and have fire behavior, the safety for triggering preset kind is pre-
It is alert.
In the embodiment of the present invention, the safe early warning of preset kind may include following at least one：It is jingle bell, vibrations, automatic
Dialing and display particular user interface.For example, particular user interface can be that " 119 ", " 120 " or emergency contact etc. are quick
Dialing interface, to facilitate user quickly to seek help.
As it can be seen that mobile terminal when predicting local environment and having fire behavior, can pass through and trigger a plurality of types of safe early warnings
User is reminded, facilitates user quickly to make counter-measure or seek help, to protect the personal safety of user.
As seen from the above-described embodiment, in the embodiment, specific machine learning algorithm and training sample training can be used to use
In the model of prediction fire behavior, when needing to predict the fire behavior of mobile terminal local environment, which can obtain current institute
The infrared data for locating environment, extraction and the relevant infrared signature of fire behavior from the infrared data, and according to the infrared signature and mould
Type, prediction mobile terminal are presently in the fire behavior of environment, and when predicting generation fire behavior, output fire behavior is reminded, so as to user's energy
It is enough to make counter-measure in time.Due to the relevant infrared signature of fire behavior, can largely reflect fire behavior occur
Possibility, therefore the embodiment of the present invention can relatively accurately predict the fire behavior of mobile terminal local environment.In addition, using moving
Dynamic terminal does fire monitoring, also improves the utilization ratio of the built-in infrared equipment of mobile terminal, at the same have convenience, in real time
Property, depth incorporates each scene in user's life, can provide comprehensive security protection.
Fig. 3 is the structural schematic diagram of the fire monitoring device of one embodiment of the present of invention, the fire monitoring device application
In mobile terminal, as shown in figure 3, fire monitoring device 300 may include：Acquiring unit 301, extraction unit 302, predicting unit
303 and prewarning unit 304, wherein
Acquiring unit 301, under conditions of meeting default fire monitoring trigger condition, obtaining the mobile terminal and working as
The infrared data of preceding local environment；
Extraction unit 302, for the extraction from the infrared data and the relevant infrared signature of fire behavior；
Predicting unit 303, for according to the infrared signature and default fire behavior prediction model, predicting that the mobile terminal is worked as
The fire behavior of preceding local environment；
Prewarning unit 304, in the case where predicting the mobile terminal and being presently in environment and have fire behavior, triggering to be pre-
If the safe early warning of type；
Wherein, the default fire behavior prediction model is related to fire behavior to training sample using specific machine learning algorithm
Infrared signature be trained obtained model, the default fire behavior prediction model is for establishing between infrared signature and fire behavior
Mapping relations.
As seen from the above-described embodiment, in the embodiment, specific machine learning algorithm and training sample training can be used to use
In the model of prediction fire behavior, when needing to predict the fire behavior of mobile terminal local environment, which can obtain current institute
The infrared data for locating environment, extraction and the relevant infrared signature of fire behavior from the infrared data, and according to the infrared signature and mould
Type, prediction mobile terminal are presently in the fire behavior of environment, and when predicting generation fire behavior, output fire behavior is reminded, so as to user's energy
It is enough to make counter-measure in time.Due to the relevant infrared signature of fire behavior, can largely reflect fire behavior occur
Possibility, therefore the embodiment of the present invention can relatively accurately predict the fire behavior of mobile terminal local environment.In addition, using moving
Dynamic terminal does fire monitoring, also improves the utilization ratio of the built-in infrared equipment of mobile terminal, at the same have convenience, in real time
Property, depth incorporates each scene in user's life, can provide comprehensive security protection.
Optionally, as one embodiment, the default fire monitoring trigger condition may include：
It receives the fire monitoring instruction of user's triggering, reach preset fire behavior detection time, mobile terminal place
Position belongs to the position of preset kind or enters the AD HOC of mobile terminal.
Optionally, as one embodiment, the infrared signature may include following at least one：It is infrared light intensity, infrared
Optical range distribution, the variation of infrared light intensity and infrared region variation.
Optionally, as one embodiment, the training sample includes positive sample and negative sample, and the positive sample includes：
The corresponding infrared signature of infrared data under fire condition in environment, the negative sample include：Under non-fire condition in environment
The corresponding infrared signature of infrared data.
Optionally, as one embodiment, the predicting unit 304 may include：
Fire behavior probability of happening determination subelement, for according to the infrared signature and default fire behavior prediction model, determining institute
It states mobile terminal and is presently in the probability value that fire behavior occurs for environment；
Fire behavior determination subelement, in the case where the probability value is more than predetermined threshold value, determining the mobile terminal
Being presently in environment has fire behavior.
Optionally, as one embodiment, the safe early warning of the preset kind includes following at least one：Jingle bell, shake
Dynamic, auto dialing and display particular user interface.
Optionally, as one embodiment, the specific machine learning algorithm can be neural network algorithm.
Fig. 4 is a kind of hardware architecture diagram for the mobile terminal for realizing each embodiment of the present invention, as shown in figure 4, should
Mobile terminal 400 includes but not limited to：Radio frequency unit 401, network module 402, audio output unit 403, input unit 404,
Sensor 405, display unit 406, user input unit 407, interface unit 408, memory 409, processor 410, Yi Ji electricity
The components such as source 411.It will be understood by those skilled in the art that mobile terminal structure shown in Fig. 4 is not constituted to mobile terminal
Restriction, mobile terminal may include either combining certain components or different components than illustrating more or fewer components
Arrangement.In embodiments of the present invention, mobile terminal include but not limited to mobile phone, tablet computer, laptop, palm PC,
Car-mounted terminal, wearable device and pedometer etc..
Wherein, processor 410 are presently in for when meeting default fire monitoring trigger condition, obtaining mobile terminal
The infrared data of environment；Extraction and the relevant infrared signature of fire behavior from the infrared data；According to the infrared signature and in advance
If fire behavior prediction model, predict that the mobile terminal is presently in the fire behavior of environment；When predicting the current institute of the mobile terminal
When place's environment has fire behavior, the safe early warning of preset kind is triggered；Wherein, the default fire behavior prediction model is to use specific machine
Learning algorithm is trained obtained model, the default fire behavior prediction to training sample and the relevant infrared signature of fire behavior
Model is used to establish the mapping relations between infrared signature and fire behavior.
In the embodiment of the present invention, specific machine learning algorithm and training sample can be used to train the mould for predicting fire behavior
Type, when needing to predict the fire behavior of mobile terminal local environment, which can obtain the infrared number for being presently in environment
According to, extraction and the relevant infrared signature of fire behavior from the infrared data, and according to the infrared signature and model, predict mobile terminal
It is presently in the fire behavior of environment, when predicting generation fire behavior, output fire behavior is reminded, and is arranged so that user can make reply in time
It applies.Due to the relevant infrared signature of fire behavior, can largely reflect fire behavior occur possibility, therefore the present invention
Embodiment can relatively accurately predict the fire behavior of mobile terminal local environment.In addition, fire monitoring is done using mobile terminal,
The utilization ratio of the built-in infrared equipment of mobile terminal is also improved, while there is convenience, real-time, depth incorporates user's life
Each scene in work, can provide comprehensive security protection.
Optionally, as one embodiment, the default fire monitoring trigger condition includes：
It receives the fire monitoring instruction of user's triggering, reach preset fire behavior detection time, mobile terminal place
Position belongs to the position of preset kind or enters the AD HOC of mobile terminal.
Optionally, as one embodiment, the infrared signature includes following at least one：Infrared light intensity, infrared light model
Enclose distribution, the variation of infrared light intensity and infrared region variation.
Optionally, as one embodiment, the training sample includes positive sample and negative sample, and the positive sample includes：
The corresponding infrared signature of infrared data under fire condition in environment, the negative sample include：Under non-fire condition in environment
The corresponding infrared signature of infrared data.
Optionally, described according to the infrared signature and default fire behavior prediction model as one embodiment, described in prediction
Mobile terminal is presently in the step of fire behavior of environment, including：
According to the infrared signature and default fire behavior prediction model, determine that the mobile terminal is presently in environment and fire occurs
The probability value of feelings；
When the probability value is more than predetermined threshold value, determine that the mobile terminal is presently in environment and has fire behavior
Optionally, as one embodiment, the safe early warning of the preset kind includes following at least one：Jingle bell, shake
Dynamic, auto dialing and display particular user interface.
Optionally, as one embodiment, the specific machine learning algorithm is neural network algorithm.
It should be understood that the embodiment of the present invention in, radio frequency unit 401 can be used for receiving and sending messages or communication process in, signal
Send and receive, specifically, by from base station downlink data receive after, to processor 410 handle；In addition, by uplink
Data are sent to base station.In general, radio frequency unit 401 includes but not limited to antenna, at least one amplifier, transceiver, coupling
Device, low-noise amplifier, duplexer etc..In addition, radio frequency unit 401 can also by radio communication system and network and other set
Standby communication.
Mobile terminal has provided wireless broadband internet to the user by network module 402 and has accessed, and such as user is helped to receive
Send e-mails, browse webpage and access streaming video etc..
It is that audio output unit 403 can receive radio frequency unit 401 or network module 402 or in memory 409
The audio data of storage is converted into audio signal and exports to be sound.Moreover, audio output unit 403 can also be provided and be moved
The relevant audio output of specific function that dynamic terminal 400 executes is (for example, call signal receives sound, message sink sound etc.
Deng).Audio output unit 403 includes loud speaker, buzzer and receiver etc..
Input unit 404 is for receiving audio or video signal.Input unit 404 may include graphics processor
(Graphics Processing Unit, GPU) 4041 and microphone 4042, graphics processor 4041 is in video acquisition mode
Or the image data of the static images or video obtained by image capture apparatus (such as camera) in image capture mode carries out
Reason.Treated, and picture frame may be displayed on display unit 406.Through graphics processor 4041, treated that picture frame can be deposited
Storage is sent in memory 409 (or other storage mediums) or via radio frequency unit 401 or network module 402.Mike
Wind 4042 can receive sound, and can be audio data by such acoustic processing.Treated audio data can be
The format output of mobile communication base station can be sent to via radio frequency unit 401 by being converted in the case of telephone calling model.
Mobile terminal 400 further includes at least one sensor 405, such as optical sensor, motion sensor and other biographies
Sensor.Specifically, optical sensor includes ambient light sensor and proximity sensor, wherein ambient light sensor can be according to environment
The light and shade of light adjusts the brightness of display panel 4061, and proximity sensor can close when mobile terminal 400 is moved in one's ear
Display panel 4061 and/or backlight.As a kind of motion sensor, accelerometer sensor can detect in all directions (general
For three axis) size of acceleration, size and the direction of gravity are can detect that when static, can be used to identify mobile terminal posture (ratio
Such as horizontal/vertical screen switching, dependent game, magnetometer pose calibrating), Vibration identification correlation function (such as pedometer, tap)；It passes
Sensor 405 can also include fingerprint sensor, pressure sensor, iris sensor, molecule sensor, gyroscope, barometer, wet
Meter, thermometer, infrared sensor etc. are spent, details are not described herein.
Display unit 406 is for showing information input by user or being supplied to the information of user.Display unit 406 can wrap
Display panel 4061 is included, liquid crystal display (Liquid Crystal Display, LCD), Organic Light Emitting Diode may be used
Forms such as (Organic Light-Emitting Diode, OLED) configure display panel 4061.
User input unit 407 can be used for receiving the number or character information of input, and generate the use with mobile terminal
Family is arranged and the related key signals input of function control.Specifically, user input unit 407 include touch panel 4071 and
Other input equipments 4072.Touch panel 4071, also referred to as touch screen collect user on it or neighbouring touch operation
(for example user uses any suitable objects or attachment such as finger, stylus on touch panel 4071 or in touch panel 4071
Neighbouring operation).Touch panel 4071 may include both touch detecting apparatus and touch controller.Wherein, touch detection
Device detects the touch orientation of user, and detects the signal that touch operation is brought, and transmits a signal to touch controller；Touch control
Device processed receives touch information from touch detecting apparatus, and is converted into contact coordinate, then gives processor 410, receiving area
It manages the order that device 410 is sent and is executed.Furthermore, it is possible to more using resistance-type, condenser type, infrared ray and surface acoustic wave etc.
Type realizes touch panel 4071.In addition to touch panel 4071, user input unit 407 can also include other input equipments
4072.Specifically, other input equipments 4072 can include but is not limited to physical keyboard, function key (such as volume control button,
Switch key etc.), trace ball, mouse, operating lever, details are not described herein.
Further, touch panel 4071 can be covered on display panel 4061, when touch panel 4071 is detected at it
On or near touch operation after, send processor 410 to determine the type of touch event, be followed by subsequent processing device 410 according to touch
The type for touching event provides corresponding visual output on display panel 4061.Although in Fig. 4, touch panel 4071 and display
Panel 4061 is to realize the function that outputs and inputs of mobile terminal as two independent components, but in some embodiments
In, can be integrated by touch panel 4071 and display panel 4061 and realize the function that outputs and inputs of mobile terminal, it is specific this
Place does not limit.
Interface unit 408 is the interface that external device (ED) is connect with mobile terminal 400.For example, external device (ED) may include having
Line or wireless head-band earphone port, external power supply (or battery charger) port, wired or wireless data port, storage card end
Mouth, port, the port audio input/output (I/O), video i/o port, earphone end for connecting the device with identification module
Mouthful etc..Interface unit 408 can be used for receiving the input (for example, data information, electric power etc.) from external device (ED) and
By one or more elements that the input received is transferred in mobile terminal 400 or can be used in 400 He of mobile terminal
Transmission data between external device (ED).
Memory 409 can be used for storing software program and various data.Memory 409 can include mainly storing program area
And storage data field, wherein storing program area can storage program area, application program (such as the sound needed at least one function
Sound playing function, image player function etc.) etc.；Storage data field can store according to mobile phone use created data (such as
Audio data, phone directory etc.) etc..In addition, memory 409 may include high-speed random access memory, can also include non-easy
The property lost memory, a for example, at least disk memory, flush memory device or other volatile solid-state parts.
Processor 410 is the control centre of mobile terminal, utilizes each of various interfaces and the entire mobile terminal of connection
A part by running or execute the software program and/or module that are stored in memory 409, and calls and is stored in storage
Data in device 409 execute the various functions and processing data of mobile terminal, to carry out integral monitoring to mobile terminal.Place
Reason device 410 may include one or more processing units；Preferably, processor 410 can integrate application processor and modulatedemodulate is mediated
Manage device, wherein the main processing operation system of application processor, user interface and application program etc., modem processor is main
Processing wireless communication.It is understood that above-mentioned modem processor can not also be integrated into processor 410.
Mobile terminal 400 can also include the power supply 411 (such as battery) powered to all parts, it is preferred that power supply 411
Can be logically contiguous by power-supply management system and processor 410, to realize management charging by power-supply management system, put
The functions such as electricity and power managed.
In addition, mobile terminal 400 includes some unshowned function modules, details are not described herein.
Preferably, the embodiment of the present invention also provides a kind of mobile terminal, including processor 410, and memory 409 is stored in
On memory 409 and the fire monitoring program that can be run on the processor 410, the fire monitoring program is by processor 410
Each process of above-mentioned fire monitoring embodiment of the method is realized when execution, and can reach identical technique effect, to avoid repeating,
Which is not described herein again.
The embodiment of the present invention also provides a kind of computer readable storage medium, and fire is stored on computer readable storage medium
Feelings monitoring program realizes that above application is real in the fire monitoring method of mobile terminal when the fire monitoring program is executed by processor
Each process of example is applied, and identical technique effect can be reached, to avoid repeating, which is not described herein again.Wherein, the calculating
Machine readable storage medium storing program for executing, such as read-only memory (Read-Only Memory, abbreviation ROM), random access memory (Random
Access Memory, abbreviation RAM), magnetic disc or CD etc..
It should be noted that herein, the terms "include", "comprise" or its any other variant are intended to non-row
His property includes, so that process, method, article or device including a series of elements include not only those elements, and
And further include other elements that are not explicitly listed, or further include for this process, method, article or device institute it is intrinsic
Element.In the absence of more restrictions, the element limited by sentence "including a ...", it is not excluded that including this
There is also other identical elements in the process of element, method, article or device.
Through the above description of the embodiments, those skilled in the art can be understood that above-described embodiment side
Method can add the mode of required general hardware platform to realize by software, naturally it is also possible to by hardware, but in many cases
The former is more preferably embodiment.Based on this understanding, technical scheme of the present invention substantially in other words does the prior art
Going out the part of contribution can be expressed in the form of software products, which is stored in a storage medium
In (such as ROM/RAM, magnetic disc, CD), including some instructions are used so that a station terminal (can be mobile phone, computer, service
Device, air conditioner or network equipment etc.) execute method described in each embodiment of the present invention.
The embodiment of the present invention is described with above attached drawing, but the invention is not limited in above-mentioned specific
Embodiment, the above mentioned embodiment is only schematical, rather than restrictive, those skilled in the art
Under the inspiration of the present invention, without breaking away from the scope protected by the purposes and claims of the present invention, it can also make very much
Form belongs within the protection of the present invention.
Claims (12)
1. a kind of fire monitoring method is applied to mobile terminal, which is characterized in that the method includes：
When meeting default fire monitoring trigger condition, the infrared data that the mobile terminal is presently in environment is obtained；
Extraction and the relevant infrared signature of fire behavior from the infrared data；
According to the infrared signature and default fire behavior prediction model, predict that the mobile terminal is presently in the fire behavior of environment；
When predicting the mobile terminal and being presently in environment and have fire behavior, the safe early warning of preset kind is triggered；
Wherein, the default fire behavior prediction model is relevant red with fire behavior to training sample using specific machine learning algorithm
Outer feature is trained obtained model, and the default fire behavior prediction model is for establishing reflecting between infrared signature and fire behavior
Penetrate relationship.
2. according to the method described in claim 1, it is characterized in that, the default fire monitoring trigger condition includes：
It receives the fire monitoring instruction of user's triggering, reach preset fire behavior detection time, mobile terminal position
Belong to the position of preset kind or enters the AD HOC of mobile terminal.
3. according to the method described in claim 1, it is characterized in that, the infrared signature includes following at least one：Infrared light
By force, infrared region distribution, the variation of infrared light intensity and infrared region variation.
4. described according to the method described in claim 1, it is characterized in that, the training sample includes positive sample and negative sample
Positive sample includes：The corresponding infrared signature of infrared data under fire condition in environment, the negative sample include：Non- fire condition
The corresponding infrared signature of infrared data in lower environment.
5. according to the method described in claim 4, it is characterized in that, described predict mould according to the infrared signature and default fire behavior
Type predicts the step of mobile terminal is presently in the fire behavior of environment, including：
According to the infrared signature and default fire behavior prediction model, determine that the mobile terminal is presently in environment and fire behavior occurs
Probability value；
When the probability value is more than predetermined threshold value, determine that the mobile terminal is presently in environment and has fire behavior.
6. method according to any one of claims 1 to 5, which is characterized in that the safe early warning of the preset kind includes
Following at least one：Jingle bell, vibrations, auto dialing and display particular user interface.
7. a kind of fire monitoring device, it is applied to mobile terminal, which is characterized in that described device includes：
Acquiring unit, under conditions of meeting default fire monitoring trigger condition, obtaining the mobile terminal and being presently in
The infrared data of environment；
Extraction unit, for the extraction from the infrared data and the relevant infrared signature of fire behavior；
Predicting unit, for according to the infrared signature and default fire behavior prediction model, predicting that the mobile terminal is presently in
The fire behavior of environment；
Prewarning unit, in the case where predicting the mobile terminal and being presently in environment and have fire behavior, triggering preset kind
Safe early warning；
Wherein, the default fire behavior prediction model is relevant red with fire behavior to training sample using specific machine learning algorithm
Outer feature is trained obtained model, and the default fire behavior prediction model is for establishing reflecting between infrared signature and fire behavior
Penetrate relationship.
8. device according to claim 7, which is characterized in that the default fire monitoring trigger condition includes：
It receives the fire monitoring instruction of user's triggering, reach preset fire behavior detection time, mobile terminal position
Belong to the position of preset kind or enters the AD HOC of mobile terminal.
9. device according to claim 7, which is characterized in that the infrared signature includes following at least one：Infrared light
By force, infrared region distribution, the variation of infrared light intensity and infrared region variation.
10. device according to claim 7, which is characterized in that the training sample includes positive sample and negative sample, described
Positive sample includes：The corresponding infrared signature of infrared data under fire condition in environment, the negative sample include：Non- fire condition
The corresponding infrared signature of infrared data in lower environment.
11. device according to claim 10, which is characterized in that the predicting unit includes：
Fire behavior probability of happening determination subelement, for according to the infrared signature and default fire behavior prediction model, determining the shifting
Dynamic terminal is presently in the probability value that fire behavior occurs for environment；
Fire behavior determination subelement, in the case where the probability value is more than predetermined threshold value, determining that the mobile terminal is current
Local environment has fire behavior.
12. according to claim 7 to 11 any one of them device, which is characterized in that the safe early warning packet of the preset kind
Include following at least one：Jingle bell, vibrations, auto dialing and display particular user interface.
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|---|---|---|---|
| CN201810205411.2A CN108550236A (en) | 2018-03-13 | 2018-03-13 | fire monitoring method and device |
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| Application Number | Priority Date | Filing Date | Title |
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| CN201810205411.2A CN108550236A (en) | 2018-03-13 | 2018-03-13 | fire monitoring method and device |
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| CN1374231A (en) * | 2001-03-13 | 2002-10-16 | 株式会社新来岛船坞 | Ship fire detection system and local fire-fighting system for ship engine room |
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Application publication date: 20180918 |