CN108346252A - A kind of integrated forest fire protection information system excavated based on big data - Google Patents
A kind of integrated forest fire protection information system excavated based on big data Download PDFInfo
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- CN108346252A CN108346252A CN201810270439.4A CN201810270439A CN108346252A CN 108346252 A CN108346252 A CN 108346252A CN 201810270439 A CN201810270439 A CN 201810270439A CN 108346252 A CN108346252 A CN 108346252A
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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
- G08B17/005—Fire alarms; Alarms responsive to explosion for forest fires, e.g. detecting fires spread over a large or outdoors area
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/10—Terrestrial scenes
- G06V20/13—Satellite images
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
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- G06V20/40—Scenes; Scene-specific elements in video content
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Abstract
The present invention provides a kind of integrated forest fire protection information systems excavated based on big data, including big data processing center and the various dimensions that connects respectively with big data processing center to perceive subsystem, early warning subsystem；For acquiring Various types of data, big data processing center is pre-processed and is calculated to data the various dimensions perception subsystem, and the early warning and alert system realizes fire alarm prediction.
Description
Technical field
The present invention relates to forest fire protection technical fields, and in particular to a kind of integrated forest fire protection excavated based on big data
Information system.
Background technology
Forest is the maximum ecosystem in land, and the variation of the forest reserves is for global ecological environment, life all the time
Object diversity, climate change and carbon cycle etc. important, it is irreplaceable for maintaining Global Ecological balance to have
Effect, be extremely important renewable resource.As area of woods and forest stock increase year by year, weather item is added
The variability of part so that the generation of forest fire is more and more frequent.Since the generation of forest fire has sudden, randomness,
And huge economic loss can be caused in a short time, cause forest fire protection task to become more and more arduous.General forest fire
Point to its effective monitoring and is in time puted out a fire to save life and property to preventing forest fire developmenting spread very often far from resident settlement
It is crucial.The existing relatively advanced forest fire prevention and control system in China is that the occurrence and development of forest fire are monitored by monitoring remote video,
The communication system being equipped with by phone or system for forestry carries out traffic guidance, and forest fire prevention and control strength is carried to equip to go to and be puted out a fire to save life and property.
In practice, forest fire is influenced by forest land environment, meteorological condition etc., and the monitoring device in existing forest fire prevention and control system can not have
It gives warning in advance to effect and finds forest fire in time, and due to lacking accurate computation model, often there is wrong report to happen.
In addition, because forest zone is with a varied topography often there is communication dead angle in fire attack, cause to command not smooth, while existing commander
Front information and rear decision effectively can not be exchanged and be shown in real time in time by technology and system.
Invention content
In view of the above-mentioned problems, the present invention provides a kind of integrated forest fire protection information system excavated based on big data.
The purpose of the present invention is realized using following technical scheme：
It provides in a kind of integrated forest fire protection information system excavated based on big data, including big data processing
The heart and various dimensions perception subsystem, the early warning subsystem being connect respectively with big data processing center；Various dimensions perception
For acquiring Various types of data, big data processing center is pre-processed and is calculated to data system, and the early warning and alert system is real
Existing fire alarm prediction.
The various dimensions perception subsystem is for acquiring satellite remote sensing date, and the image by being carried on unmanned plane and machine
Video camera, positioning device and monitoring device provide the video, image, numbered of monitored forest for big data processing center
According to；
The big data processing center includes data preprocessing module, data analysis module, distributed memory, the number
Data preprocess module carries out error detection, removal after being used to obtain all types of data that various dimensions perception subsystem provides to data
Mistake distracter and useless abnormal data, output data sample；The data analysis module handles vedio data, utilizes fire
The characteristics of image of flame and smog identifies the presence of flame and smog, when having flame and/or smog in image, that is, thinks to occur
Fire behavior sends danger warning information to early warning and alert system.
Preferably, it when by image recognition fire behavior occurs for data analysis module, transfers in the shooting area of corresponding time ground
Satellite remote sensing date, obtain suspicious object be accurately positioned, positioning result is synchronized and is sent to early warning and alert system.
Preferably, the corresponding time shooting area is according to the shooting direction of photographic device, position, time and video camera
Shooting distance calculates.
Preferably, big data processing center further includes Data Post module, and Data Post module is used for pre- to data
The data sample of processing module output carries out steady-state analysis, marks off steady state data sample and unstable state data sample, after label
Distributed memory is sent to be stored respectively.
Preferably, further include multi-layer application subsystem for realizing each forest management system scheduling of resource and commander,
The multi-layer application subsystem includes that forest fire protection management module, forest law enforcement management module, forest fires are puted out a fire to save life and property commander's module, gloomy
Woods protection module.
Beneficial effects of the present invention are：Based on big data technology, multi-faceted comprehensive monitoring can be carried out to forest, to going through
History data and the mass data monitored in real time carry out mining analysis, the accurately generation of prediction, early warning forest fire.
Description of the drawings
Using attached drawing, the invention will be further described, but the embodiment in attached drawing does not constitute any limit to the present invention
System, for those of ordinary skill in the art, without creative efforts, can also obtain according to the following drawings
Other attached drawings.
Fig. 1 is the structural schematic block diagram of the integrated forest fire protection information system of an illustrative embodiment of the invention；
Fig. 2 is the structural schematic block diagram of the big data processing center of an illustrative embodiment of the invention.
Reference numeral：
Various dimensions perceive subsystem 1, big data processing center 2, early warning subsystem 3, data preprocessing module 10, data point
Analyse module 20, distributed memory 30, Data Post module 40.
Specific implementation mode
The invention will be further described with the following Examples.
Referring to Fig. 1, a kind of integrated forest fire protection information system excavated based on big data provided in this embodiment, packet
Include big data processing center 2 and the various dimensions being connect respectively with big data processing center 2 perception subsystem 1, early warning subsystem
3；For acquiring Various types of data, big data processing center 2 is pre-processed and is counted to data the various dimensions perception subsystem 1
It calculates, the early warning and alert system realizes fire alarm prediction.
The various dimensions perception subsystem 1 is for acquiring satellite remote sensing date, and the figure by being carried on unmanned plane and machine
As video camera, positioning device and monitoring device, the video, image, numerical value of monitored forest are provided for big data processing center 2
Data；
The big data processing center 2 includes data preprocessing module 10, data analysis module 20, distributed memory
30, the data preprocessing module 10 carries out data after being used to obtain all types of data that various dimensions perception subsystem 1 provides
Error detection removes wrong distracter and useless abnormal data, output data sample；The data analysis module 20 handles video
Image data, using the characteristics of image of flame and smog identify flame and smog presence, when in image have flame and/or cigarette
When mist, that is, think that fire behavior occurs, danger warning information is sent to early warning and alert system.
In an optional mode, when by image recognition fire behavior occurs for data analysis module 20, the corresponding time is transferred
Satellite remote sensing date in the shooting area of ground, obtain suspicious object be accurately positioned, positioning result is synchronized be sent to it is pre-
Alert forecasting system.
Wherein, the corresponding time shooting area is clapped according to the shooting direction of photographic device, position, time and video camera
Photographic range calculates.
In an optional mode, system further includes for realizing each forest management system scheduling of resource and commanding more
Level application subsystem, the multi-layer application subsystem include forest fire protection management module, forest law enforcement management module, forest fires
It puts out a fire to save life and property and commands module, forest conservation module.
The above embodiment of the present invention is based on big data technology, multi-faceted comprehensive monitoring can be carried out to forest, to history
Data and the mass data monitored in real time carry out mining analysis, the accurately generation of prediction, early warning forest fire.
In one embodiment, it is specific to execute when 10 logarithm Value Data of data preprocessing module carries out error detection：
(1) set the data sample that monitoring device i is acquired in certain period of time asniFor data sample
Data amount check in this calculates SiThe mathematic expectaion of middle dataAnd varianceTraverse SiIn data, if SiIn there are data
sαBeyond fiducial rangeThen by data sαIt is considered as suspicious data；
(2) if the data sample S that monitoring device i is sentiThere is no suspicious datas, carry out the mistake inspection of next data sample
It surveys；If the data sample S that monitoring device i is sentiThere are suspicious datas, then by data sample SiIn data according to from small to large
Be ranked sequentially, obtain the median in new sequenceFalse judgment is carried out to suspicious data；
Wherein, if suspicious data sβWhen meeting following condition, then by suspicious data sβIt is considered as wrong data：
In formula, sδFor section [ei,ni] in the δ data, sεFor section [1, ei] in the ε data.
Monitoring device often collects the data of mistake by extraneous interference or when occurring measuring failure.This reality
The differentiation mechanism that example innovatively proposes wrong data is applied, which determines suspicious data according to Pauta criterion first,
And false judgment only is carried out to suspicious data, relative to the mode that all data are carried out with false judgment, improve error detection
Efficiency.
The present embodiment sets the condition for misjudgment data, has certain robustness.Wrong data is carried out
It rejects, can effectively exclude the random disturbances during monitoring device measures, and improve the accuracy of data to a certain extent.
In one embodiment, the data preprocessing module 10 is additionally operable to calculate substitute corresponding with wrong data
Value, calculated substitution value is added into position corresponding with the wrong data；
Wrong data is wherein set as Sk, substitution value Sk' calculation formula be：
In formula, se(k) it is SkData in the data sample at place according to from small to large be ranked sequentially rear corresponding middle position
Number, Ze(k)SkThe mathematic expectaion of data in the data sample at place.
When handling in the prior art wrong data, wrong data is directly typically subjected to rejecting processing, it is this
Mode can cause the missing of data, to influence the time response of data, further influence subsequently to carry out processing analysis to data
Precision.
When the present embodiment handles wrong data, substitution value is calculated according to the formula of setting, substitution value is replaced
Wrong data in data group, the data advantageously allowed in data group tend to be steady, and avoid causing shortage of data and influencing number
According to time response.The present embodiment is based on desired value and median calculates substitution value, is conducive to ensure that substitution value can meet number
According to the time response of sample, the accuracy of data is improved.
In an optional mode, big data processing center 2 further includes Data Post module 40, Data Post mould
Block 40 is used to carry out steady-state analysis to the data sample that data preprocessing module exports, and marks off steady state data sample and unstable state
Data sample is sent to distributed memory 30 after label and is stored respectively.
In one embodiment, Data Post module 40 carries out steady-state analysis to data sample, marks off steady state data
Sample and unstable state data sample, specifically include：
(1) by the data sample of monitoring device node λResolve into one group of w n dimensional vector n：
In formula, w is the insertion dimension of setting；
(2) R is setw(μ) and RwThe distance between (c) threshold valueWith dimension w, statistics meets the number N of the μ of following conditionμ：
(3) by NμIt is denoted as with the ratio of v-2It calculates according to the following formulaMean value Pw(y)：
(4) dimension is increased into w+1, repeats (1) and arrive (3), obtains Pw+1(y), if data sampleMeet
Following condition then willIt is classified as steady state data sample, is otherwise classified as unstable state data sample：
In formula, Φ is the stable state threshold degrees of setting.
Angle of the present embodiment based on Sample Entropy provides a kind of efficient data sample steady-state analysis mechanism, utilizes this
Mechanism carries out steady-state analysis to the data sample that data preprocessing module 10 exports, and marks off steady state data sample and unstable state number
According to sample, the differentiation to data stability is realized.The present embodiment is further to steady state data sample and unstable state data sample
Retransmited after being marked to distributed memory 30 and stored respectively, be conducive to for subsequent data analysis provide it is good,
Stable data source.
Finally it should be noted that the above embodiments are merely illustrative of the technical solutions of the present invention, rather than the present invention is protected
The limitation of range is protected, although being explained in detail to the present invention with reference to preferred embodiment, those skilled in the art answer
Work as understanding, technical scheme of the present invention can be modified or replaced equivalently, without departing from the reality of technical solution of the present invention
Matter and range.
Claims (6)
1. a kind of integrated forest fire protection information system excavated based on big data, characterized in that including in big data processing
The heart and various dimensions perception subsystem, the early warning subsystem being connect respectively with big data processing center；Various dimensions perception
For acquiring Various types of data, big data processing center is pre-processed and is calculated to data system, and the early warning and alert system is real
Existing fire alarm prediction.
The various dimensions perception subsystem is for acquiring satellite remote sensing date, and the image pickup by being carried on unmanned plane and machine
Machine, positioning device and monitoring device provide the video, image, numeric data of monitored forest for big data processing center；
The big data processing center includes data preprocessing module, data analysis module, distributed memory, and the data are pre-
Processing module carries out error detection after being used to obtain all types of data that various dimensions perception subsystem provides to data, removes mistake
Distracter and useless abnormal data, output data sample；The data analysis module handles vedio data, using flame and
The presence of characteristics of image the identification flame and smog of smog when having flame and/or smog in image thinks that fire occurs
Feelings send danger warning information to early warning and alert system.
2. a kind of integrated forest fire protection information system excavated based on big data according to claim 1, feature
It is when by image recognition fire behavior occurs for data analysis module, to transfer the satellite remote sensing number in the shooting area of corresponding time ground
According to acquisition suspicious object is accurately positioned, and positioning result is synchronized and is sent to early warning and alert system.
3. a kind of integrated forest fire protection information system excavated based on big data according to claim 2, feature
It is that the corresponding time shooting area is according to the shooting direction of photographic device, position, time and video camera shooting distance meter
It calculates.
4. according to a kind of integrated forest fire protection informationization system excavated based on big data of claim 1-3 any one of them
System, characterized in that big data processing center further includes Data Post module, and Data Post module is used for data prediction
The data sample of module output carries out steady-state analysis, marks off steady state data sample and unstable state data sample, is sent after label
It is stored respectively to distributed memory.
5. a kind of integrated forest fire protection information system excavated based on big data according to claim 4, feature
It is that Data Post module carries out steady-state analysis to data sample, marks off steady state data sample and unstable state data sample, has
Body includes：
(1) by the data sample of monitoring device node λResolve into one group of w n dimensional vector n：
μ, c=1,2 ..., v；V=nλ-w+1
In formula, w is the insertion dimension of setting；
(2) R is setw(μ) and RwThe distance between (c) threshold valueWith dimension w, statistics meets the number N of the μ of following conditionμ：
(3) by NμIt is denoted as with the ratio of v-2It calculates according to the following formulaMean value Pw(y)：
(4) dimension is increased into w+1, repeats (1) and arrive (3), obtains Pw+1(y), if data sampleMeet following
Condition then willIt is classified as steady state data sample, is otherwise classified as unstable state data sample：
In formula, Φ is the stable state threshold degrees of setting.
6. a kind of integrated forest fire protection information system excavated based on big data according to claim 1, feature
It further includes multi-layer application subsystem for realizing each forest management system scheduling of resource and commander to be, the multi-layer is answered
Include that forest fire protection management module, forest law enforcement management module, forest fires are puted out a fire to save life and property commander's module, forest conservation module with subsystem.
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| CN114935369A (en) * | 2022-06-14 | 2022-08-23 | 湖北筑森生态科技有限公司 | Intelligent recognition forest ecological monitoring system and method |
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