CN107784771A - A kind of forest fire monitoring method based on neural network model - Google Patents
A kind of forest fire monitoring method based on neural network model Download PDFInfo
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- CN107784771A CN107784771A CN201711320988.XA CN201711320988A CN107784771A CN 107784771 A CN107784771 A CN 107784771A CN 201711320988 A CN201711320988 A CN 201711320988A CN 107784771 A CN107784771 A CN 107784771A
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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
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B29/00—Checking or monitoring of signalling or alarm systems; Prevention or correction of operating errors, e.g. preventing unauthorised operation
- G08B29/18—Prevention or correction of operating errors
- G08B29/185—Signal analysis techniques for reducing or preventing false alarms or for enhancing the reliability of the system
- G08B29/186—Fuzzy logic; neural networks
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Abstract
The invention discloses a kind of forest fire monitoring method based on neural network model, utilize the forest fire monitoring technology of seamless Integrated Intelligent Network network neural model, with reference to the professional knowledge and forestry fireproof experience of Management offorestry, establish forestry fire prevention intellectual monitoring early warning and emergency commading system, so as to realize the automatic monitoring of forest zone video, pyrotechnics accurately identifies, fire point is accurately positioned, condition of a fire spreading trend is deduced, put out a fire to save life and property the aid decision of commander, many-sided function such as hazards entropy, establish the complete business chain of forest fire protection, and pointedly solve the various individual demands of user.By being monitored in real time to the temperature information at forest scene, intensity information, humidity information, wind direction information etc., Monitoring Data is inputted to neural network model and carries out Parameter analysis, whether the parameter for judging to detect is in safe range, so as to be monitored in real time to danger of the forest with the presence or absence of unknown fire.
Description
Technical field
The present invention relates to nerual network technique field, more particularly to a kind of forest fire monitoring based on neural network model
Method.
Background technology
Forest fire is the most dangerous enemy of forest, and the disaster that forestry is most fearful, it can come to forest region it is most harmful,
With destructive consequence.Forest fire is more than burning sheet of forest, the animal injured in woods, but also reduces forest
Updating ability, cause the barren of soil and destroy the effect of forest water conservation, even cause ecological environment disequilibrium.Although
The science of the world today advances with rapid changepl. never-ending changes and improvements, and still, the mankind but still not yet obtain length in uniform forest fire
The progress of foot；Then forest fire prevention and discovery ratio put out more realistic meaning.
The site environment information of forest is not monitored in real time on forest fire monitoring method in the prior art, because
This causes the data of the site environment information gathering to forest not accurate enough, it is impossible to the generation of effective control and fire preventing.
The content of the invention
The problem of being existed according to prior art, the invention discloses a kind of forest fire monitoring based on neural network model
Method, comprise the following steps：
S1：The live environmental information of actual forest is gathered in real time by the information record collected and output：Wherein forest
Site environment information includes humidity information, temperature information, illumination intensity information, smokescope information and wind direction information；
S2：Neural network model is established, designs multigroup experiment parameter, experiment parameter includes humidity information, temperature information, light
According to strength information, smokescope information and wind direction information, multigroup experiment parameter is inputted to neural network model to neutral net
Model carries out Experiment Training, and neural network model described in training process carries out carrying for characteristic to the experiment parameter of input
Take, the identification of characteristic, the judgement of threshold value and the output of judged result, the neural network model are carried out to experiment parameter
Autonomous learning is carried out in processing procedure；
S3：The learning ability of neural network model is judged, if the learning ability of the neural network model reaches setting
It is required that then the model carries out the monitoring of forest fire；
S4：The context information monitored using mobile terminal extract real-time neutral net to forest fire, by the information
Preserved.
Further, the humidity information at forest scene is gathered using humidity sensor, forest is gathered using light intensity sensor
The illumination intensity information at scene, the smokescope information at forest scene is gathered using Smoke Sensor, is adopted using wind transducer
Collect the wind direction information at forest scene.
Further, during the neural network model progress threshold decision in the following way：
Humidity threshold is set in neural network model, and the humidity information that forest scene is received when neural network model is entered
Row judges, if the humidity information received is more than the humidity threshold of setting, the neural network model alert, adopts
The neural network model is completed to temperature information, illumination intensity information, smokescope information and wind direction information in fashion described above
Judgement, export forest environment in whether the judged result of fire-prone situation.
Further, the neural network model is using communication and mobile terminal real-time data communication.
A kind of by adopting the above-described technical solution, forest fire monitoring based on neural network model provided by the invention
Method, will by being monitored in real time to the temperature information at forest scene, intensity information, humidity information, wind direction information etc.
Monitoring Data input to neural network model carry out Parameter analysis, the parameter for judging to detect whether in safe range, so as to
Danger of the forest with the presence or absence of unknown fire is monitored in real time.
Brief description of the drawings
, below will be to embodiment or existing in order to illustrate more clearly of the embodiment of the present application or technical scheme of the prior art
There is the required accompanying drawing used in technology description to be briefly described, it should be apparent that, drawings in the following description are only this
Some embodiments described in application, for those of ordinary skill in the art, on the premise of not paying creative work,
Other accompanying drawings can also be obtained according to these accompanying drawings.
Fig. 1 is the flow chart of the forest fire monitoring method of the invention based on neural network model.
Embodiment
To make technical scheme and advantage clearer, with reference to the accompanying drawing in the embodiment of the present invention, to this
Technical scheme in inventive embodiments is clearly completely described：
A kind of forest fire monitoring method based on neural network model as shown in Figure 1, specifically includes following steps：
S1：The live environmental information of actual forest is gathered in real time by the information record collected and output：Wherein forest
Site environment information includes humidity information, temperature information, illumination intensity information, smokescope information and wind direction information.Will detection
Equipment is arranged on the real-time monitoring that forest condition information is carried out in forest, and the information of detection is recorded and preserved in real time.
S2：Neural network model is established, designs multigroup experiment parameter, experiment parameter includes humidity information, temperature information, light
According to strength information, smokescope information and wind direction information, multigroup experiment parameter is inputted to neural network model to neutral net
Model carries out Experiment Training, and neural network model described in training process carries out carrying for characteristic to the experiment parameter of input
Take, the identification of characteristic, the judgement of threshold value and the output of judged result, the neural network model are carried out to experiment parameter
Autonomous learning is carried out in processing procedure.Multigroup parameter designed first inputting to neural network model, the model is trained,
Neural network model is constantly improved in the training process, the speed of parameter identification is constantly strengthened.
S3：The learning ability of neural network model is judged, if the learning ability of the neural network model reaches setting
It is required that then the model carries out the monitoring of forest fire.When judging the learning ability of neutral net in the following way, if neural
Identification and processing speed of the network to parameter reach predetermined value, and then the neural network model reaches requirement.
S4：The context information monitored using mobile terminal extract real-time neutral net to forest fire, by the information
Preserved.
Further, the humidity information at forest scene is gathered using humidity sensor, forest is gathered using light intensity sensor
The illumination intensity information at scene, the smokescope information at forest scene is gathered using Smoke Sensor, is adopted using wind transducer
Collect the wind direction information at forest scene.
Further, during the neural network model progress threshold decision in the following way：
Humidity threshold is set in neural network model, and the humidity information that forest scene is received when neural network model is entered
Row judges, if the humidity information received is more than the humidity threshold of setting, the neural network model alert, adopts
The neural network model is completed to temperature information, illumination intensity information, smokescope information and wind direction information in fashion described above
Judgement.
Further, the neural network model is using communication and mobile terminal real-time data communication.
A kind of forest fire monitoring method based on neural network model disclosed by the invention, utilizes seamless Integrated Intelligent Network
The forest fire monitoring technology of network neural model, with reference to the professional knowledge and forestry fireproof experience of Management offorestry, establish forestry
Prevent fires intellectual monitoring early warning and emergency commading system, so as to realize that automatic monitoring to forest zone environment, pyrotechnics accurately identify
Function, the complete business chain of forest fire protection can also be established, and pointedly solve the various individual demands of user.
The foregoing is only a preferred embodiment of the present invention, but protection scope of the present invention be not limited thereto,
Any one skilled in the art the invention discloses technical scope in, technique according to the invention scheme and its
Inventive concept is subject to equivalent substitution or change, should all be included within the scope of the present invention.
Claims (4)
- A kind of 1. forest fire monitoring method based on neural network model, it is characterised in that：Comprise the following steps：S1：The live environmental information of actual forest is gathered in real time by the information record collected and output：The wherein scene of forest Environmental information includes humidity information, temperature information, illumination intensity information, smokescope information and wind direction information；S2：Neural network model is established, designs multigroup experiment parameter, experiment parameter is strong including humidity information, temperature information, illumination Information, smokescope information and wind direction information are spent, multigroup experiment parameter is inputted to neural network model to neural network model Experiment Training is carried out, neural network model described in training process carries out extracting, being special for characteristic to the experiment parameter of input Identification, the judgement of threshold value and the output of judged result of data are levied, the neural network model is handled to experiment parameter During carry out autonomous learning；S3：Judge the learning ability of neural network model, if the learning ability of the neural network model reaches the requirement of setting, Then the model carries out the monitoring of forest fire；S4：The context information monitored using mobile terminal extract real-time neutral net to forest fire, the information is carried out Preserve.
- 2. a kind of forest fire monitoring method based on neural network model according to claim 1, is further characterized in that： Using the humidity information at humidity sensor collection forest scene, the intensity of illumination that forest scene is gathered using light intensity sensor is believed Breath, the smokescope information at forest scene is gathered using Smoke Sensor, the wind direction at forest scene is gathered using wind transducer Information.
- 3. a kind of forest fire monitoring method based on neural network model according to claim 1, is further characterized in that： During the neural network model progress threshold decision in the following way：Humidity threshold is set in neural network model, and the humidity information that forest scene is received when neural network model is sentenced It is disconnected, if the humidity information received is more than the humidity threshold of setting, the neural network model alert, in use Neural network model described in mode is stated to complete to sentence temperature information, illumination intensity information, smokescope information and wind direction information It is disconnected, export in forest environment whether the judged result of fire-prone situation.
- 4. a kind of forest fire monitoring method based on neural network model according to claim 1, is further characterized in that： The neural network model is using communication and mobile terminal real-time data communication.
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Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109410503A (en) * | 2018-10-29 | 2019-03-01 | 中国联合网络通信集团有限公司 | A kind of fire monitoring method and apparatus, system |
| CN110147762A (en) * | 2019-05-20 | 2019-08-20 | 北京唐芯物联网科技有限公司 | A kind of embedded type fire control wrong report elimination system |
| CN112309068A (en) * | 2020-10-29 | 2021-02-02 | 电子科技大学中山学院 | Forest fire early warning method based on deep learning |
| CN112687070A (en) * | 2020-12-14 | 2021-04-20 | 浙江弄潮儿智慧科技有限公司 | Forest fire prevention early warning information emergency command system based on 5G communication |
| CN113237190A (en) * | 2021-05-24 | 2021-08-10 | 珠海拓芯科技有限公司 | Air conditioner fire prevention control method and device, air conditioner and readable storage medium |
| CN114005236A (en) * | 2021-10-09 | 2022-02-01 | 泰山学院 | Forest fire detection method and system based on Internet of things and readable storage medium |
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Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN109410503A (en) * | 2018-10-29 | 2019-03-01 | 中国联合网络通信集团有限公司 | A kind of fire monitoring method and apparatus, system |
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| CN113237190A (en) * | 2021-05-24 | 2021-08-10 | 珠海拓芯科技有限公司 | Air conditioner fire prevention control method and device, air conditioner and readable storage medium |
| CN114005236A (en) * | 2021-10-09 | 2022-02-01 | 泰山学院 | Forest fire detection method and system based on Internet of things and readable storage medium |
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