CN103136538A - Multidata fusion flame recognition device and method - Google Patents
Multidata fusion flame recognition device and method Download PDFInfo
- Publication number
- CN103136538A CN103136538A CN2013100549033A CN201310054903A CN103136538A CN 103136538 A CN103136538 A CN 103136538A CN 2013100549033 A CN2013100549033 A CN 2013100549033A CN 201310054903 A CN201310054903 A CN 201310054903A CN 103136538 A CN103136538 A CN 103136538A
- Authority
- CN
- China
- Prior art keywords
- data
- sensor
- module
- data fusion
- flame
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Images
Landscapes
- Alarm Systems (AREA)
- Fire-Detection Mechanisms (AREA)
- Fire Alarms (AREA)
Abstract
The invention provides a multidata fusion flame recognition device and method. After the device and device are applied to the internet of things, the problem that node electric quantity consumption is too fast is well solved. A data fusion and pattern recognition algorithm is added, fire prediction success rate is improved, and on the contrary, energy consumption of a node is reduced. The device is effectively combined with a network in a zigbee type in a wireless sensor network (WSN), so long-distance wireless transmission of trace amount of valid data is achieved successfully. Especially after image recognition technology is applied to the device, requirements of staff for forest fire prevention are reduced, automatic collection of valid data in a wireless network is achieved, surplus data are eliminated, problems inherent in hardware in the WSN are well made up, and the device can effectively collect and feed back information in the internet of things.
Description
Technical field
The invention belongs to Internet of Things, the technical fields such as forest fire protection relate to a kind of flame identification device and method of multi-data fusion.
Background technology
Internet of Things carries out Real-time Obtaining to data, gathers environmental information, has been applied to a plurality of fields.Internet of Things is causing the life style change of a new round under the support of infotech.Along with the development of Internet of Things, an a series of scientific research difficult problem also produces in succession.This paper author is applied to technology of Internet of things to have found this class problem in the process of forest fire protection, such as: the deficiency large due to the consumption of WSN power consumption, that network life is short, caused the utilizability of node poor.Because the detectability of node in the WSN of Internet of Things is single, caused data corruption.
Summary of the invention
The object of the invention is to overcome above-mentioned technological deficiency, a kind of flame identification device and method of multi-data fusion is provided.
Its technical scheme is:
A kind of flame identification device of multi-data fusion comprises sensing module, communication module, image capture module, arduino single-chip microcomputer, and wherein single-chip microcomputer comprises processing module, data acquisition module, data fusion module:
Sensing module: gather basic data by Temperature Humidity Sensor, gas sensor, detection burning things which may cause a fire disaster sensor and imageing sensor and be used for data fusion;
Processing module: complete data fusion by the Arduino single-chip microcomputer and calculate and image recognition algorithm, thereby the judgement active data passes to communication module again, single-chip microcomputer also has the function of power management to provide power policies to whole device simultaneously;
Communication module: hard-wired Xbee protocol stack;
Data acquisition module: be the driver of sensor, the driving sensor image data, it is unnecessary, invalid to reject automatically by data lock value, the sensing data that mixes, thus reach the effect of power consumption;
Image capture module: be used for gathering image, then carry out pattern-recognition, gathered video drive and the algorithm for pattern recognition on Arduino;
Data fusion module: various information consolidations are got up to be fused into key message, report the possible intensity of a fire.
Described Temperature Humidity Sensor is the DHT11 digital hygro sensor, contains to calibrate digital signal output.
Described gas sensor, is combined with Arduino sensor special expansion board for detection of to airborne alcohol, alcohol gas based on the MQ3 gas sensor of gas sensor, is used for the concentration of the smog of detecting air.
Described detection burning things which may cause a fire disaster sensor may detect the light source of wavelength in 760 nanometers～1100 nanometer range, converts digital signal transfers to processing module.
Described imageing sensor CMUcam4 is programmable embedded image sensor, adopts Parallax P8X32A chip and Omini Vision9665CMOS camera module to flutter the photo of catching the forest Flame.
A kind of flame identification method of multi-data fusion, a kind of flame identification method of multi-data fusion is first by the camera collection data, then use single-chip microcomputer to delete and select active data, delete by the lock value and select image information, synthesize at last effective graph data, thus identification flame.
Compared with prior art, beneficial effect of the present invention is:
This application of installation has well solved the high problem of node power consumption after the Internet of Things of forest fire protection.Utilize data that Internet of Things is collected more accurately, directly to reflect the various environmental factor situations of change of monitoring site, and ageing better, can make up well the deficiency of conventional fire monitoring and warning technology.Project utilizes Data fusion technique to solve present forest fire monitoring early warning by to the tracking of inductor induction information in the fire monitoring process and the information fusion decision-making of multiple information sources.More rare is that algorithm and the software that the author uses has well made up the intrinsic problem of hardware in WSN, has invented the device of information in a kind of effective collection feedback Internet of Things.
Fig. 1 is the hardware johning knot composition of the present invention's flame identification device of filling multi-data fusion;
Fig. 2 is the flame identification device software structural drawing of multi-data fusion;
The procedure chart that Fig. 3 several data merges.
Embodiment
Below in conjunction with accompanying drawing and embodiment, device of the present invention is described in more detail.
The present invention builds the several data Fusion Model, and the data that obtain are carried out arrangement on sequential, judges valid data on the criterion of mathematical model.With the judgement of the informixs such as the flame that collects, temperature, humidity, gas.Thereby eliminated the burden that a large amount of gibberishes has alleviated network.Table 1 is the every value in data fusion model.
Table 1
| Fire probability | Temperature (C) | Humidity | Gas | Flame | Image |
| 3.023％ | 0 | 20％ | 30％ | Nothing | Nothing |
| 6.340％ | 10 | 60％ | 60％ | Nothing | Nothing |
| 19.980％ | 20 | 80％ | 80％ | Nothing | Nothing |
| 25.331％ | 30 | 100％ | 100％ | Have | Have |
| 55.326％ | 40 | 200％ | 300％ | Have | Have |
The present invention has also built the flame image model of cognition simultaneously, has realized the algorithm of identification flame, and author oneself has invented a kind of algorithm of low-power consumption, uses hardware resource seldom just can in recognition image, whether flame be arranged.Be transplanted to the characteristic of finding very perfectly to combine platform after the Arduino platform from PC the improvement of node power consumption is had significant effect.
As shown in Fig. 1-2, a kind of flame identification device of multi-data fusion comprises, sensing module, communication module, image capture module, arduino single-chip microcomputer, and wherein single-chip microcomputer comprises processing module, data acquisition module, data fusion module.Then the data that collect as various sensors in Fig. 2 obtain result through data fusion.
Sensing module: gather basic data by Temperature Humidity Sensor, gas sensor, detection burning things which may cause a fire disaster sensor and imageing sensor and be used for data fusion;
Processing module: complete data fusion by the Arduino single-chip microcomputer and calculate and image recognition algorithm, thereby the judgement active data passes to communication module again, single-chip microcomputer also has the function of power management to provide power policies to whole device simultaneously;
Communication module: hard-wired Xbee protocol stack;
Data acquisition module: be the driver of sensor, the driving sensor image data, it is unnecessary, invalid to reject automatically by data lock value, the sensing data that mixes, thus reach the effect of power consumption;
Image capture module: be used for gathering image, then carry out pattern-recognition, gathered video drive and the algorithm for pattern recognition on Arduino;
Data fusion module: various information consolidations are got up to be fused into key message, report the possible intensity of a fire.
Described Temperature Humidity Sensor is the DHT11 digital hygro sensor, contains to calibrate digital signal output.
Described gas sensor, is combined with Arduino sensor special expansion board for detection of to airborne alcohol, alcohol gas based on the MQ3 gas sensor of gas sensor, is used for the concentration of the smog of detecting air.
Described detection burning things which may cause a fire disaster sensor may detect the light source of wavelength in 760 nanometers～1100 nanometer range, converts digital signal transfers to processing module.
Described imageing sensor CMUcam4 is programmable embedded image sensor, adopts Parallax P8X32A chip and Omini Vision9665CMOS camera module to flutter the photo of catching the forest Flame.
With reference to Fig. 3, a kind of flame identification method of multi-data fusion first by the camera collection data, is then used single-chip microcomputer to delete and is selected active data, deletes by the lock value and selects image information, synthesizes at last effective graph data, thus identification flame.The single-chip microcomputers such as arduino that are deployed on node have certain processing power can carry out data fusion, consider node electric weight and processing power, use the blending algorithm based on coefficient.Supposing to have each sensor output data of a plurality of sensors is X, then they is used method of weighted mean, obtains the result of fusion.
Embodiment 1
The simulated fire scene:
| Temperature | Humidity | Gas | Flame | Image |
| 80 | 10％ | 200％ | - | - |
After accepting the temperature and humidity data, judge that by data anastomosing algorithm fire condition is arranged.The function of not opening flame and image recognition has reduced the loss of energy efficiency.Estimate by electric weight, the battery of this device is more than five times of function ordinary node of the same race.
Embodiment 2
The simulated fire scene:
| Temperature | Humidity | Gas | Flame | Image |
| 0 | 10％ | 200％ | Have | - |
After accepting the temperature and humidity data, can't judge whether the condition of a fire, the gas index is 200%, draws by blending algorithm and need to open flame sensor and identify the condition of a fire.Finding after device is opened has the condition of a fire, successfully predicts flame.
Embodiment 3
The simulated fire scene:
| Temperature | Humidity | Gas | Flame | Image |
| 30 | 10％ | 20％ | Have | Nothing |
Accepting four item numbers might be the condition of a fire according to (temperature, humidity, gas, flame) rear discovery, and blending algorithm is opened final step and checked by image recognition algorithm whether the condition of a fire is arranged in forest.Result is the invalid data of flame sensor.Arduino automatic decision not open wireless transmits, thereby has reached the effect of power saving.
The above is only best mode for carrying out the invention, anyly is familiar with those skilled in the art in the technical scope that the present invention discloses, and the simple change of the technical scheme that can obtain apparently or equivalence are replaced and all fallen within the scope of protection of the present invention.
Claims (6)
1. the flame identification device of a multi-data fusion, is characterized in that, comprises sensing module, communication module, image capture module, arduino single-chip microcomputer, and wherein single-chip microcomputer comprises processing module, data acquisition module, data fusion module:
Sensing module: gather basic data by Temperature Humidity Sensor, gas sensor, detection burning things which may cause a fire disaster sensor and imageing sensor and be used for data fusion;
Processing module: complete data fusion by the Arduino single-chip microcomputer and calculate and image recognition algorithm, thereby the judgement active data passes to communication module again, single-chip microcomputer also has the function of power management to provide power policies to whole device simultaneously;
Communication module: hard-wired Xbee protocol stack;
Data acquisition module: be the driver of sensor, the driving sensor image data, it is unnecessary, invalid to reject automatically by data lock value, the sensing data that mixes, thus reach the effect of power consumption;
Image capture module: be used for gathering image, then carry out pattern-recognition, gathered video drive and the algorithm for pattern recognition on Arduino;
Data fusion module: various information consolidations are got up to be fused into key message, report the possible intensity of a fire.
2. the flame identification device of multi-data fusion according to claim 1, is characterized in that, described Temperature Humidity Sensor is the DHT11 digital hygro sensor, contains to calibrate digital signal output.
3. the flame identification device of multi-data fusion according to claim 1, it is characterized in that, described gas sensor is based on the MQ3 gas sensor of gas sensor, for detection of arriving airborne alcohol, alcohol gas, be combined with Arduino sensor special expansion board, be used for the concentration of the smog of detecting air.
4. the flame identification device of multi-data fusion according to claim 1, is characterized in that, described detection burning things which may cause a fire disaster sensor may detect the light source of wavelength in 760 nanometers～1100 nanometer range, converts digital signal transfers to processing module.
5. the flame identification device of multi-data fusion according to claim 1, it is characterized in that, described imageing sensor CMUcam4 is programmable embedded image sensor, adopts Parallax P8X32A chip and Omini Vision9665CMOS camera module to flutter the photo of catching the forest Flame.
6. the flame identification method of a multi-data fusion, is characterized in that, first by the camera collection data, then uses single-chip microcomputer to delete and select active data, deletes by the lock value and select image information, synthesizes at last effective graph data, thus identification flame.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN2013100549033A CN103136538A (en) | 2013-02-04 | 2013-02-04 | Multidata fusion flame recognition device and method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN2013100549033A CN103136538A (en) | 2013-02-04 | 2013-02-04 | Multidata fusion flame recognition device and method |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN103136538A true CN103136538A (en) | 2013-06-05 |
Family
ID=48496345
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN2013100549033A Pending CN103136538A (en) | 2013-02-04 | 2013-02-04 | Multidata fusion flame recognition device and method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN103136538A (en) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106384102A (en) * | 2016-09-30 | 2017-02-08 | 深圳火星人智慧科技有限公司 | IR-card-equipped day-night digital network camera flame detection system and method |
| CN107566373A (en) * | 2017-09-07 | 2018-01-09 | 中山火炬职业技术学院 | Internet of Things data fusion method, device, terminal and computer-readable recording medium |
| CN110278533A (en) * | 2019-06-14 | 2019-09-24 | 浙江理工大学 | Forest fire protection data communications method based on network control system |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20100023362A (en) * | 2008-08-21 | 2010-03-04 | 랜스(주) | Zigbee fire defense system |
| US20120302219A1 (en) * | 2011-05-24 | 2012-11-29 | Vang Vang | Monitoring and automating a network of independent wireless remote devices based on a mobile device location |
| CN202584340U (en) * | 2012-05-30 | 2012-12-05 | 英利能源（中国）有限公司 | Forest fire hazard alarm system |
-
2013
- 2013-02-04 CN CN2013100549033A patent/CN103136538A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20100023362A (en) * | 2008-08-21 | 2010-03-04 | 랜스(주) | Zigbee fire defense system |
| US20120302219A1 (en) * | 2011-05-24 | 2012-11-29 | Vang Vang | Monitoring and automating a network of independent wireless remote devices based on a mobile device location |
| CN202584340U (en) * | 2012-05-30 | 2012-12-05 | 英利能源（中国）有限公司 | Forest fire hazard alarm system |
Non-Patent Citations (2)
| Title |
|---|
| 余荣华: ""森林火灾图像自动识别系统的研究与实现"", 《中国优秀硕士学位论文全文数据库（信息科技辑）》, 30 June 2010 (2010-06-30) * |
| 颜学义: ""基于ZigBee的智能火灾报警系统设计"", 《中国优秀硕士学位论文全文数据库（信息科技辑）》, 31 May 2010 (2010-05-31) * |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106384102A (en) * | 2016-09-30 | 2017-02-08 | 深圳火星人智慧科技有限公司 | IR-card-equipped day-night digital network camera flame detection system and method |
| CN107566373A (en) * | 2017-09-07 | 2018-01-09 | 中山火炬职业技术学院 | Internet of Things data fusion method, device, terminal and computer-readable recording medium |
| CN110278533A (en) * | 2019-06-14 | 2019-09-24 | 浙江理工大学 | Forest fire protection data communications method based on network control system |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN107831285B (en) | A kind of dystrophication monitoring system and method based on Internet of Things | |
| CN101922310B (en) | Security monitoring and managing system of coal mine underground operators | |
| CN206594783U (en) | A kind of forest fire monitoring system based on wireless sense network | |
| CN107767618A (en) | wireless environment monitoring system based on internet of things | |
| US11935378B2 (en) | Intrusion detection methods and devices | |
| CN205809598U (en) | A kind of water resources fund based on Internet of Things management platform | |
| CN204759670U (en) | Forest fire prevention system based on cloud calculates | |
| CN105005234A (en) | Intelligent greenhouse environment remote measurement and control system based on zigbee | |
| CN107231738A (en) | city street lamp state monitoring method and device | |
| CN206258860U (en) | A kind of data collection station based on Internet of Things and cloud | |
| CN101848240A (en) | System and method for monitoring parameters of watermelon seedling raising environment | |
| CN106227689A (en) | A kind of based on Internet of Things and the data collection station of cloud | |
| CN103136538A (en) | Multidata fusion flame recognition device and method | |
| Yan et al. | Field microclimate monitoring system based on wireless sensor network | |
| CN110445762A (en) | Intelligent environment protection monitoring management system in highway network based on Internet of Things | |
| CN106815961A (en) | A kind of forest fire protection focus networking monitoring device and monitoring method based on Lora wireless technologys | |
| CN202306884U (en) | Internet of things experiment system based on wireless sensing network | |
| CN205983585U (en) | Join in marriage net transformer system of patrolling and examining, RFID module and handheld piece module | |
| CN106292611A (en) | A kind of wisdom agricultural control system based on cloud computing | |
| CN104049602A (en) | Nursing hog house monitoring system of multi-path routing algorithm | |
| CN105788141A (en) | Forest fire early-warning system powered by microbiological fuel cell and realizing method thereof | |
| CN105137891A (en) | Internet of things passive data acquisition system | |
| CN107643102A (en) | A kind of environmental improvement monitoring and managing method and device based on Internet of Things | |
| Zhu et al. | Forest fire detection system based on ZigBee wireless sensor network | |
| CN205983736U (en) | Warehouse security intelligent monitoring system based on thing networking |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| C02 | Deemed withdrawal of patent application after publication (patent law 2001) | ||
| WD01 | Invention patent application deemed withdrawn after publication |
Application publication date: 20130605 |