Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Forest grassland fire early warning system and method based on PNN neural network

A technology of fire early warning and neural network, which is applied to forest fire alarms, neural learning methods, biological neural network models, etc., can solve problems such as low accuracy, inability to obtain fire information, and mismatch, so as to improve accuracy degree of effect

Active Publication Date: 2022-01-28
TERMINUSBEIJING TECH CO LTD
View PDF11 Cites 2 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] Therefore, the technical problem to be solved by the embodiments of the present invention is to overcome the defects of low accuracy of the forest and grassland fire early warning scheme in the prior art and the inability to obtain fire information, which leads to waste of fire resources or mismatch with the fire situation, thereby providing a system based on Forest Grassland Fire Early Warning System and Method Based on PNN Neural Network

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Forest grassland fire early warning system and method based on PNN neural network
  • Forest grassland fire early warning system and method based on PNN neural network
  • Forest grassland fire early warning system and method based on PNN neural network

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0051] The present embodiment provides a kind of forest and grassland fire warning system based on PNN neural network, such as figure 1 As shown, it includes: an early warning management platform 1 and a plurality of detection devices 2 connected in communication with the early warning management platform 1;

[0052] A plurality of detection devices 2 are used to be respectively arranged in a plurality of different positions in the forest or grassland; the detection device 2 includes: a detection module 21, a wireless communication module 22 and a microprocessor 23;

[0053] The detection module 21 includes a plurality of detection sensors, and the detection sensors include at least one of a smoke sensor, a carbon dioxide concentration sensor, a carbon monoxide concentration sensor, a temperature sensor, a humidity sensor, an illumination sensor and an image sensor;

[0054] The microprocessor 23 is used to control the wireless communication module 22 to send the information d...

Embodiment 2

[0117] The present embodiment provides a kind of forest grassland fire early warning method based on PNN neural network, such as figure 2 shown, including the following steps:

[0118] S1: Using the fire early warning model based on the PNN neural network, analyze the information detected by the detection module to obtain fire early warning information, the fire early warning information includes the fire early warning level; the detection module includes a plurality of detection sensors, the The detection sensor includes at least one of a smoke sensor, a carbon dioxide concentration sensor, a carbon monoxide concentration sensor, a temperature sensor, a humidity sensor, a light sensor and an image sensor;

[0119] S2: Perform an early warning according to the fire early warning information.

[0120] In this embodiment, multiple detection sensors are used to collect fire-related information, which can improve the accuracy of fire early warning. In addition, artificial intell...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention provides a forest grassland fire early warning system and method based on a PNN neural network, and belongs to the technical field of artificial intelligence early warning. The system comprises an early warning management platform and a plurality of detection devices which are in communication connection with the early warning management platform. Each detection device comprises a detection module, a wireless communication module and a microprocessor. Each detection module comprises a plurality of detection sensors. Each microprocessor is used for controlling the wireless communication module to send the information detected by the detection module to the early warning management platform, and is also used for analyzing the information detected by the detection module by using the fire early warning model based on a PNN neural network to obtain fire early warning information including a fire early warning level. The early warning management platform is used for carrying out early warning according to the fire early warning information determined by the detection devices. According to the invention, the artificial intelligence neural network is adopted to carry out intelligent analysis on various detection information, the early warning accuracy can be improved, and the fire early warning level matched with the current fire behavior is obtained, so that the early warning processing is more suitable.

Description

technical field [0001] The invention relates to the technical field of artificial intelligence early warning, in particular to a forest and grassland fire early warning system and method based on a PNN neural network. Background technique [0002] Forest and grassland fires not only seriously damage forest and grassland resources and the ecological environment, but also cause great harm to people's lives and property and public safety, and pose a huge threat to the sustainable development of the national economy and ecological security. The specific hazards are manifested in the following aspects: burning forest and grassland vegetation resources, endangering wild animals, causing soil erosion, reducing the water quality of downstream rivers, causing air pollution, and threatening the safety of people's lives and property. [0003] Timely fire warning and timely extinguishment of forest and grassland fires at the initial stage are the most practical and effective methods, wh...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
IPC IPC(8): G08B17/00G08B21/18H04W4/38G01D21/02G06V10/22G06V10/26G06V10/30G06V10/762G06V10/774G06K9/62G06N3/00G06N3/04G06N3/08
CPCG08B17/005G08B21/182H04W4/38G01D21/02G06N3/006G06N3/08G06N3/047G06F18/23G06F18/214
Inventor 张大鹏
Owner TERMINUSBEIJING TECH CO LTD
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com