Unlock instant, AI-driven research and patent intelligence for your innovation.

Forest smoke-fire monitoring and recognizing method suitable for distributed type parallel processing

A technology of parallel processing and identification methods, applied in fire alarms, instruments, alarms, etc., can solve the problem of large amount of real-time video stream data, and achieve the effect of enhancing the effect of identification

Active Publication Date: 2013-08-14
武汉万德智新科技股份有限公司
View PDF5 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

In the actual use of the system, the forest fire monitoring area in a certain administrative division is usually composed of multiple monitoring points distributed in various terrains, and the summary is sent back through the network level by level, especially to the provincial forestry authority In the future, the number of video channels that need to be processed at the same time may be as many as several hundred, so that the information processing centers of management departments at all levels need to process a huge amount of real-time video stream data at the same time, and the computing power of the running recognition algorithm is also raised. requirements

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 smoke-fire monitoring and recognizing method suitable for distributed type parallel processing
  • Forest smoke-fire monitoring and recognizing method suitable for distributed type parallel processing

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0033] The invention is a firework feature recognition method suitable for large-scale distributed parallel processing in a forest fire prevention real-time video monitoring system.

[0034] The technical solution of the present invention will be described in detail below in conjunction with the drawings and embodiments. see figure 1 , the process of the embodiment includes the following steps:

[0035] Step 1, intercepting video frames from the video stream, assigning an ID to each of the intercepted video frames and stamping them with time stamps, where ID is an identification code used to identify the source of the video stream, and video frames with the same ID number constitute a video frame Group.

[0036] The embodiment intercepts the video stream at a certain interval frequency (such as intercepting one frame every 5 frames), and assigns a unique ID number to the source of each front-end monitoring point as the basis for grouping, and adds a time stamp to distinguish...

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 discloses a forest smoke-fire monitoring and recognizing method suitable for distributed type parallel processing. The method comprises the following steps of: uniformly segmenting an image of each frame in video stream into video blocks with the width being W and the height being H, carrying out distributed-calculation distribution and recovery on all video blocks, fully utilizing all computing resources, supporting and processing monitoring and recognition of the characteristics of smoke and fire of large-scale video stream. The forest smoke-fire monitoring and recognizing method disclosed by the invention has the advantages that the large-scale video stream can be conveniently concentrated, and by extraction and grouping of frames, the computing resources can be submittedto a distributed computing platform for unified management and parallel recognition algorithm processing, so that the recognizing and processing capabilities are enhanced; for the detailed recognition process, the extracted image frames are segmented, the characteristic threshold can be flexibly set, and the recognition sensitivity is controlled, so that the efficiency and the accuracy of forest smoke-fire monitoring and recognition are improved.

Description

technical field [0001] The invention relates to the field of computer application technology, in particular to a forest fire monitoring and early warning method based on digital image processing and pyrotechnic identification. Background technique [0002] At present, in forest fire monitoring and early warning, various technical means have been adopted all over the world. In recent years, the forestry departments at the city and county levels in our country have mainly adopted the real-time video monitoring method in key fire danger areas. [0003] The invention patent represented by application number 02135403.0 provides a real-time video-based forest fire prevention monitoring system integration solution. Based on this scheme, the centralized monitoring of real-time video of forest fire prevention in a certain area can be constructed, which is a kind of progress technically. Real-time video monitoring can play a very good role in preventing forest fire monitoring. Howev...

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
Patent Type & Authority Patents(China)
IPC IPC(8): G08B17/00
Inventor 武小平王骞章登义
Owner 武汉万德智新科技股份有限公司
Features
  • R&D
  • Intellectual Property
  • Life Sciences
  • Materials
  • Tech Scout
Why Patsnap Eureka
  • Unparalleled Data Quality
  • Higher Quality Content
  • 60% Fewer Hallucinations
Social media
Patsnap Eureka Blog
Learn More