Fire Detection Technologies Based on Video Image

2013 ◽  
Vol 659 ◽  
pp. 134-138
Author(s):  
Meng Xin Li ◽  
Wei Jing Xu ◽  
Ying Zhang ◽  
Jing Hou
Keyword(s):  
Signal Detection ◽  
Real Time ◽  
Monitoring System ◽  
Error Rate ◽  
Detection Method ◽  
Fire Detection ◽  
Fire Frequency ◽  
Large Impact ◽  
The Real ◽  
Detection Technologies

Because of high fire frequency and huge losses, the research of fire signal detection in the monitoring system is an important task in the fire-preventing field. The fire signal detection method based on vision can overcome the shortcomings that exist in some traditional methods i.e. it can surmount the large impact on environmental interference factors, such as temperature, photographic and smoke of environment. With many researcher’s results, it shows clearly that the error rate of flame recognition is low, and also the real-time ability and the anti-disturbance ability are very good.

scholarly journals AdaGUM: An Adaptive Graph Updating Model-Based Anomaly Detection Method for Edge Computing Environment

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Xiang Yu ◽  
Chun Shan ◽  
Jilong Bian ◽  
Xianfei Yang ◽  
Ying Chen ◽  
...  
Keyword(s):  
Internet Of Things ◽  
Anomaly Detection ◽  
Real Time ◽  
Detection Method ◽  
Edge Computing ◽  
Sensor Data ◽  
Computing Environment ◽  
The Real ◽  
Edge Node ◽  
Model Based

With the rapid development of Internet of Things (IoT), massive sensor data are being generated by the sensors deployed everywhere at an unprecedented rate. As the number of Internet of Things devices is estimated to grow to 25 billion by 2021, when facing the explicit or implicit anomalies in the real-time sensor data collected from Internet of Things devices, it is necessary to develop an effective and efficient anomaly detection method for IoT devices. Recent advances in the edge computing have significant impacts on the solution of anomaly detection in IoT. In this study, an adaptive graph updating model is first presented, based on which a novel anomaly detection method for edge computing environment is then proposed. At the cloud center, the unknown patterns are classified by a deep leaning model, based on the classification results, the feature graphs are updated periodically, and the classification results are constantly transmitted to each edge node where a cache is employed to keep the newly emerging anomalies or normal patterns temporarily until the edge node receives a newly updated feature graph. Finally, a series of comparison experiments are conducted to demonstrate the effectiveness of the proposed anomaly detection method for edge computing. And the results show that the proposed method can detect the anomalies in the real-time sensor data efficiently and accurately. More than that, the proposed method performs well when there exist newly emerging patterns, no matter they are anomalous or normal.

Design of Embedded Video Monitoring System Based on DM6437

2014 ◽  
Vol 1003 ◽  
pp. 249-253
Author(s):  
Hao Fang ◽  
Ai Hua Li ◽  
Yan Fei Liu
Keyword(s):  
Real Time ◽  
Monitoring System ◽  
Transmission Function ◽  
Video Signal ◽  
Video Encoding ◽  
Video Monitoring ◽  
Time Requirement ◽  
The Real ◽  
Monitoring Platform

To solve the difficulty of traditional video monitoring system in system upgrade and expansion, an solution of embedded video monitoring system based on DaVinci technology was put forward in this paper. By building the monitoring platform by DM6437 and DSP/BIOS in the solution, TVP5151 was used for receiving video signal in PAL/NTSC formats, and an JPEG Baseline Profile Encoder was integrated for video encoding, and the 10/100M Ethernet transmission function was realized based on NDK. Finally, the system is tested and the result shows that the system can capture and transmit D1 format signal in 25f/s and met the real-time requirement. At the same time, the system is easy to use and expand with a bright application prospect.

Detection of Human Body Motion Based on Electrostatic Measurements in the Indoor Environment

2011 ◽  
Vol 480-481 ◽  
pp. 1329-1334
Author(s):  
Wei Zheng ◽  
Zhan Zhong Cui
Keyword(s):  
Theoretical Analysis ◽  
Real Time ◽  
Human Body ◽  
Motion Detection ◽  
Average Velocity ◽  
Indoor Environment ◽  
Detection Method ◽  
Body Motion ◽  
The Real ◽  
Multiple Electrodes

An effective non-contact electrostatic detection method is used for human body motion detection. Theoretical analysis and pratical experiments are carried out to prove that this method is effective in the field of human body monitoring, in which a model for human body induced potential by stepping has been proposed. Furthermore, experiment results also prove that it’s feasible to measure the average velocity and route of human body motion by multiple electrodes array. What’s more the real-time velocity and direction of human body motion can be determined by orthogonal electrostatic detector array, and the real-time velocity and direction of human body motion can be obtained within the range of 2 meters.

scholarly journals An Approach of Failure-Analysis for the Real-Time Fire Reconnaissance Satellite-Monitoring System

2013 ◽  
Vol 6 (4) ◽  
Author(s):  
Omar Ariosto Niño Prieto ◽  
Luis Enrique Colmenares-Guillén ◽  
Edilberto Huerta Niño ◽  
Aldo Enrique Aguila Jurado
Keyword(s):  
Failure Analysis ◽  
Real Time ◽  
Monitoring System ◽  
Satellite Monitoring ◽  
The Real

scholarly journals Deformation Monitoring and Stability Analysis of Shaft Lining in Weakly Cemented Stratum

2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Xianzhou Lyu ◽  
Weiming Wang
Keyword(s):  
Real Time ◽  
Monitoring System ◽  
Coal Mine ◽  
Deformation Monitoring ◽  
Dynamic Monitoring ◽  
Thick Wall ◽  
Additional Stress ◽  
The Real ◽  
Shaft Lining

Shaft linings in thick weakly cemented stratum have the disadvantages of large deformation and repeated damage after repair. Considering the typical geologic characteristics and the failure characteristics of shaft linings, we establish a multilayer automatic deformation monitoring system in this paper, and the monitoring system can realize the real-time, continuous, and long-term dynamic monitoring on shaft linings. Based on the concrete strength failure criterion under biaxial compression and the analytical solution for spatially axisymmetric problem of thick-wall cylinders, the damage limit of the shaft lining in Xieqiao coal mine is obtained. Then, we choose three sections as the test area according to the typical damage forms of shaft linings to carry out the monitoring scheme on the auxiliary shaft in Xieqiao coal mine. The monitoring results show that the extreme value of the shaft lining deformation is 2.369 mm. And the shaft lining located in the border between the floor aquifer and the bedrock generates the most severe deformation, which is about 89.4% of the deformation limit. The shaft lining deformation increment fluctuates in certain range, which belongs to elastic deformation. Finally, we inverse the stress state according to the deformation value of the shaft lining, and the obtained additional stress is found to be lower than the ultimate compressive strength. Long-term project practice confirms that the deformation monitoring results can reflect the real stress condition of the shaft lining and that the monitoring system can realize the real-time dynamic evaluation for the status of the shaft lining.

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