Motion image detection algorithm for juvenile obesity based on video surveillance and internet of things

2021 ◽  
Vol 81 ◽  
pp. 103788
Author(s):  
Nana Tang
Keyword(s):  
Internet Of Things ◽  
Video Surveillance ◽  
Detection Algorithm ◽  
Image Detection ◽  
Juvenile Obesity

scholarly journals Design of Vehicle License Monitoring System to Control Theft by using IOT

2019 ◽  
Vol 9 (1) ◽  
pp. 2174-2177
Keyword(s):  
Internet Of Things ◽  
Heavy Traffic ◽  
External Disturbance ◽  
Digital Camera ◽  
Detection Algorithm ◽  
Rfid Tags ◽  
License Plate ◽  
Smart Transportation ◽  
Automated Object Detection ◽  
Vehicle Movement

Smart transportation for urban cities can be done using Internet of Things (IOT). An automated object detection algorithm is used to identify the vehicle by using VLPR system. Identification of vehicle in heavy traffic or in parking lots is difficult and hence we propose a system by using RFID tags where the vehicle movement and vehicle license plate number can be obtained accurately. So by using IOT we can access the data from anywhere and the vehicle movement can be identified. Instead of using digital camera where due to external disturbance the images gets blurred, so we go for RFID where due to radio frequency transmission they stores the data. The performance of the device will not get degraded due to shadow noise, thunders and due to heavy speed. The main aim of proposed system is to check the vehicles license number and drivers vehicle license and to verify the vehicles RC book renewal.

Fuzzy Penetration Control for TIG Weld Based on Wavelet-Fractal

2013 ◽  
Vol 722 ◽  
pp. 545-549
Author(s):  
Li Qin Zhang ◽  
Li Ling Zhang ◽  
Le Hui Huang
Keyword(s):  
Closed Loop ◽  
Welding Process ◽  
Detection Algorithm ◽  
Image Feature ◽  
Fuzzy Pid ◽  
Image Detection ◽  
Controlling System ◽  
Welding Automation ◽  
Welding Image ◽  
Poor Stability

Image detection was the important step of Welding automation. In view of the welding image feature of strong noise and poor stability, conventional detect method can not get the clear welding process image, so a fuzzy detection algorithm of welding image based on wavelet and fractal denoising was presented. The fuzzy detection algorithm is used to process welding image and extract molten-pools edge; and then fuzzy PID controlling theory are combined to form a whole image processing and closed-loop penetration controlling system. The experimental results indicated that the controlling system has the good anti-interference ability in welding process and therefore ensure the stabilization of welding formation quality.

scholarly journals Research on Video Quality Diagnosis Technology Based on Artificial Intelligence and Internet of Things

2021 ◽  
Vol 2021 ◽  
pp. 1-6
Author(s):  
Zhidong Sun ◽  
Jie Sun ◽  
Xueqing Li
Keyword(s):  
Artificial Intelligence ◽  
Internet Of Things ◽  
Video Surveillance ◽  
Surveillance System ◽  
Video Quality ◽  
Noise Detection ◽  
Diagnosis System ◽  
Human Eyes ◽  
Quality Diagnosis ◽  
The Internet Of Things

The remote video diagnosis system based on the Internet of Things is based on the Internet of Things and integrates advanced intelligent technology. To better promote a harmonious society, constructing a video surveillance system is accelerating in our country. Many enterprises and government agencies have invested much money to build video surveillance systems. The quality of video images is an important index to evaluate the video surveillance system. However, as the number of cameras continues to increase, the monitoring time continues to extend. In the face of many cameras, it is not realistic to rely on human eyes to diagnose video-solely quality. Besides, due to human eyes’ subjectivity, there will be some deviation in diagnosis through human eyes, and these factors bring new challenges to system maintenance. Therefore, relying on artificial intelligence technology and digital image processing technology, the intelligent diagnosis system of monitoring video quality is born using the computer’s efficient mathematical operation ability. Based on artificial intelligence, this paper focuses on studying video quality diagnosis technology and establishes a video quality diagnosis system for video definition detection and noise detection. This article takes the artificial intelligence algorithm in the diagnosis of video quality effect. Compared with the improved algorithm, the improved video quality diagnosis algorithm has excellent improvement and can well finish video quality inspection work. The accuracy of the improved definition evaluation function for the definition detection of surveillance video and noise detection is as high as 95.56%.

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