The Software Design and Implementation of a Real-Time Automatic-Tracking System

2011 ◽  
Vol 383-390 ◽  
pp. 1595-1599
Author(s):  
Xin Yu Liu ◽  
Bo Gu
Keyword(s):  
Real Time ◽  
Software Design ◽  
Tracking System ◽  
Prediction Algorithm ◽  
Moving Target ◽  
Direction Discrimination ◽  
Target Field ◽  
Low Degree ◽  
Velocity Prediction

Aiming at the low degree and the poor real-time quality of the old monitoring system at present, this paper develops direction discrimination and velocity prediction algorithm in order to detect the parameters of moving object and then to control camera to track the abnormal moving target. Field test and operation prove that the system has a good tracking performance and stability.

Controlling a motorized electric wheelchair based on face tilting

2019 ◽  
Vol 15 (4) ◽  
Author(s):  
Hassan M. Qassim ◽  
Abdulrahman K. Eesee ◽  
Omar T. Osman ◽  
Mohammed S. Jarjees
Keyword(s):  
Quality Of Life ◽  
Real Time ◽  
Tracking System ◽  
Lower Limbs ◽  
Direct Impact ◽  
Excellent Performance ◽  
Electric Wheelchair ◽  
Real Time Tracking

AbstractDisability, specifically impaired upper and/or lower limbs, has a direct impact on the patients’ quality of life. Nowadays, motorized wheelchairs supported by a mobility-aided technique have been devised to improve the quality of life of these patients by increasing their independence. This study aims to present a platform to control a motorized wheelchair based on face tilting. A real-time tracking system of face tilting using a webcam and a microcontroller circuit has been designed and implemented. The designed system is dedicated to control the movement directions of the motorized wheelchair. Four commands were adequate to perform the required movements for the motorized wheelchair (forward, right, and left, as well as stopping status). The platform showed an excellent performance regarding controlling the motorized wheelchair using face tilting, and the position of the eyes was shown as the most useful face feature to track face tilting.

scholarly journals Wisdom of patients: predicting the quality of care using aggregated patient feedback

2017 ◽  
Vol 27 (2) ◽  
pp. 110-118 ◽  
Author(s):  
Alex Griffiths ◽  
Meghan P Leaver
Keyword(s):  
Quality Of Care ◽  
Real Time ◽  
Tracking System ◽  
Predictive Ability ◽  
Positive Association ◽  
High Risk Group ◽  
Care Quality ◽  
Multiple Sources ◽  
Patient Feedback

BackgroundThe Care Quality Commission (CQC) is responsible for ensuring the quality of healthcare in England. To that end, CQC has developed statistical surveillance tools that periodically aggregate large numbers of quantitative performance measures to identify risks to the quality of care and prioritise its limited inspection resource. These tools have, however, failed to successfully identify poor-quality providers. Facing continued budget cuts, CQC is now further reliant on an ‘intelligence-driven’, risk-based approach to prioritising inspections and a new effective tool is required.ObjectiveTo determine whether the near real-time, automated collection and aggregation of multiple sources of patient feedback can provide a collective judgement that effectively identifies risks to the quality of care, and hence can be used to help prioritise inspections.MethodsOur Patient Voice Tracking System combines patient feedback from NHS Choices, Patient Opinion, Facebook and Twitter to form a near real-time collective judgement score for acute hospitals and trusts on any given date. The predictive ability of the collective judgement score is evaluated through a logistic regression analysis of the relationship between the collective judgement score on the start date of 456 hospital and trust-level inspections, and the subsequent inspection outcomes.ResultsAggregating patient feedback increases the volume and diversity of patient-centred insights into the quality of care. There is a positive association between the resulting collective judgement score and subsequent inspection outcomes (OR for being rated ‘Inadequate’ compared with ‘Requires improvement’ 0.35 (95% CI 0.16 to 0.76), Requires improvement/Good OR 0.23 (95% CI 0.12 to 0.44), and Good/Outstanding OR 0.13 (95% CI 0.02 to 0.84), with p<0.05 for all).ConclusionsThe collective judgement score can successfully identify a high-risk group of organisations for inspection, is available in near real time and is available at a more granular level than the majority of existing data sets. The collective judgement score could therefore be used to help prioritise inspections.

Design of High Accuracy Robot Welding Machine for a Cone Bottom

2014 ◽  
Vol 496-500 ◽  
pp. 1289-1292
Author(s):  
De Huan Tang ◽  
De Yang Luo
Keyword(s):  
Real Time ◽  
Tracking System ◽  
High Accuracy ◽  
Welding Robot ◽  
Robotic Welding ◽  
High Quality ◽  
The Real ◽  
Laser Tracking ◽  
Welding Machine

This paper designed a special welding machine for an aluminum cone bottom workpiece. This machine contains highly accurate positioner system, laser tracking system, and robotic welding devices. It is used to weld the transverse seams and the longitudinal seams of the workpiece. The interaction of welding robot with positioner and the real-time seam correcting can ensure high quality of welding.

Fast Tracking of Moving Target Combining SURF and Cluster Analysis

2013 ◽  
Vol 552 ◽  
pp. 542-547
Author(s):  
Ying Li ◽  
Jing Jiang Yu ◽  
Yue Gang Fu ◽  
Zheng Ping Xu ◽  
Xun Zhou
Keyword(s):  
Cluster Analysis ◽  
Real Time ◽  
Tracking System ◽  
Moving Target ◽  
Feature Points ◽  
Fast Tracking ◽  
Tracking Process ◽  
System Requirements ◽  
And Cluster Analysis ◽  
Environment Condition

In order to design a moving target fast tracking system with respect to a real-time and stable tracking process, especially when the shape of moving target or its environment condition changes, a new algorithm named SURF-KMs is proposed. SURF-KMs combines the advantages of SURF algorithm with a cluster analysis of K-means method. First, feature points are collected and then they generate the matching template vectors based on the SURF algorithm. Second, the feature points and the center of the target are estimated by using the K-means method to determine the target’s cluster scope and update the tracking window. Finally, a self-adapting updating strategy for matching template is also proposed in order to track moving target automatically. Experimental results indicate that SURF-KMs is mostly able to achieve a stable tracking while with the monitored target rotating, scale changing, and also the environment illumination glittering. Moreover, it can satisfy the system requirements of tracking stability, higher precision and anti-jamming.

Implementation of a real-time moving object tracking system using visual servoing

Robotica ◽  
2003 ◽  
Vol 21 (6) ◽  
pp. 615-625 ◽  
Author(s):  
M-C. Tsai ◽  
K-Y. Chen ◽  
M-Y. Cheng ◽  
K.C. Lin
Keyword(s):  
Real Time ◽  
Visual Servoing ◽  
Tracking System ◽  
Moving Target ◽  
Tracking Accuracy ◽  
Security Systems ◽  
Detection Techniques ◽  
Control Scheme ◽  
High System ◽  
Automatically Tracking

Due to the increasing popularity of surveillance and security systems, the problem of automatically tracking a moving target by visual servoing has become a research topic deserving more investigation. Nonetheless, the success of tracking a moving target in real-time primarily depends on the performance of the motion detection techniques employed. This paper addresses visual tracking control of an unknown target that could be motional arbitrarily in the scene. A pan-tilt mechanism is used to gain the flexibility of tracking, and the so-called region-based matching method and motion energy method are modified and proposed in this study to detect a moving target based on the consecutive images acquired. A visual servo control scheme that adopts proportional control in the visual loop for reducing the servo lagging is proposed using output disturbance feedforward compensation. Experimental results show the superiority of the proposed method in achieving high system bandwidth and tracking accuracy.

Optimizing Design of Real-Time Spatial Moving Target Tracking System

2011 ◽  
Vol 328-330 ◽  
pp. 2234-2237
Author(s):  
Dong Sheng Liang ◽  
Zhao Hui Liu ◽  
Wen Liu
Keyword(s):  
Real Time ◽  
Video Processing ◽  
Tracking System ◽  
Processing System ◽  
Video Tracking ◽  
Image Resolution ◽  
Frame Rate ◽  
Moving Target ◽  
Detection And Tracking ◽  
Operation Speed

Achieving the detection and tracking of moving targets has been widely applied in all fields of today's society. Because of the shortcomings of traditional video tracking system, this paper proposes a novel method for designing video processing system based on hardware design of FPGA and DSP, and moving target in video can be detected and tracked by this system. In this system, DSP as the core of the system, it mainly completes the processing algorithms of video and image data, FPGA as a coprocessor, responsible for the completion of the processing of external data and logic. The hardware structure, link configuration, program code and other aspects of system are optimized. Finally, through the experiment, the input frame rate of video is 40frames/s, and the image resolution is 512pixels × 512pixels, median 16bites quantitative image sequence, the system can complete the relevant real-time detection and tracking algorithm and extract targets position of image sequences correctly. The results show that the advantage is that this system has powerful operation speed, real time, high accuracy and stability.

scholarly journals A Public Platform for Virtual IoT-Based Monitoring and Tracking of COVID-19

Electronics ◽  
2020 ◽  
Vol 10 (1) ◽  
pp. 12
Author(s):  
Younchan Jung ◽  
Ronnel Agulto
Keyword(s):  
Real Time ◽  
Information Disclosure ◽  
World Wide ◽  
Virus Disease ◽  
Tracking System ◽  
The World ◽  
Secret Keys ◽  
Control And Prevention ◽  
Real Time Information

The world is developing an app that alerts my smartphone when a COVID-19 (COrona VIrus Disease 19) confirmed case comes near me. However, regardless of what will be put to practical use first, the COVID-19 tracking system should satisfy the issues of legalization of location tracking and scalability as a public platform used by the world. Additional problems need solutions related to real-time authentication for information gathering, blind naming and privacy of tracked persons, and quality of service on the Query/Reply procedure. This paper proposes the Software-Defined Networking Controller-centric global public platform to monitor and track information for the COVID-19 relevant people and provide real-time information disclosure services to world-wide Centers for Disease Control and Prevention (CDCs) and regular users. The CDC manages a list of people who needs to be monitored related to the COVID-19 and forcibly installs COVID-19 virtual Internet of Things (vIoT) nodes in the form of applications on their smartphones. In addition to these nodes, the vIoT support nodes also engage as information providers to improve the quality of information services. The design of our platform aims to ensure confidentiality and authentication services giving individually different secret keys. In addition, our platform meets system scalability and reduces Query/Reply latency, where the platform accommodates a large number of world-wide CDCs and persons in control per CDC.

scholarly journals Effective Bandwidth Prediction through Statistical Technique over Heterogeneous Networks

2019 ◽  
Vol 8 (12) ◽  
pp. 508-512
Keyword(s):  
Real Time ◽  
Mobile Devices ◽  
Video Streaming ◽  
Heterogeneous Networks ◽  
Streaming Media ◽  
Statistical Technique ◽  
Prediction Algorithm ◽  
Effective Bandwidth ◽  
Battery Life

Real time Streaming Media (Video Streaming) applications are mostly popular on the mobiles and computers using Internet. Due to higher demand of video streaming through wireless network and mobile devices, video are being transmitted through various heterogeneous networks so as to efficiently deliver to the clients devices. This has resulted in the lower quality of real time video, since real time streaming media has quality of parameter requirements like high bandwidth, low packet loss ratio, higher delay and jitter. Streaming media such as video through heterogeneous networks has more challenges due to unreliable wireless networks and device mobility; moreover bandwidth, delay and loss are unknown in advance and are unbounded. In this paper, effective bandwidth prediction through statistical technique over heterogeneous wireless communication networks is proposed. Statistical technique offers computationally efficient bandwidth prediction with reasonably better accuracy. Especially with mobile devices with limited computational power and battery life, necessitates better bandwidth prediction with efficient but computationally simpler algorithms. Bandwidth predictions assist in selecting effective network for video streaming when various heterogeneous networks are available. Detailed bandwidth prediction algorithm is presented with use of quality of service (QoS) parameters data sets available online.

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