Design and Implementation of Embedded Multimedia Surveillance System

Author(s):  
Yan Liu ◽  
Ren-Fa Li ◽  
Cheng Xu ◽  
Fei Yu
Author(s):  
Godwin Akpan ◽  
Johnson Muluh Ticha ◽  
Lara M.F. Paige ◽  
Daniel Rasheed Oyaole ◽  
Patrick Briand ◽  
...  

BACKGROUND Acute Flaccid Paralysis (AFP) surveillance is the bedrock of polio case detection. The Auto Visual AFP Detection and Reporting (AVADAR) is a digital health intervention designed as a supplemental community surveillance system. OBJECTIVE This paper describes the design and implementation process that made AVADAR a successful disease surveillance strategy at the community level. METHODS This paper outlines the methods for the design and implementation of the AVADAR application. It explains the co-design of the application, the implementation of a helpdesk support structure, the process involved in trouble shooting the application, the benefits of utilizing a closed user group for telecommunication requirements, and the use of a consented video. We also describe how these features combined led to user acceptance testing using black box methodology. RESULTS A total of 198 community informants across two provinces, four districts and 32 settlements were interviewed about application performance, usability, security, load, stress and functionality testing black box components. The responses showed most community participants giving positive reviews. Data from the Blackbox testing yielded optimum acceptance ratings from over 90% of the users involved in the testing. A total of 22380 AFP Alerts were sent out by community informants and 21589 (95%) were investigated by health workers or WHO AVADAR coordinators. Overall there was 93% assimilation at regional level. About 83% of investigations were done in the vicinity of the alerts in 2018 compared to 77% in 2017. CONCLUSIONS AVADAR implementation model offers a simplistic step by step model that includes community participation as an integral tool for the successful deployment of a mobile based surveillance reporting tool. AVADAR can be a veritable source of project planning data and a mobile application for other interventions that target using community participation to influence health outcomes.


2016 ◽  
Vol 76 (22) ◽  
pp. 23777-23804 ◽  
Author(s):  
Zeyad Q. H. Al-Zaydi ◽  
David L. Ndzi ◽  
Munirah L. Kamarudin ◽  
Ammar Zakaria ◽  
Ali Y. M. Shakaff

2015 ◽  
Vol 738-739 ◽  
pp. 779-783
Author(s):  
Jin Hua Sun ◽  
Cui Hua Tian

In view of the problems existed in moving object detection in video surveillance system, background subtraction method is adopted and combined with Surendra algorithm for background modeling, an algorithm of detecting moving object from video is proposed, and OpenCV programming is adopted in Visual c ++ 6.0 for implementation. Experimental results indicate that the algorithm can accurately detect and identify moving object in video by reading the image sequence of surveillance video, the validity of the algorithm is verified.


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