Low-Cost CNN Design for Intelligent Surveillance System

2018 ◽  
Author(s):  
Liang Wei Yang ◽  
Chung Yen Su
Keyword(s):  
Surveillance System ◽  
Low Cost ◽  
Intelligent Surveillance

Situational Strategic Awareness Monitoring Surveillance System–Microcomputer and Microcomputer Clustering used for Intelligent, Economical, Scalable, and Deployable Approach for Safeguarding Materials

2020 ◽  
Vol 2020 (3) ◽  
pp. 60408-1-60408-10
Author(s):  
Kenly Maldonado ◽  
Steve Simske
Keyword(s):  
Surveillance System ◽  
Cost Effective ◽  
Government Agencies ◽  
Electronic Systems ◽  
Time Data ◽  
Potential Threat ◽  
Intelligent Surveillance ◽  
World Markets ◽  
Programming Software ◽  
And Control

The principal objective of this research is to create a system that is quickly deployable, scalable, adaptable, and intelligent and provides cost-effective surveillance, both locally and globally. The intelligent surveillance system should be capable of rapid implementation to track (monitor) sensitive materials, i.e., radioactive or weapons stockpiles and person(s) within rooms, buildings, and/or areas in order to predict potential incidents proactively (versus reactively) through intelligence, locally and globally. The system will incorporate a combination of electronic systems that include commercial and modifiable off-the-shelf microcomputers to create a microcomputer cluster which acts as a mini supercomputer which leverages real-time data feed if a potential threat is present. Through programming, software, and intelligence (artificial intelligence, machine learning, and neural networks), the system should be capable of monitoring, tracking, and warning (communicating) the system observer operations (command and control) within a few minutes when sensitive materials are at potential risk for loss. The potential customer is government agencies looking to control sensitive materials and/or items in developing world markets intelligently, economically, and quickly.

PyDOSS: An open-source Python-based communicable disease outbreak surveillance system designed and used in a COVID-19 community care facility (Preprint)

2020 ◽  
Author(s):  
Andrew Fang ◽  
Jonathan Kia-Sheng Phua ◽  
Terrence Chiew ◽  
Daniel De-Liang Loh ◽  
Lincoln Ming Han Liow ◽  
...  
Keyword(s):  
Open Source ◽  
Surveillance System ◽  
Community Care ◽  
Communicable Disease ◽  
Low Cost ◽  
Real Life ◽  
Disease Outbreak ◽  
Disease Spread ◽  
Healthcare Team ◽  
Increased Risk

BACKGROUND During the Coronavirus Disease 2019 (COVID-19) outbreak, community care facilities (CCF) were set up as temporary out-of-hospital isolation facilities to contain the surge of cases in Singapore. Confined living spaces within CCFs posed an increased risk of communicable disease spread among residents. OBJECTIVE This inspired our healthcare team managing a CCF operation to design a low-cost communicable disease outbreak surveillance system (CDOSS). METHODS Our CDOSS was designed with the following considerations: (1) comprehensiveness, (2) efficiency through passive reconnoitering from electronic medical record (EMR) data, (3) ability to provide spatiotemporal insights, (4) low-cost and (5) ease of use. We used Python to develop a lightweight application – Python-based Communicable Disease Outbreak Surveillance System (PyDOSS) – that was able perform syndromic surveillance and fever monitoring. With minimal user actions, its data pipeline would generate daily control charts and geospatial heat maps of cases from raw EMR data and logged vital signs. PyDOSS was successfully implemented as part of our CCF workflow. We also simulated a gastroenteritis (GE) outbreak to test the effectiveness of the system. RESULTS PyDOSS was used throughout the entire duration of operation; the output was reviewed daily by senior management. No disease outbreaks were identified during our medical operation. In the simulated GE outbreak, PyDOSS was able to effectively detect an outbreak within 24 hours and provided information about cluster progression which could aid in contact tracing. The code for a stock version of PyDOSS has been made publicly available. CONCLUSIONS PyDOSS is an effective surveillance system which was successfully implemented in a real-life medical operation. With the system developed using open-source technology and the code made freely available, it significantly reduces the cost of developing and operating CDOSS and may be useful for similar temporary medical operations, or in resource-limited settings.

scholarly journals Design of Intelligent Surveillance System for Cable Connector

2020 ◽  
Vol 598 ◽  
pp. 012096
Author(s):  
Hongguang Li ◽  
Xinhua Feng ◽  
Deming Wu ◽  
Lifeng Liang
Keyword(s):  
Surveillance System ◽  
Intelligent Surveillance

scholarly journals Low-Cost National Media-Based Surveillance System for Public Health Events, Bangladesh

2016 ◽  
Vol 22 (4) ◽  
pp. 720-722 ◽  
Author(s):  
Trong T. Ao ◽  
Mahmudur Rahman ◽  
Farhana Haque ◽  
Apurba Chakraborty ◽  
M. Jahangir Hossain ◽  
...  
Keyword(s):  
Public Health ◽  
Surveillance System ◽  
Low Cost ◽  
Health Events ◽  
National Media

scholarly journals Study on the Surveillance System of Water Stage Used the Resonator Pressure Transducer and Wireless Connectivity

2018 ◽  
Vol 228 ◽  
pp. 02001
Author(s):  
Bing Han ◽  
Qiang Fu
Keyword(s):  
Surveillance System ◽  
Pressure Transducer ◽  
Oil And Gas ◽  
Low Cost ◽  
Regional Scale ◽  
Time Data ◽  
Long Distance ◽  
Hydrogeological Parameters ◽  
Water Stage ◽  
Wireless Connectivity

For the sake of ameliorating the faultiness of low precision for conventional surveillance methods of water stage, and realize the goal of real time data collection, automated actions and long-distance conveying, we have designed a novel surveillance system of water stage with the resonator pressure transducer and wireless connectivity technologies. The surveillance system of water stage has come into service in a field experiment project of a certain oil and gas pipeline engineering. By analyzing and comparing the results of experiments, the system has the merits of high agility, reliability, instantaneity and accuracy, low cost, capacity of resisting disturbance, which making it ideal for use in unattended supervising of water stage for multi-spots observation based on regional scale. The surveillance system can well satisfy the actual demand of auto hydrogeological parameters monitoring for geotechnical engineering.

Identification of crowd behaviour patterns using stability analysis

2021 ◽  
pp. 1-15
Author(s):  
V. Muhammed Anees ◽  
G. Santhosh Kumar
Keyword(s):  
Real Time ◽  
Surveillance System ◽  
Security Requirements ◽  
Video Sequences ◽  
World Population ◽  
System Modelling ◽  
Intelligent Surveillance ◽  
Flow Modelling ◽  
Wide Range ◽  
Crowd Behaviour

Crowd behaviour analysis and management have become a significant research problem for the last few years because of the substantial growth in the world population and their security requirements. There are numerous unsolved problems like crowd flow modelling and crowd behaviour detection, which are still open in this area, seeking great attention from the research community. Crowd flow modelling is one of such problems, and it is also an integral part of an intelligent surveillance system. Modelling of crowd flow has now become a vital concern in the development of intelligent surveillance systems. Real-time analysis of crowd behavior needs accurate models that represent crowded scenarios. An intelligent surveillance system supporting a good crowd flow model will help identify the risks in a wide range of emergencies and facilitate human safety. Mathematical models of crowd flow developed from real-time video sequences enable further analysis and decision making. A novel method identifying eight possible crowd flow behaviours commonly seen in the crowd video sequences is explained in this paper. The proposed method uses crowd flow localisation using the Gunnar-Farneback optical flow method. The Jacobian and Hessian matrix analysis along with corresponding eigenvalues helps to find stability points identifying the flow patterns. This work is carried out on 80 videos taken from UCF crowd and CUHK video datasets. Comparison with existing works from the literature proves our method yields better results.

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