Leveraging Polio GIS platforms in the African Region for mitigating Covid-19 contact tracing challenges (Preprint)

2020 ◽  
Author(s):  
Godwin Ubong Akpan ◽  
Isah Mohammed Bello ◽  
Kebba Touray ◽  
Reuben Ngofa ◽  
Daniel Oyaole ◽  
...  

BACKGROUND The growth of the novel coronavirus 2019 (COVID-19) pandemic in Africa is an urgent public health crisis. Estimated models project over 150,000 deaths and 4,600,000 hospitalizations in the first year of disease in the absence of adequate interventions. Electronic contact tracing, therefore, offers a critical role in decreasing COVID-19 transmission; yet if not conducted properly can rapidly become a bottleneck for synchronized data collection, case detection, and case management. While the continent is currently reporting relatively low COVID-19 cases, digitized contact tracing mechanisms are necessary for standardizing real-time reporting of new chains of infection to quickly reverse growing trends and halt the pandemic. OBJECTIVE The aim of this study is describing an effective contact tracing smartphone app developed with expertise and experience gained from the numerous digital apps that the Polio programme has used to successfully support disease surveillance and immunization assessment in the African Region. A secondary objective is to describe how we leveraged Polio GIS resources to enhance existing contact tracing solutions to be more efficient through the connection to real-time data visualization platforms. METHODS We propose the use of a hybrid Open Data Kit (ODK) electronic COVID-19 contact registra- tion form that automates contacts and follow-ups. A proof-of-concept form on ODK has been developed that integrates collected contact tracing information from multiple platforms to generate an interactive regional dashboard to monitor the COVID-19 response. Analytics outputs extrapolate key outbreak response indi- cators such as timeliness, completeness and outcomes of contact tracing including new positive cases. This system allows multiple outbreak outputs to be monitored including sources of new infection for immediate response with minimal disruption to existing contact tracing tools. RESULTS Standardized electronic registration of COVID-19 contacts and follow-up using ODK has en- hanced monitoring of contact tracing. Countries and communities have increased their capacity to track COVID-19 cases and contacts in the general population quickly based on the onset of signs or symptoms. Registered contacts for contact tracing are matched to their respective cases more efficiently and for con- tacts that can engage in self-reporting, the anonymity of self-reporting. The country-specific results suggest that higher adoption rates of the tools may result in better quality data on the pandemic and elicited better decisions for a response. CONCLUSIONS Our proposed contact tracing solution which uses ODK based tools on smartphones and visualization bridge systems presents a scalable and easy to implement solution, that collects and aggregates good quality contact data with geographic information that can help make spatial based decisions and preserves privacy while demonstrating the potential to help make better decisions in response to an epidemic or pandemic outbreak. This application has been applied to the current COVID-19 pandemic and can also be used for other epidemics or pandemics in the future, to achieve quality data collection for better decision making.

Author(s):  
Sepehr Fathizadan ◽  
Feng Ju ◽  
Kyle Rowe ◽  
Alex Fiechter ◽  
Nils Hofmann

Abstract Production efficiency and product quality need to be addressed simultaneously to ensure the reliability of large scale additive manufacturing. Specifically, print surface temperature plays a critical role in determining the quality characteristics of the product. Moreover, heat transfer via conduction as a result of spatial correlation between locations on the surface of large and complex geometries necessitates the employment of more robust methodologies to extract and monitor the data. In this paper, we propose a framework for real-time data extraction from thermal images as well as a novel method for controlling layer time during the printing process. A FLIR™ thermal camera captures and stores the stream of images from the print surface temperature while the Thermwood Large Scale Additive Manufacturing (LSAM™) machine is printing components. A set of digital image processing tasks were performed to extract the thermal data. Separate regression models based on real-time thermal imaging data are built on each location on the surface to predict the associated temperatures. Subsequently, a control method is proposed to find the best time for printing the next layer given the predictions. Finally, several scenarios based on the cooling dynamics of surface structure were defined and analyzed, and the results were compared to the current fixed layer time policy. It was concluded that the proposed method can significantly increase the efficiency by reducing the overall printing time while preserving the quality.


2021 ◽  
Author(s):  
Ryan Daher ◽  
Nesma Aldash

Abstract With the global push towards Industry 4.0, a number of leading companies and organizations have invested heavily in Industrial Internet of Things (IIOT's) and acquired a massive amount of data. But data without proper analysis that converts it into actionable insights is just more information. With the advancement of Data analytics, machine learning, artificial intelligence, numerous methods can be used to better extract value out of the amassed data from various IIOTs and leverage the analysis to better make decisions impacting efficiency, productivity, optimization and safety. This paper focuses on two case studies- one from upstream and one from downstream using RTLS (Real Time Location Services). Two types of challenges were present: the first one being the identification of the location of all personnel on site in case of emergency and ensuring that all have mustered in a timely fashion hence reducing the time to muster and lessening the risks of Leaving someone behind. The second challenge being the identification of personnel and various contractors, the time they entered in productive or nonproductive areas and time it took to complete various tasks within their crafts while on the job hence accounting for efficiency, productivity and cost reduction. In both case studies, advanced analytics were used, and data collection issues were encountered highlighting the need for further and seamless integration between data, analytics and intelligence is needed. Achievements from both cases were visible increase in productivity and efficiency along with the heightened safety awareness hence lowering the overall risk and liability of the operation. Novel/Additive Information: The results presented from both studies have highlighted other potential applications of the IIOT and its related analytics. Pertinent to COVID-19, new application of such approach was tested in contact tracing identifying workers who could have tested positive and tracing back to personnel that have been in close proximity and contact therefore reducing the spread of COVID. Other application of the IIOT and its related analytics has also been tested in crane, forklift and heavy machinery proximity alert reducing the risk of accidents.


2013 ◽  
Vol 278-280 ◽  
pp. 831-834 ◽  
Author(s):  
Xiao Sun ◽  
Hao Zhou ◽  
Xiang Jiang Lu ◽  
Yong Yang

This paper designed a motor winding testing system, it can do the dielectric withstand voltage test of inter-turn under 30kV.The system can communicate effectively between PC and machine, by using the PC's powerful capacity of process data and PLC's better stability and the Labview's convenient UI. So the system has real-time data collection, preservation, analysis and other characteristics. This system is able to achieve factory testing and type testing of the motor windings facilitating. Various performance indicators were stable and reliable by field test during a long time.


2019 ◽  
Vol 26 (1) ◽  
pp. 244-252 ◽  
Author(s):  
Shibom Basu ◽  
Jakub W. Kaminski ◽  
Ezequiel Panepucci ◽  
Chia-Ying Huang ◽  
Rangana Warshamanage ◽  
...  

At the Swiss Light Source macromolecular crystallography (MX) beamlines the collection of serial synchrotron crystallography (SSX) diffraction data is facilitated by the recent DA+ data acquisition and analysis software developments. The SSX suite allows easy, efficient and high-throughput measurements on a large number of crystals. The fast continuous diffraction-based two-dimensional grid scan method allows initial location of microcrystals. The CY+ GUI utility enables efficient assessment of a grid scan's analysis output and subsequent collection of multiple wedges of data (so-called minisets) from automatically selected positions in a serial and automated way. The automated data processing (adp) routines adapted to the SSX data collection mode provide near real time analysis for data in both CBF and HDF5 formats. The automatic data merging (adm) is the latest extension of the DA+ data analysis software routines. It utilizes the sxdm (SSX data merging) package, which provides automatic online scaling and merging of minisets and allows identification of a minisets subset resulting in the best quality of the final merged data. The results of both adp and adm are sent to the MX MongoDB database and displayed in the web-based tracker, which provides the user with on-the-fly feedback about the experiment.


Author(s):  
Shawn M. Turner

Travel time information is becoming more important for applications ranging from congestion measurement to real-time travel information. Several advanced techniques for travel time data collection are discussed, including electronic distance-measuring instruments (DMIs), computerized and video license plate matching, cellular phone tracking, automatic vehicle identification (AVI), automatic vehicle location (AVL), and video imaging. The various advanced techniques are described, the necessary equipment and procedures are outlined, the applications of each technique are discussed, and the advantages and disadvantages are summarized. Electronic DMIs are low in cost but typically limited to congestion monitoring applications. Computerized and video license plate matching are more expensive and would be most applicable for congestion measurement and monitoring. Cellular phone tracking, AVI, and AVL systems may require a significant investment in communications infrastructure, but they can provide real-time information. Video imaging is still in testing stages, with some uncertainty about costs and accuracy.


Author(s):  
James L. Wofford ◽  
James R. Kimberly ◽  
William P. Moran ◽  
David P. Miller ◽  
Jerry L. Hopping ◽  
...  

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