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Article

TraceAll: A Real-Time Processing for Contact Tracing Using Indoor Trajectories

1
Department of Computer Science, Umm Al-Qura University, Makkah 24236, Saudi Arabia
2
Department of Computer Engineering, Umm Al-Qura University, Makkah 24236, Saudi Arabia
3
Department of Computer Science and Statistics, University of Rhode Island, Kingston, RI 02881, USA
4
Faculty of Computers and Artificial Intelligence, Beni-Suef University, Giza 8655, Egypt
*
Author to whom correspondence should be addressed.
Academic Editor: Martin Haenggi
Information 2021, 12(5), 202; https://doi.org/10.3390/info12050202
Received: 14 March 2021 / Revised: 30 April 2021 / Accepted: 4 May 2021 / Published: 6 May 2021
(This article belongs to the Special Issue Big Spatial Data Management)
The rapid spread of infectious diseases is a major public health problem. Recent developments in fighting these diseases have heightened the need for a contact tracing process. Contact tracing can be considered an ideal method for controlling the transmission of infectious diseases. The result of the contact tracing process is performing diagnostic tests, treating for suspected cases or self-isolation, and then treating for infected persons; this eventually results in limiting the spread of diseases. This paper proposes a technique named TraceAll that traces all contacts exposed to the infected patient and produces a list of these contacts to be considered potentially infected patients. Initially, it considers the infected patient as the querying user and starts to fetch the contacts exposed to him. Secondly, it obtains all the trajectories that belong to the objects moved nearby the querying user. Next, it investigates these trajectories by considering the social distance and exposure period to identify if these objects have become infected or not. The experimental evaluation of the proposed technique with real data sets illustrates the effectiveness of this solution. Comparative analysis experiments confirm that TraceAll outperforms baseline methods by 40% regarding the efficiency of answering contact tracing queries. View Full-Text
Keywords: COVID19; contact tracing; query processing; spatial computing; spatial analysis; decision support systems; spatio-temporal databases COVID19; contact tracing; query processing; spatial computing; spatial analysis; decision support systems; spatio-temporal databases
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MDPI and ACS Style

Alarabi, L.; Basalamah, S.; Hendawi, A.; Abdalla, M. TraceAll: A Real-Time Processing for Contact Tracing Using Indoor Trajectories. Information 2021, 12, 202. https://doi.org/10.3390/info12050202

AMA Style

Alarabi L, Basalamah S, Hendawi A, Abdalla M. TraceAll: A Real-Time Processing for Contact Tracing Using Indoor Trajectories. Information. 2021; 12(5):202. https://doi.org/10.3390/info12050202

Chicago/Turabian Style

Alarabi, Louai; Basalamah, Saleh; Hendawi, Abdeltawab; Abdalla, Mohammed. 2021. "TraceAll: A Real-Time Processing for Contact Tracing Using Indoor Trajectories" Information 12, no. 5: 202. https://doi.org/10.3390/info12050202

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