Date of Award
Master of Science in Information Systems and Technology
Information and Decision Sciences
First Reader/Committee Chair
The number of confirmed cases of the covid-19 virus have skyrocketed since November 2019. Now researchers are beginning to realize that due to the continuous change in the mode of virus transmission, it is too slow to rely on outdated news from the government. This project focused on solving the following question: How can we use a cost effective real-time regional diagnosis to slow down the spread of the virus and save more lives? .This project developed a real-time monitoring system model that had four main modules: (1) the data receiving, processing and transmission module, (2) the real-time analysis module, (3) the remote control module, and (4) the mobile terminal module. The real-time monitoring system collected confirmed cases in specific areas (e.g. Fontana area) and rendered them through a mobile terminal module. Through the data receiving, processing and transmission module and the real-time analysis module, people in the region are reminded not to crowd too densely, resulting in accelerated virus transmission. The combination of the remote control module and mobile platform module dynamically obtained the diagnosis position, without setting a fixed sampling point. The main conclusion is that compared with manual sampling, the cost of a case monitoring system 5was more effective, and the monitoring results were more accurate. Future studies should explore more effective prevention of the virus. For example, the development of facial recognition systems can remind users to wear masks when unlocking mobile phones.
Wang, Haoyu, "APPLICATION OF REAL-TIME DETECTION SYSTEM IN EPIDEMIC PREVENTION" (2021). Electronic Theses, Projects, and Dissertations. 1314.
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Haoyu_Wang Final project.docx (725 kB)