Abstract
In December 2019, global communities were started to face a pandemic that was growing out of control. This chapter focus on implementing a system that uses anomaly detection on the data collected from geographically distributed subjects to mitigate the effect of Covid-19 disease by achieving the goal of early detection of the spreading. Other than the new diseases like Covid-19, most of the other known diseases and it’s spreading has been already studied to some extent and have the vaccines and treatments. So new diseases like Covid-19’s spreading can be differentiated from other disease patterns of transmission and can be seen as an anomaly. Also, as there is availability of wide range of smart devices, the anomaly detection can be a potential candidate for early detection and prevention system implementation for Covid-19-like infectious diseases. This kind of system can be used as an interactive tool to give advice and support for the end users. Analyzing the methodologies to achieve these goals will be the primary purpose of the chapter.
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Srikusan, R., Karunamoorthy, M. (2021). Implementing Early Detection System for Covid-19 Using Anomaly Detection. In: Santosh, K., Joshi, A. (eds) COVID-19: Prediction, Decision-Making, and its Impacts. Lecture Notes on Data Engineering and Communications Technologies, vol 60. Springer, Singapore. https://doi.org/10.1007/978-981-15-9682-7_5
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DOI: https://doi.org/10.1007/978-981-15-9682-7_5
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