Abstract
The global outbreak of the COVID-19 in the worldwide has drawn lots of attention recently. The elderly are more vulnerable to COVID-19 and tend to have severe conditions and higher mortality as their immune function decreased and they are prone to having multiple chronic diseases. Therefore, avoiding viral infection, early detection and treatment of viral infection in the elderly are important measures to protect the safety of the elderly. In this paper, we propose a real-time robot-based COVID-19 detection system: Epidemic Guard. It combines speech recognition, keyword detection, cough classification, and medical services to convert real-time audio into structured data to record the user’s real condition. These data can be further utilized by the rules engine to provide a basis for real-time supervision and medical services. In addition, Epidemic Guard comes with a powerful pre-training model to effectively customize the user’s health status.
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Acknowledgements
This paper is supported by National Key Research and Development Program of China under grant No.2018YFB1003500, No.2018YFB0204400 and No.2017YFB-1401202. Corresponding author is Jianzong Wang from Ping An Technology (Shenzhen) Co., Ltd.
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Wei, W., Wang, J., Cheng, N., Chen, Y., Zhou, B., Xiao, J. (2020). Epidemic Guard: A COVID-19 Detection System for Elderly People. In: Wang, X., Zhang, R., Lee, YK., Sun, L., Moon, YS. (eds) Web and Big Data. APWeb-WAIM 2020. Lecture Notes in Computer Science(), vol 12318. Springer, Cham. https://doi.org/10.1007/978-3-030-60290-1_44
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DOI: https://doi.org/10.1007/978-3-030-60290-1_44
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