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The fast evolving and deadly outbreak of coronavirus disease (COVID-19) has posed grand challenges to human society. To slow the spread of virus infections and better respond for community mitigation, by advancing capabilities of artificial intelligence (AI) and leveraging the large-scale and up-to-date data generated from heterogeneous sources (e.g., disease related data, demographic, mobility and social media data), in this work, we propose and develop an AI-driven system (named α-Satellite), as an initial offering, to provide dynamic COVID-19 risk assessment in the United States. More specifically, given a point of interest (POI), the system will automatically provide risk indices associated with it in a hierarchical manner (e.g., state, county, POI) to enable people to select appropriate actions for protection while minimizing disruptions to daily life. To comprehensively evaluate our system for dynamic COVID-19 risk assessment, we first conduct a set of empirical studies; and then we validate it based on a real-world dataset consisting of 5,060 annotated POIs, which achieves the area of under curve (AUC) of 0.9202. As of June 18, 2020, α-Satellite has had 56,980 users. Based on the feedback from its large-scale users, we perform further analysis and have three key findings: i) people from more severe regions (i.e., with larger numbers of COVID-19 cases) have stronger interests using our system to assist with actionable information; ii) users are more concerned about their nearby areas in terms of COVID-19 risks; iii) the user feedback about their perceptions towards COVID-19 risks of their query POIs indicate the challenge of public concerns about the safety versus its negative effects on society and the economy. Our system and generated datasets have been made publicly accessible via our website.

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Holographic Teleportation is an emerging media application allowing people or objects to be teleported in a realtime and immersive fashion into the virtual space of the audience side. Compared to the traditional video content, the network requirements for supporting such applications will be much more challenging. In this paper, we present a 5G edge computing framework for enabling remote production functions for live holographic Teleportation applications. The key idea is to offload complex holographic content production functions from end user premises to the 5G mobile edge in order to substantially reduce the cost of running such applications on the user side. We comprehensively evaluated how specific network-oriented and application-oriented factors may affect the performances of remote production operations based on 5G systems. Specifically, we tested the application performance from the following four dimensions: (1) different data rate requirements with multiple content resolution levels, (2) different transport-layer mechanisms over 5G uplink radio, (3) different indoor/outdoor location environments with imperfect 5G connections and (4) different object capturing scenarios including the number of teleported objects and the number of sensor cameras required. Based on these evaluations we derive useful guidelines and policies for future remote production operation for holographic Teleportation through 5G systems.

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