Edge computing (EC) has shown to have a significant impact on offloading traffic/computations/AI tasks from backhaul links/servers and improving users’ Quality of Service (QoS). It is anticipated that EC in general and its use to implement AI at the edge (a.k.a. edge intelligence, EI) will be necessary components of all digital business by 2022 and that 40% of large enterprises will integrate EC/EI into their production systems by 2021.

The objective of the proposed research is to transform the already existing yet latent computing resources into on-demand clusters of distributed EC/EI workers, with a focus on distributed learning and intelligence. The proposed research will develop foundational elements of the COVID-19 and future pandemic analysis platform using KDS’s Distributed Compute Protocol (DCP). DCP allows massive computing resources to be accessed in parallel.

The proposed DCP COVID-19 project will support the Looking Glass project, a free and open platform to better inform remediation strategies, public health interventions, and vaccine campaign strategies against COVID-19 – as well as time strategies to relax lockdown measures during the recovery phase – for municipalities, state/federal authorities by modelling transmission patterns of diseases based on reports from epidemiologists fused with economic report data, and high-resolution mobility data.

Identifying disease clusters, spatial patterns, and methods of transmission of endemic, epidemic and pandemic diseases are essential to inform policymakers, programs, and interventions at both local and global scales. Health authorities depend on alerts provided by front-line employees or by members of the public when there is a disease cluster. The recent emergence of the COVID-19 as a global pandemic is one example of a critical public health threat that challenged management systems.

Industry Partner(s):Kings Distributed Systems

Academic Institution:Queen's University

Academic Researcher: Hassanein, Hossam

Focus Areas: COVID-19

Platforms: Cloud