Seminar: COVID-19 — Distributed Risk Response
Background
With the onset of COVID-19 as a world pandemic, social contact plays an important role in the spread of the virus. When a person is tested positive for the virus, the risk of infection of that person’s social network increases. As a mean to slow down the spread of the virus, experts propose to remove individuals at risk from the general population. Some countries started deploying centralised systems to notify, identify, and request to self-isolate individuals at risk, based on their social connections.
Aim
The goal of the seminar is to build a distributed messaging system that enables a user to update the risk of their network in the case of a status change.
Learning Objectives
- Gain an overview of edge computing and decentralized messaging frameworks.
- Understand concepts of privacy, global consistency and distributed ledgers.
- Apply messaging frameworks, and compare performance for safety and accuracy.
- Create a distributed health risk calculator which enables users to notify others that they might be at risk of being infected, and they should self-isolate.
Course Data
| Project type | Seminar (optional: Bachelor or Master thesis) |
| ECTS | 5 |
| Language | English |
| Period | Summer semester 2020 |
| Presence time | Virtual seminar, working from remote. |
| Useful knowledge | Python, data analytics |
| Work distribution | 40% algorithm development, 30% data analysis and evaluation, 20% consultation, 10% reporting |
| Med. Eng. designation | Advanced Context Recognition (ACR) |
| StudOn link | Please join |
| First meeting | Online introduction/Vorbesprechung, see: online-introduction-vorbesprechung-of-summer-term-2020-seminars |
| Registration | Via StudOn, obligatory after introduction. |
Literature
Up-to-date literature recommendations are provided during the lectures.
Examination
- Final project presentation, demonstrator and final report.
Contact
Dr. Luis I. Lopera G.
- Job title: Researcher
- Address:
Henkestraße 91, Haus 7, 1. OG
91052 Erlangen
Germany - Phone number: +49 9131 85-23605
- Email: luis.i.lopera@fau.de