Name:
tero project
Description:
Studying Internet latency from Gaming Footage
Professor — Lab:
Katerina ArgyrakiNetwork Architecture Lab

Home page:
tero project
Layman description:
The project collects screenshots from video game live streams on Twitch. It reads the Internet latency numbers displayed on screen during gameplay. It figures out the streamer's location from their social media information. It processes all this data to estimate the Internet speed in different parts of the world.
Technical description:
The system downloads gaming footage from the Twitch streaming platform. It extracts the displayed latency measurements using optical character recognition and knowledge of each game's user interface. It maps streamers to locations using natural language processing on their social media profiles. It analyzes the measurements to produce latency distributions per geographical location.
Papers:
Project status:
active — entered showcase: 2024-03-08 — entry updated: 2024-03-08

Source code:
Lab Github - last commit: 2023-12-12
Code quality:
This project has not yet been evaluated by the C4DT Factory team. We will be happy to evaluate it upon request.
Project type:
Application
Programming language:
Python