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==“Smart Cities” Course==
==“Smart City” Course==


WS 2020/2021
WS 2020/2021

Revision as of 20:24, 9 September 2020

“Smart City” Course

WS 2020/2021

Computer Networks Group, Institute of Computer Science, Universität Göttingen is collaborating with Göttinger Verkehrsbetriebe GmbH (represented by Dipl. Anne-Katrin Engelmann) and setting up this exciting course.

Leading lecturer: Prof. Xiaoming Fu

Teaching assistants: Fabian Wölk, Weijun Wang, Dr. Tingting Yuan

5-6 ECTS, 2 SWS

Course module: M.Inf.1222 (Specialisation Computer Networks, 5 ECTS) or M.Inf.1129 (Social Networks and Big Data Methods, 5 ECTS) or M.Inf.1800 (Practical Course Advanced Networking, 6 ECTS)

General Description

This course covers two aspects on Smart Cities in the context of public transport: event monitoring and passenger counting.

The goal of this course is to:

-- Help students to further understand computer networks and data science knowledge.

-- Help students to use computer science knowledge to build a practical AI system.

-- Guide students to utilize knowledge to improve the performance of the system.

In this course, each student (max. number 30) needs to:

-- Read state-of-art papers.

-- Use programming to build systems including computer vision algorithms, embedded design programs, and SOCKET network programs.

-- Learn how to analyze city public transport sensor data.

For the project we will design, implement, and deploy the system at several buses at specific positions with sub-systems consisting of:

-- Depth camera (e.g. Intel RealSense D435)

-- On-Board-Computers (e.g. Raspberry Pi Zero)

-- Power Supply (e.g. EC Technology Powerbank)

All these sub-systems in each bus will be combined to one system which shall be deployed for ideally an initial period of 2 months, thus obtaining sufficient data patterns for further analysis.

Further details are being defined.