Physics Department, TUM | Course 0000004908 in WS 2020/1

General Data

Course Type	practical training
Semester Weekly Hours	6 SWS
Organisational Unit	Informatics 11 - Chair of Connected Mobility (Prof. Ott)
Lecturers	Vittorio Cozzolino Teemu Henrikki Kärkkäinen Christian Prehofer Responsible/Coordination: Jörg Ott
Dates

Assignment to Modules

IN2106: Master-Praktikum / Advanced Practical Course
This module is included in the following catalogs:
- Further Modules from Other Disciplines

Further Information

Courses are together with exams the building blocks for modules. Please keep in mind that information on the contents, learning outcomes and, especially examination conditions are given on the module level only – see section "Assignment to Modules" above.

additional remarks	The Internet interconnects people globally and allows access to networked services pretty much anytime, anywhere. The notion of the Internet of Things (IoT) extends this to pervasive devices (i.e. the "Things"), which are increasingly networked and connected to the Internet. These devices can act as sensors or actuators can interact with other devices, e.g. including mobile phones, and with the global Internet. Edge Computing is an upcoming infrastructure paradigm where computation is pushed closer to the data source and executed on a broad range of devices ranging from RPIs to small microservers. It enables faster connections, data preprocessing and cleansing, and faster reaction time compared to cloud services. As sensors can create massive amounts of data, the interplay between IoT devices and edge networks assumes a fundamental role in the process of reducing core network saturation by offering an offloading platform where to deploy smart services independent from the cloud. The Edge Computing and the Internet of Things course aims to build local services based on IoT devices relevant to the people at a given place and time using Raspberry Pis and enhanced WLAN access points, mobile devices and local sensors. The goal of this practical course is threefold: 1. Understand the background and underlying concepts of IoT and Edge Computing based on sensing and Internet connectivity. We will provide introductory lectures and practical sessions for the background and the tools. 2. Conceptualize an application/service that fits some definition of localized IoT and edge computing with particular interest in exploiting sensing and location. 3. Design and implement your idea in a team and demonstrate it at the end of the class by documenting your system. To illustrate the above, examples of applications could be: ● A service to analyse vehicle data inside a vehicle or in an edge computing device, depending on the current load and network condition. ● A digital version of geocaching where content can be retrieved and posted via short range radio rather than exchanging physical goods with the cache. ● A local music sharing tool that allows exploring what people around you (e.g., in a certain café) would listen to. ● A basic edge analytics application using images or video feeds to do people counting (e.g. in a cafe). Topics covered during the lectures: ● Programming things: IoT OS, hardware abstractions, IoT programming frameworks ● Connecting things: lower layers, IPv6, transport protocols ● Web of things: REST, MQTT, CoAP ● IoT service architectures: Cloud-based, edge-based, device-to-device ● IoT services: Mashups, big data, machine learning ● Overview of security and IoT: privacy, threat models, attacks, mechanisms
Links	E-Learning course (e. g. Moodle) TUMonline entry

additional remarks

The Internet interconnects people globally and allows access to networked services pretty much anytime, anywhere. The notion of the Internet of Things (IoT) extends this to pervasive devices (i.e. the "Things"), which are increasingly networked and connected to the Internet. These devices can act as sensors or actuators can interact with other devices, e.g. including mobile phones, and with the global Internet. Edge Computing is an upcoming infrastructure paradigm where computation is pushed closer to the data source and executed on a broad range of devices ranging from RPIs to small microservers. It enables faster connections, data preprocessing and cleansing, and faster reaction time compared to cloud services. As sensors can create massive amounts of data, the interplay between IoT devices and edge networks assumes a fundamental role in the process of reducing core network saturation by offering an offloading platform where to deploy smart services independent from the cloud. The Edge Computing and the Internet of Things course aims to build local services based on IoT devices relevant to the people at a given place and time using Raspberry Pis and enhanced WLAN access points, mobile devices and local sensors. The goal of this practical course is threefold: 1. Understand the background and underlying concepts of IoT and Edge Computing based on sensing and Internet connectivity. We will provide introductory lectures and practical sessions for the background and the tools. 2. Conceptualize an application/service that fits some definition of localized IoT and edge computing with particular interest in exploiting sensing and location. 3. Design and implement your idea in a team and demonstrate it at the end of the class by documenting your system. To illustrate the above, examples of applications could be: ● A service to analyse vehicle data inside a vehicle or in an edge computing device, depending on the current load and network condition. ● A digital version of geocaching where content can be retrieved and posted via short range radio rather than exchanging physical goods with the cache. ● A local music sharing tool that allows exploring what people around you (e.g., in a certain café) would listen to. ● A basic edge analytics application using images or video feeds to do people counting (e.g. in a cafe). Topics covered during the lectures: ● Programming things: IoT OS, hardware abstractions, IoT programming frameworks ● Connecting things: lower layers, IPv6, transport protocols ● Web of things: REST, MQTT, CoAP ● IoT service architectures: Cloud-based, edge-based, device-to-device ● IoT services: Mashups, big data, machine learning ● Overview of security and IoT: privacy, threat models, attacks, mechanisms

Links

E-Learning course (e. g. Moodle)
TUMonline entry

Equivalent Courses (e. g. in other semesters)

Semester	Title	Lecturers	Dates
WS 2023/4	Master Practical Course: Edge Computing and the Internet of Things (IN2106, IN4261)	Bartolomeo, G. Hetzel, R. Prehofer, C. Responsible/Coordination: Ott, J.	Fri, 13:00–17:00, MI 02.09.023 Mon, 14:00–18:00, MI 02.09.023
SS 2022	Master Practical Course: Edge Computing and the Internet of Things (IN2106, IN4261)	Bese, M. Hetzel, R. Prehofer, C. Responsible/Coordination: Ott, J.	Fri, 13:00–17:00, MI 01.13.007 Mon, 16:00–18:00, MI 01.13.007
SS 2021	Master Practical Course: Edge Computing and the Internet of Things (IN2106, IN4261)	Cozzolino, V. Kärkkäinen, T. Prehofer, C. Responsible/Coordination: Ott, J.
WS 2019/20	Master Practical Course: Edge Computing and the Internet of Things (IN2106, IN4261)	Cozzolino, V. Kärkkäinen, T. Prehofer, C. Responsible/Coordination: Ott, J.

Master Practical Course: Edge Computing and the Internet of Things (IN2106, IN4261)

Course 0000004908 in WS 2020/1

General Data

Assignment to Modules

Further Information

Equivalent Courses (e. g. in other semesters)