Internet of Things Laboratory (IN2106, IN4224)

Prof. Dr. Michael Gerndt, Vladimir Podolskiy

 

Dates:Monday, 10:15 - 11.45, 01.06.020

Planning meeting:

7.07.17, 12:30, 01.06.020
First meeting:23.10.17
ECTS:10
Language:English
Type:Master lab course, 6P
Moodle course:click here
Registration:Registration is through the matching system

 

 

Registration

Lectures on Cloud Computing cover all the necessary theoretical and some practical aspects of Cloud Computing that is used as a base for the project to be developed in the scope of the practical course. In case you haven’t learned Cloud Computing before, we cordially invite you to attend these lectures in the same semester as IoT-Praktikum.

Registration for the IoT Lab is through the matching system. Please provide a statement about your background in related topics, e.g. virtualization, distributed programming with node.js, Scala, Go, cloud applications and management, data analytics, etc. to v.podolskiy@tum.de.

Objectives

You will learn how to receive the sensors data from external hardware and a full stack of cloud technologies for IoT. By the end of the course you will develop a scalable cloud storage and execution platform for Internet of Things to store and stream sensors data. The solution to be developed will receive sensors data from sensors installed at MakerSpace and will provide controlled access to this data for third party analytical applications.

Prerequisites

It is highly recommended to learn at least one programming language that is widely used for web programming, e.g. JavaScript, and at least one web framework, e.g. Node.js.

Ability to work in team is also needed for the successful completion of the course

Description

Internet of Things (IoT) is a novel area that thrives on numerous different technologies and transforms businesses of such companies as BMW, Siemens, General Electrics, Huawei, and many others. The main idea of Internet of Things is that each object can collect the information about itself and the environment using sensors. Such data is stored and processed in the cloud in order to receive the analytics necessary to manage an enterprise. The central component of each IoT solution is a platform to store sensors data, to prepare it for the analytical processing and to provide it in a scalable and secure manner.

You will develop such an IoT cloud-based platform in the scope of the course.

You will get practice in following topics:

  • Understanding IoT and the role of the cloud in IoT
  • Understanding business requirements to cloud applications in IoT
  • Setting up IoT equipment (boards + sensors) on the example of Odroid XU-4 boards
  • Developing on-board apps for sensors data processing and transfer to the cloud
  • Usage of cloud infrastructure and services of LRZ Cloud
  • Development, deployment and management of cloud applications
  • Data storing and streaming data processing solutions for clouds, Lambda architecture
  • Developing and managing scalable cloud storage and execution platform for IoT
  • Developing interfaces to acquire the sensors data and to provide the data to third-party IoT solutions
  • Estimation of the performance of the developed scalable cloud storage and execution platform for IoT on the real sensors data
  • Giving technical presentations about your work
  • Team work and work with other teams (TechChallenge)

In the scope of the course, you will work closely with participants of UnternehmerTUM TechChallenge (MakerSpace track) – a course provided by UnternehmerTUM each semester, in cooperation with up to 5 corporate partners and startups. One of the aims of TechChallenge is to foster digital innovation for industrial IoT, which heavily relies on Cloud Computing. The particular focus lies on student teams’ addressing a hardware- or a software-challenge, each of which is outlined together with a respective corporate partner or startup. You are also cordially invited to participate both in our lab course and in the TechChallenge as they are complementary in terms of technologies, but it is not obligatory.

The input sensors data for the developed IoT cloud-based platform is to be acquired by installing the sensors in MakerSpace equipment.