IoT Laboratory (IN2106)

Prof. Dr. Michael Gerndt, Vladimir Podolskiy

Registration

Registration for the IoT Lab Course is through the matching system.

Goal

The goal of this course is to provide you the hands-on experience in Internet of Things (IoT) technologies, viz, implementation of the real-world use-cases for sensing and actuating using microcontrollers and cloud. You will gather the experience of working with the real hardware, connecting it to the IoT platform, deploying your own virtual machines in the cloud, collecting the measurements, processing them, and making the predictions based on these data. 

Prerequisites

For the successful participation in the course, it is most important to be enthusiastic about building IoT applications. It is helpful to have background in programming for microcontroller units (MCUs), web application technologies, and data analytics techniques. 

As teams are arranged of multiple students, it is not obligatory to have the experience in all of the mentioned areas.

Particularly, it is advantageous to have the experience in some of the following topics:

• Programming in C/C++ (for programming the edge device)
• Programming in Python or Node.js
• ML frameworks e.g. TensorFlow / PyTorch
• REST API
• Apache Kafka, ElasticSearch, Kibana
• Linux administration
• Docker [ optional ]

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. Edge computers are used to receive and forward sensor data as well as to provide low latency control messages. 

The use case that you will work with in this course is a Room Tracking system. We will monitor the number of people entering or exiting our seminar room. The data will be used to predict in advance if the room will be available in the future and anomalies from the typical room usage will be identified. The data will be recorded by MCU-based sensor nodes, sent over WLAN to the I10 IoT Cloud platform, and further used to predict the room occupancy on virtual machines that act as an edge server. The sensor node will show the current room occupancy and the prediction on the attached display. 

Connected courses

Lectures on Cloud Computing cover some theoretical knowledge and practical aspects of cloud computing relevant for this course. In case you haven’t learned cloud computing before, we cordially invite you to attend these lectures.