|Dates:||Monday, 10:15 - 11.45, Zoom|
|Type:||Master lab course, 6P|
|Moodle course:||click here|
|Registration:||Registration is through the matching system|
The registration for the IoT Lab Course is through the matching system.
The slides of the premeeting are available here.
The goal of the course is to provide the hands-on experience in the development of real-world use-cases for sensing and actuating with edge devices.
The first objective is to learn how to deploy and test the open-source IoT platform that provides gateways, data storage, processing and access control functionality.
The second objective is to implement a real-world IoT use-case in a group of up to 4 persons. You will attach the sensors to edge devices, write the software that collects the measurements, and to send it to the deployed IoT platform via LoRaWAN protocol. The streamed data should be processed using the IoT platform capabilities in the scope of SMART Home, SMART City, and SMART industry scenarios that require machine learning-based modeling e.g. for predictive maintenance case.
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 system level programming, installation of large software packages, cloud native 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 using such frameworks as TensorFlow (for ML-related tasks)
- Containerized apps deployment using Kubernetes
- Computer networks
- Apache Kafka, ElasticSearch, Kibana, Apache Flink
- Linux administration
Ability to work in team is also needed for the successful completion of the course.
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 course will develop 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 LoRaWAN sensors, send to the IoT Cloud and a room occupancy prediction model will be computed. This model will be installed on the edge computer to signal the prediction to the sensor and to detect anomalies. The sensor will signal the prediction through LEDs visible at the outside of our seminar room.
More details can be found here.
the lecture on Cloud Computing covers 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.