Bachelor Practical Course: IoT Sensor Nodes (IN0012, IN4224)
Course 0000002028 in SS 2024
General Data
| Course Type | practical training |
|---|---|
| Semester Weekly Hours | 6 SWS |
| Organisational Unit | Informatics 10 - Chair of Computer Architecture and Parallel Systems (Prof. Schulz) |
| Lecturers |
Hans Michael Gerndt Isaac David Nunez Araya |
| Dates |
Mon, 10:00–11:30, MI 01.06.020 |
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 | Internet of Things (IoT) provides rich platforms with distributed and lightweight applications that have transformed the businesses of companies such as Apple, BMW, Siemens, Huawei, and many others. The main idea of IoT is to collect data from devices and their surrounding environment through sensors. However, it is imperative to consider the limited resources many of these devices have. From battery to memory, everything we program has an effect. Power sources are rarely available when they are remotely located, and exchanging batteries is a complex task. Moreover, their storage units are in the range of megabytes and RAM in kilobytes, which requires avil programming to fulfill many functions while ensuring optimal resource usage. Hence, learning to collect, store, and communicate data efficiently is more critical than ever.So, during the semester, we'll be able to guide you through the intricacies of embedded programming for IoT devices by solving numerous challenges on the popular ESP32 and ESP-IDF. You will get the chance to explore and apply programming techniques, e.g., threads, memory addressing, and power optimization while learning to address the challenges of resource constraints. The Praktikum will culminate with a group project to record data through multiple sensors and nodes scattered through Fraueninsel and interconnected using our mesh network for sensors. Nonetheless, collecting data is just one part of the story. Therefore, we will also show popular software for communicating and visualizing sensor data. |
|---|---|
| Links |
E-Learning course (e. g. Moodle) Additional information Contact TUMonline entry |