Bachelor-Praktikum: IoT Sensor Nodes (IN0012, IN4224)
Bachelor Practical Course: IoT Sensor Nodes (IN0012, IN4224)
Lehrveranstaltung 0000002028 im SS 2024
Basisdaten
| LV-Art | Praktikum |
|---|---|
| Umfang | 6 SWS |
| betreuende Organisation | Informatik 10 - Lehrstuhl für Rechnerarchitektur & Parallele Systeme (Prof. Schulz) |
| Dozent(inn)en |
Hans Michael Gerndt Isaac David Nunez Araya |
| Termine |
Mo, 10:00–11:30, MI 01.06.020 |
Zuordnung zu Modulen
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IN2106: Master-Praktikum / Advanced Practical Course
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weitere Informationen
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| ergänzende Hinweise | 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. |
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| Links |
E-Learning-Kurs (z. B. Moodle) Zusatzinformationen Kontakt TUMonline-Eintrag |