Antagningsdata

Choose region and language

Choose the language for the entire website.

Published education catalogue

Course Package in Autonomous Sensors

Education information from the published source. The education record and its time-bound offerings are kept separate.

Education facts

Code: ETA06

Sensors and sensor systems are increasingly used in many application domains, such as industrial and process automation, environmental monitoring, and smart cities. A consequence of this is a growing demand for these systems to operate more autonomously and to be less dependent on existing infrastructures for energy supply and data handling. This course package provides you with a thematic semester on enabling technologies for autonomous sensors. You will learn about low-power techniques and methods for energy harvesting that enable sensor systems to operate energy-autonomously. Moreover, you will learn about embedded machine learning to bring modern data analysis approaches as close to the origin of the data as possible. Finally, you will conduct a project, which will deepen your understanding of this domain, and provide you with a foundation in conducting and communicating research. The course package consists of the following courses: Low-power and Energy-autonomous Systems, 7.5 credits, Machine Learning on Embedded Systems, 7.5 credits, Specialization Project within Autonomous Sensors, 9 credits, and Scientific Writing and Research Methods, 6 credits.

Entry requirements

Electrical Engineering BA, 45 credits, including digital electronics, microcontrollers and analog electronics.

Education offerings

Each offering has its own dates and conditions. Closed offerings are retained as history and do not mean that a new application is open.

Source and updates

Skolverket Susa-navet

Retrieved: .

Published: .

Show source version

Publication version: 8e217193-f5fa-4778-b085-a4521fd03e8d

Checksum: 1b0dc54c0fc8a359f83ba9dc8f9d468479ce432de4c03bce3b8b33dd67fe3f6c

Last changed according to the source: 2025-11-06T08:56:44