Course Package in Autonomous Sensors, 30 credits
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.
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.
Syllabuses
Electrical Engineering MA, Low-power and Energy-autonomous Systems, 7.5 creditsElectrical Engineering MA, Machine Learning on Embedded Systems, 7.5 credits
Electrical Engineering MA, Specialization Project within Autonomous Sensors, 9 credits
Electrical Engineering MA, Scientific Writing and Research Methods, 6 credits
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