English

Every autumn semester

The purpose of the course is to provide an introduction to artificial intelligence and machine learning techniques for IoT systems e.g. wearable sensors for health monitoring.

Introduction to IoT systems and the challenges and opportunities in this domain
Introduction and foundation of machine learning and deep neural networks in the context of IoT systems e.g. for wearable devices and sensors for health monitoring and medical informatics;
Machine learning for IoT systems and distributed resource-constrained platforms.

For a passing grade the student must

understand the IoT domain and the corresponding challenges and opportunities
understand the state-of-the-art machine learning and artificial intelligence techniques
understand the fundamental ideas behind the state-of-the-art machine learning techniques in the context of IoT systems e.g. in wearable sensors for health monitoring and medical informatics.

For a passing grade the student must

analyze the suitability of a given machine learning technique for IoT systems
apply and implement the state-of-the-art techniques in machine learning and artificial intelligence in the context of IoT systems
evaluate and validate the existing machine learning techniques for IoT systems, in terms of relevant domain metrics.

For a passing grade the student must

show knowledge of the possibilities and limitations of artificial intelligence and machine learning in the context of IoT systems
independently develop, train, and implement machine learning techniques on IoT systems and investigate the results obtained.

Lectures

Laboratory exercises

Exercises

Project

Oral exam

Failed, pass

Programming, Basic probability, statistics, and algebra.

Goodfellow, I., Bengio, Y. & Courville, A.: Deep Learning. 2016.
Lindholm, A., Wahlström, N., Lindsten, F. & Schön, Thomas B.: Machine Learning, A First Course for Engineers and Scientists.
Pete Warden, D.: TinyML:, Machine Learning with TensorFlow Lite on Arduino and Ultra-Low-Power Microcontrollers.

Course Coordinator: Amir Aminifar amir.aminifar@eit.lth.se

EITP40F

2022-10-10

Maria Sandsten