INTERNET OF THINGS PLATFORMS FOR MANUFACTURING INDUSTRY

This course provides a fundamental knowledge of IoT, targeting physical devices, communication and computation infrastructure. The course gives theoretical knowledge as well as hands-on experiences to build an IoT application.

Learn how to use the Internet of Things (IoT) to develop smart products and services. The Internet of Things (IoT) is a collective term for the technologies that enable devices with embedded electronics and internet connectivity such as appliances, machines, and vehicles to be controlled or exchange data over a network. In this course, you will gain basic knowledge of the various components that make up Industrial Internet of Things (IIoT) systems, including sensor technologies, smart tags, data communication, and cyber security. You will learn What requirements are imposed on data communication Understand computer communication technologies and their possibilities, limitations and expected role in the development of IIoT Understand appropriate measures against common security issues

Edge computing enables faster and more energy-efficient data processing directly at the source. In robotics, this can lead to improved performance and sustainability. This course introduces the concept of edge computing and its applications in robotics. Course content • Fundamentals of edge computing• Applications of edge computing in robotics• Energy-efficient solutions for data processing What you will learn • Understand the principles of edge computing• Implement edge computing in robotic systems• Optimize data processing for energy efficiency Who is the course for?The course is designed for engineers, developers, and technicians working with robotics, IoT, and data processing who want to implement energy-efficient solutions in their projects. LanguageThe course is conducted in English. Additional informationThe course includes 15 hours of study and is offered for a fee.

Would you like to know what smart production is about? Then this is a course for you! In the course, we look at enabling technologies within advanced and smart production systems from an industrial perspective. We will cover how recent advancements in technologies such as 3D printing, computer vision, IoT, AI and robotics can be leveraged in designing new and better production flows. Focusing on how advanced production systems can be set up to allow for greater flexibility in production, both in terms of handling different unit variants and production volumes. There will also be an opportunity in the individual projects to deep dive into how these technologies could fit into your company’s needs, focusing on both the potential benefits and challenges these technologies would entail. The course covers many topics, and you will learn the basic terminology related to discrete and rapid production, connected factories and automation in assembly. You will get insight and understanding of industrial competitiveness and how it affects industry and individuals. The course work will consist of three online seminars, a project report and independent work. Examples of professional roles that will benefit from this course are manufacturing engineers, production managers and automation engineers. This course is given by Mälardalen university in cooperation with Luleå University of Technology.   Study effort: 80 hours

This course explores the role of intelligent sensor systems in driving sustainability and enabling the green transition. Participants will learn the fundamentals of sensor technologies and their integration into intelligent, distributed systems. Emphasis is placed on applications in energy efficiency, environmental monitoring, and sustainable automation. The course covers topics such as basic sensor technologies, embedded systems, distributed computing, low-resource machine learning approaches, and federated learning for privacy-preserving, decentralized model training across sensor nodes. Through a combination of lectures, practical examples, and hands-on project work, participants will gain experience in designing and deploying intelligent sensor systems tailored to real-world sustainability challenges. The students bring their own case study example as the background for a practical project, through which the student is also finally examined. Recommended prerequisites: At least 180 credits including 15 credits programming as well as qualifications corresponding to the course "English 5"/"English A" from the Swedish Upper Secondary School. Online meetings (estimated): 14 Oct.: Introduction11 Nov.: Project Idea16 Dec.: Project Presentation Study hours: 80 This course is given by Örebro University.

Understanding and optimizing battery performance is crucial for advancing electrification, sustainable mobility, and renewable energy systems. This course provides a comprehensive overview of battery performance, ageing processes, and modelling techniques to improve efficiency, reliability, and service life. Participants will explore battery operation from a whole-system perspective, including its integration in electric vehicles (EVs), charging infrastructure, and energy grids. The course covers both physics-based and data-driven modelling approaches at the cell, module, and pack levels, equipping learners with tools to monitor, predict, and optimize battery performance in real-world applications. Through this course, you will gain the ability to assess battery health, model degradation, and evaluate second-life applications from both technical and economic standpoints. Course content Battery fundamentals and degradation mechanisms Battery modelling Battery monitoring and diagnostics Operational strategies for battery systems Techno-economic performance assessment Battery second-life applications   You will learn to: Explain the principles of battery operation and degradation mechanisms. Develop battery performance models using both physics-based and data-driven approaches. Apply methods for State of Health (SOH) estimation and Remaining Useful Life (RUL) prediction. Analyze key factors influencing battery lifespan economics in different applications. Evaluate battery second-life potential and identify suitable applications. Target group: Professionals in energy, automotive, R&D, or sustainability roles Engineers and data scientists transitioning into battery technologies Technical specialists working with electrification, battery management systems, or energy storage