Course: Mathematics for Smart Systems credits: 5

This module covers mathematics often used in smart systems, especially applied linear algebra. 

 Professional products  

• Simulations and calculations – Studying the performance of a process or system through the imitation of a physical system or design in a virtual environment or on paper. In this module: Calculations involving linear algebra, used for data fusion 
• Smart system – A system that incorporates (multiple) sensor(s), data processing, and automation to analyse information, make decisions, and adapt to changing conditions, enhancing efficiency, performance, and user interaction or recommendations. 
• System Design – An overview of components and interactions between different components of a system. It includes the design of software and hardware architecture, components, interfaces, and data. 
• Software for a Smart System – The applications and algorithms that enable intelligent functionality, data processing, decision-making, and communication within a smart system. It typically includes embedded software, control software, and communication protocols to facilitate real-time operations, automation, and system integration. 

Skills 

• Information and recommendation generation – The process of analyzing and combining data—often through embedded software, data fusion, and AI algorithms—to produce meaningful insights or actionable suggestions. This enables systems to support decision-making, personalize responses, or automate actions based on real-time sensor input and learned patterns. 

Knowledge  

• Linear algebra – The branch of mathematics that deals with vectors, matrices, and linear equations, and studies how they can be used to model and solve problems involving linear relationships. Concepts include matrices, vectors, systems of equations, fundamental subspaces, orthogonality and least squares, determinants, eigenvalues and eigenvectors, singular value decomposition, etc.