Dit is de lectorale rede van Jeroen Linssen, lector Symbiotic AI bij het lectoraat Ambient Intelligence van Hogeschool Saxion. Artificial Intelligence maakt veel dingen mogelijk en werpt veel uitdagingen op. AI wordt steeds ‘slimmer’, maar worden wij dat zelf ook? Hoe gaan we verantwoord om met deze …

Revolutionary advances in technology have been seen in many industries, with the IIoT being a prime example. The IIoT creates a network of interconnected devices, allowing smooth communication and interoperability in industrial settings. This not only boosts efficiency, productivity, and safety but also …

Abstract Technology has a major impact on the way nurses work. Data-driven technologies, such as artificial intelligence (AI), have particularly strong potential to support nurses in their work. However, their use also introduces ambiguities. An example of such a technology is AI-driven lifestyle monitoring …

The effective operation of distributed energy sources relies significantly on the communication systems employed in microgrids. This article explores the fundamental communication requirements, structures, and protocols necessary to establish a secure connection in microgrids. This article examines the …

This graduation project, led by the Smart Industry research group at Saxion together with the Ambient Intelligence research group (AmI), aims to create an energy analysis tool for the SERENE/SUSTENANCE projects in the Dutch sustainable communities of Vriendenerf and Aardehuis. The goal of the project …

Peer-reviewed artikel over semantische segmentatie van point clouds.

The graduation project of Andrii Roizin, a software engineering student at Saxion, was developed as a part of the Sportkeur 2.0 project. This project is led by Go2Sure and the Saxion Ambient Intelligence research group is one of its partners.             The purpose of the project was to discover the …

An overview of fundamentals, best practices and a tutorial.

The goal of this study was to develop an automated monitoring system for the detection of pigs’ bodies, heads and tails. The aim in the first part of the study was to recognize individual pigs (in lying and standing positions) in groups and their body parts (head/ears, and tail) by using machine learning …