Titlebook: Intelligent Secure Trustable Things; Michael Karner,Johannes Peltola,Peter Priller Book‘‘‘‘‘‘‘‘ 2024 The Editor(s) (if applicable) and The

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The InSecTT Reference Architecture new AI (Artificial Intelligence) algorithms and their associated building blocks (BBs) on standard architectures for IoT. The chapter focuses on the main views or perspectives of the architecture, on how AI interacts with each one of these perspectives and in the end we provide two examples of use

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Structuring the Technology Landscape for Successful Innovation in AIoTt in such a large project with many partners be structured and managed to lead to successful innovations? Especially in such a highly competitive market of digital solutions? This section provides an overview of processes and methods, from requirement engineering, followed by technology structuring,

REIGN

InSecTT Technologies for the Enhancement of Industrial Security and Safetyf the huge potential benefits in productivity, these trends also bring in some concerns related to safety and security to the traditionally closed industrial operation scenarios. This paper presents a high-level view of some of the research results and technological contributions of the InSecTT Proj

Coronation

Algorithmic and Implementation-Based Threats for the Security of Embedded Machine Learning Models confidentiality and availability. These security issues encompass the overall traditional machine learning pipeline, including the training and the inference processes. In the case of embedded models deployed in physically accessible devices, the attack surface is particularly complex because of ad

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Indoor Navigation with a Smartphonemmunication networks. The system, implemented as a smartphone app, relies on QR codes that are pre-generated and attached to the walls inside the building. By utilizing the information from these codes and the smartphone‘s inertial motion unit (IMU) sensors processed by the Pedestrian Dead-Reckoning

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Reconfigurable Antennas for Trustable Things and assets. Additionally, the reliability of Internet of Things components is crucial from the application point of view, where a resilient and low-latency network is needed. This can be achieved by utilizing reconfigurable antennas to  enhance the capabilities of the wireless sensor network (WSN).

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AI-Enhanced Connection Management for Cellular Networksas smart mobility, intelligent transportation systems and autonomous driving heavily depend on the availability of ubiquitous connectivity. In addition, consumer demand for cellular network resources is ever growing. In the context of the InSecTT project, cellular connectivity contributes, e.g., to