A new paper from our group was recently awarded Best Paper at the International Conference on Sensing, Communication and Networking 2021.

The work, titled “Compensating Altered Sensitivity of Duty-Cycled MOX Gas Sensors with Machine Learning“, has been a collaboration with researchers from TU Graz and ETH Zurich. In it, we show that it is possible to recover accurate continuous-sensor measurements from transient responses obtained from a duty cycled sensor and compensate for an altered multi-gas cross-sensitivity profile using machine learning methods.

Link to the full paper and to the teaser video.

A new paper from our group was published at the International Provenance and Annotation Workshop: Towards Provenance Integration for Field Devices in Industrial IoT Systems.

Abstract: Industrial Internet of Things (IoT) systems are becoming increasingly complex with interconnected field devices. To cope with the complexity and to facilitate further interoperability between heterogeneous field devices, it is necessary to have a holistic understanding of different types of provenance information about field devices and associated processes. In this paper, we investigate the potential integration of such provenance with the W3C Web of Things and current industrial standards to realize more explainable, efficient, and safer industrial IoT systems.

Link to the full paper

We are happy to announce that the 11^th iteration of the International Conference on the Internet of Things will take place in St Gallen (and virtually) from November 8-12^th. The IoT Conference is the premier gathering for visionary, groundbreaking research in the IoT field. It connects world-class researchers with leading industry experts to steer innovation in multiple IoT verticals (e.g., smart city, smart health, smart buildings, rural areas). Since its beginnings in 2008, the conference has been backed by strong support from leading academic institutions as well as industry.

We invite you to visit the official website for more information and encourage you to submit your contributions by August 23^rd. The topics of interest are:

• IoT Architectures
• AI and Machine Learning for the IoT
• Web of Things including Hypermedia Agents for the IoT
• New IoT Communication Technologies
• Energy Efficiency and Sustainability in IoT
• Sensing, Signal Processing, Actuation and Analytics in Small and Large-scale pilots
• Security and Privacy in IoT
• Human Interaction with IoT
• (Syntactic/Semantic) Interoperability in IoT
• Distributed Ledger Technologies for IoT
• Real-world Deployments, and Testbeds
• Novel Applications of IoT in Verticals (e.g., industrial, rural, business processes, etc.)
• Societal Impacts and Ethical Implications of the IoT

Gaze-enabled systems have been proposed decades ago but the computing power and connectivity of mobile devices enable just recently an interactive user and environment understanding in systems that are ergonomic and affordable. We believe that promising and generalizable solutions can now be achieved by developing a gaze-enabled Augmented Reality (AR) system (GEAR) that can dynamically adapt the information load on a display to the changing situation of its user and surroundings.

For instance, in an industrial setup, safety is one of the concerns when a human operator interacts with a robot. In this context, we will develop a system that will employ a mobile eye tracker as a diagnostic tool to understand the user’s cognitive situation. GEAR aims directing its user’s attention to relevant artifacts, which can be physical (e.g., emergency button or a robot) or virtual (e.g., interfaces to control the robot’s speed). Furthermore, GEAR will need to integrate information about the user, the robot, and heterogeneous virtual and physical artifacts that are available to the system. Thus, we plan to carry out a contextual assessment by integrating available sensors in the environment, semantic models and information about the user, and even state and prediction models of the robot and its behavior. Finally, GEAR will also need to be able to highlight safety-specific information within the operator’s visual field using an AR display. Additional details can be found here.

This project is funded by the University of St. Gallen and started in May 2021.

In this new project (funded by the Swiss Innovation Agency, Innosuisse) we will create, deploy, and evaluate a Mixed Reality (MR) solution for industrial maintenance, repair, and operations (MRO) with advanced context awareness and autonomy features. We aim to advance research in the domains of gaze-based assistance in remote support settings, attention tracking and personalized rendering, and integrated tooling processes.

Together with our research partner Ostschweizer Fachhochschule (OST) we will transfer our research findings and prototypes as advanced features into the main commercial product of our implementation partner, holo|one. Our application partners, Bystronic AG and pwb AG, will deploy our solutions in the field. The consortium will thus operate a complete feedback loop from academic research to the development of research prototypes, the integration of novel features in a commercial product, the deployment of the enhanced product in the field, and the on-site testing and evaluation which will inform further academic research.

In April 2021, we kicked off the project and organized two workshops that were hosted by our application partners. In these workshops, we started the initial discussions on the development of the technological requirements for the target scenarios.

Together with four partner institutions, we warmly invite young researchers and practitioners to a rich 5-day schedule of keynotes, lectures and coding! The 2021 ai4industry summer school (link to event) is dedicated to AI Technologies for Trust, Interoperability and Autonomy in Industry 4.0 and will take place on 26-30 July, 2021. Talks and discussions will focus on Web of Things, Knowledge Graphs, Multi-Agent Systems and Responsible AI, building a narrative thread towards the envisioned generation of industrial systems: industrial components are flexibly integrated and operate autonomously in dynamic and trustful environments. The summer school will also feature a hackathon that will enable participants to exploit models and tools of these four domains, while challenging them to work on concrete industrial use cases.

With respect to current health-protection measures, the event will take place in a distributed setting: participants may join one of the three physical host locations at Mines Saint-Étienne, the Friedrich–Alexander University Erlangen–Nürnberg and the University of St. Gallen, while a shared virtual location will be made available to everyone.

Together with twelve partners from across Europe, our research group is engaged in the H2020-ICT-56 Next-Generation Internet of Things Project “IntellIoT – Intelligent, Distributed, Human-centred & Trustworthy IoT Environments” (link to project). Our group’s research in this context will primarily focus on novel concepts to enable end-user programming for Hypermedia Multi-agent Systems as well as further conceptual designs and software components that enable the usage of hypermedia as a general mechanism for uniform interaction among people and autonomous software agents. We will furthermore contribute to the hypermedia-based integration of machine learning in this context, and support the project’s target use case of human-machine collaboration in manufacturing, alongside use cases in agriculture and healthcare.

A new paper from our group was published in the Personal and Ubiquitous Computing journal: Autonomous Search in a Social and Ubiquitous Web.

Abstract: Recent W3C recommendations for the Web of Things (WoT) and the Social Web are turning hypermedia into a homogeneous information fabric that interconnects heterogeneous resources: devices, people, information resources, abstract concepts, etc. The integration of multi-agent systems with such hypermedia environments now provides a means to distribute autonomous behavior in worldwide pervasive systems. A central problem then is to enable autonomous agents to discover heterogeneous resources in worldwide and dynamic hypermedia environments. This is a problem in particular in WoT environments that rely on open standards and evolve rapidly—thus requiring agents to adapt their behavior at run time in pursuit of their design objectives. To this end, we developed a hypermedia search engine for the WoT that allows autonomous agents to perform approximate search queries in order to retrieve relevant resources in their environment in (weak) real time. The search engine crawls dynamic WoT environments to discover and index device metadata described with the W3C WoT Thing Description, and exposes a SPARQL endpoint that agents can use for approximate search. To demonstrate the feasibility of our approach, we implemented a prototype application for the maintenance of industrial robots in worldwide manufacturing systems. The prototype demonstrates that our semantic hypermedia search engine enhances the flexibility and agility of autonomous agents in a social and ubiquitous Web.

Link to the full paper