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Interaction- and Communication-based Systems

Prof. Dr. Simon Mayer

In our research group, we explore interactions among devices and people in ubiquitous computing environments. Our focus is on the integration of physical things into the Web, on increasing the autonomy of Web-enabled devices, and on making interactions of connected devices intelligible for people.


BetterPlanet: Sustainability Feedback from Digital Receipts

A new paper from our group has been published at the International Conference on Advances in Mobile Computing and Multimedia Intelligence (MoMM 2022): BetterPlanet: Sustainability Feedback from Digital Receipts

Abstract: The global food system accounts for 25–30% of anthropogenic greenhouse gas emissions. A large share of these emissions is due to individual food shopping patterns. Despite the rising concern about the environment, many individuals fail to act upon it and change their food consumption. In this study, we attempt to motivate individuals to reduce their food-shopping-induced environmental footprint. To narrow the intention-behavior gap, we propose a novel technical system that gives automated near-term sustainability feedback on individuals’ food shopping recorded on digital receipts and communicates this feedback through the mobile application BetterPlanet. Based on a small sample (n = 8), we find a directional decrease in the overall CO2-Scores. Therefore, our study demonstrates the technical feasibility of automated sustainability feedback from digital receipts. The proposed energy-weighted CO2-Scoring Model contributes to the growing knowledge body of sustainability assessment.

Author: Simon Mayer

Date: 27. November 2022

Increasing the Intelligence of Low-Power Sensors with Autonomous Agents

A new paper from our group has been published and won the Best Paper Award at the 2022 Workshop on Challenges in Artificial Intelligence and Machine Learning for Internet of Things (in conjunction with ACM SenSys 2022): Increasing the Intelligence of Low-Power Sensors with Autonomous Agents

Abstract: Low-power sensors are becoming ever more powerful, increasing both their energy efficiency as well as their processing capabilities. Much work in recent years has focused on optimizing machine learning models to low-power systems, typically to locally process sensor data. Significantly less attention has been paid to other artificial intelligence fields such as knowledge representation and automated reasoning, which may contribute to building autonomous devices. In this work, we present a low-power sensor node with an autonomous belief-desire-intention agent. This kind of agent simplifies the implementation of both proactive and reactive behaviors, promoting autonomy in our target applications. It does so by locally perceiving and reasoning, and then wirelessly broadcasting an intention, which can be forwarded to an actuator. The capabilities of the autonomous agent are demonstrated with a light-control application. Experiments demonstrate the feasibility of running intelligent agents in low-power platforms with little overhead.

Author: Simon Mayer

Date: 26. November 2022

Solar Semantics: Every Thing under the Sun

A new paper from our group has been published at the Next-Generation Internet of Things Infrastructures Workshop of the 12th International Conference on the Internet of Things: Every Thing Under the Sun: How Web of Things and Semantic Data Brings Benefit to Small-Scale Photovoltaic Installations

Abstract: Small-scale photovoltaic (PV) systems of up to a few kilowatts capacities are becoming increasingly available and affordable for off-grid installations. However, in our experience with using PV energy in farming in India, we found that many installations had faults or were lying underutilized. Though integrating such systems into IoT applications is now practical, analyzing the system’s performance and utilization requires knowledge of the components and the system design. Off-band infusion of this knowledge into the software applications leads to tight coupling and vertical silos. To address this challenge, we have developed an ontology to describe small-scale PV installations, which enables us to represent subsystems and their components in the form of Web of Things (WoT) Thing Descriptions. We show that our approach results in technical and semantic integration of the PV system into IoT applications, allowing the development of reusable fault detection and optimization programs. This reduces the cost of developing solutions to monitor and optimize the usage of PV systems, thereby bringing benefits to the farming community by improving their livelihood.

Author: Simon Mayer

Date: 26. November 2022

Semantic OCR through Augmented Reality

A new paper from our group has been published at the 12th International Conference on the Internet of Things: Semantic OCR through Augmented Reality (SOCRAR)


To enable people to interact more efficiently with virtual and physical services in their surroundings, it would be beneficial if information could more fluently be passed across digital and non-digital spaces. To this end, we propose to combine semantic technologies with Optical Character Recognition on an Augmented Reality (AR) interface to enable the semantic integration of (written) information located in our everyday environments with Internet of Things devices. We hence present SOCRAR, a system that is able to detect written information from a user’s physical environment while contextualizing this data through a semantic backend. The SOCRAR system enables in-band semantic translation on an AR interface, permits semantic filtering and selection of appropriate device interfaces, and provides cognitive offloading by enabling users to store information for later use. We demonstrate the feasibility of SOCRAR through the implementation of three concrete scenarios.

Link to the full paper

Author: Simon Mayer

Date: 20. November 2022

FoodCoach: Automated e-coach for a healthier diet

FoodCoach is a study by the University of St.Gallen and the University Hospital of Bern, supported by Swiss National Science Foundation and Sanitas Management AG. Sanitas Management AG supports the recruiting of study participants without interfering with the study content.

Project Goal:

The objective of this research project is to investigate the effectiveness of improving people’s food shopping healthiness by providing automated food shopping recommendations.

Participants donate their grocery data recorded on the loyalty card programs “Migros Cumulus” and “Coop Supercard”. Based these data, the study team has built a model to generate automated recommendations according to the Nutri-Score framework and expertise of dieticians at the University Hospital of Bern. The results of the study could possibly help improve the health status of the Swiss population and beyond in a low-cost, automated, and longitudinal manner.


Unhealthy diets are a major risk for the development of non-communicable diseases. Changing unhealthy dietary behavior can have a significant impact on this risk. Providing interventions towards individual food purchase behavior offers tremendous potential to reduce cardiometabolic morbidity and mortality by the promotion of a healthier diet. By using digital receipts, data on purchased food can be collected automatically. This provides the opportunity to analyze food choices according to different criteria and design automated, low-cost and longitudinal interventions.Fo

How can I participate and what can I benefit?

You need to be at least 18 years old and use Migros Cumulus and/or Coop Supercard to join the study.

By consenting to participate, your historic and up-to-date grocery data recorded on Migros Cumulus and/or Coop Supercard will be anonymously shared with the study team. In return, you will receive an analysis of your food shopping. Your anonymized partial food shopping data will be published to support health and nutrition researchers world-wide.

You can quit the study at any time without giving reasons or incurring any risks.

Find more details and join the study on by December 15, 2022.

For your best experience, we recommend joining the study via your mobile phone.

Author: Jing Wu

Date: 20. November 2022

Towards Semantic Content Negotiation

A new poster with involvement of our group has been published at the 23rd International Conference on Knowledge Engineering and Knowledge Management: A Step Toward Semantic Content Negotiation



Content negotiation aims at enabling a server to provide a client with a representation of a resource that meets its needs. However, client and server might desire to negotiate constraints that go beyond the media type or language of the alternative representation. This is especially true in the Semantic Web, as a resource can be described with a single media type, but with different vocabularies (FOAF,, etc.), and may match specific patterns. In this paper, we propose an approach to increase the flexibility when negotiating a representation between client and server. Our approach follows the goals of the World Wide Web and uses a set of existing technologies: SHACL and profile-based negotiation. We define the mechanism (in terms of protocol and algorithm) for clients to announce their expectations and for servers to react and respond to them. We then explain, through a use case, how the same approach could be used in Web-based Multi-Agent Systems to help autonomous agents achieve their goals on the Web.

Link to the full paper

Author: Simon Mayer

Date: 28. September 2022

Machine Capacity of Judgment

A new paper from our group has been published in Technology and Society: Machine Capacity of Judgment: An Interdisciplinary Approach for making Machine Intelligence Transparent to End Users.

Abstract: Intelligent machines surprise us with unexpected behaviors, giving rise to the question of whether such machines exhibit autonomous judgment. With judgment comes (the allocation of) responsibility. While it can be dangerous or misplaced to shift responsibility from humans to intelligent machines, current frameworks to think about responsible and transparent distribution of responsibility between all involved stakeholders are lacking. A more granular understanding of the autonomy exhibited by intelligent machines is needed to promote a more nuanced public discussion and allow laypersons as well as legal experts to think about, categorize, and differentiate among the capacities of artificial agents when distributing responsibility. To tackle this issue, we propose criteria that would support people in assessing the Machine Capacity of Judgment (MCOJ) of artificial agents. We conceive MCOJ drawing from the use of Human Capacity of Judgment (HCOJ) in the legal discourse, where HCOJ criteria are legal abstractions to assess when decision-making and judgment by humans must lead to legally binding actions or inactions under the law. In this article, we show in what way these criteria can be transferred to machines.

Link to the full paper

Author: Simon Mayer

Date: 7. September 2022

A Typology of Automatically Processable Regulation

A new paper from our group has been published in Law, Innovation and Technology: A Typology of Automatically Processable Regulation.

Abstract: The possibility of encoding regulation to make it processable automatically by computers has been gaining attention within the legal discipline. With it, an abundance of terms has emerged as much as an array of academic discussions providing different examples, raising different concerns, while, unfortunately, having different premises in mind. This makes contributions within the field of what we refer to as ‘automatically processable regulation’ difficult to compare with each other and research results hard to transfer among different research projects and groups. To overcome this problem, we propose a typology that enables researchers to locate their research project within the domain of automatically processable regulation, understand what issues might arise depending on where within the typology a project falls, and determine the relationship between projects.The typology revolves around three dimensions: the primary aim of the project, the potential for divergence of interests amongst stakeholders, and the degree of mediation by computers.

Link to the full paper

Author: Simon Mayer

Date: 6. September 2022



Full Professor, Interaction and Communication based Systems


Research Assistant, Hypermedia Multi-agent Systems