Designers face opportunities and challenges in leveraging AI to make sense of increasingly available data. There is limited research on how designers engage with AI in data sensemaking to inform design decisions, especially in safety-critical contexts. To address this knowledge gap, we co-designed and evaluated an AI-supported prototype that supports data exploration using truck interaction design as a case study. Our analysis highlighted a bidirectional relationship between AI and data, where designers used AI to gain an overview of user scenarios, and used data to contextualize and validate AI outputs. We identified three sensemaking styles, illustrating how designers flexibly orchestrated expertise, data, and interaction to interpret AI outputs. Our findings contribute to an in-depth characterization of AI-supported data sensemaking and offer implications for designing tools that empower diverse, situated, and critical engagement with data through AI in high-stakes settings.

As artificial intelligence continues to permeate working life, the integration of AI in truck UX design is gaining prominence. While the majority of AI research, especially in the field of Explainable AI (XAI), is rooted in a technical perspective, this work explores and unpacks the user perspective by addressing the research question: “How do UX designers of truck HCI systems perceive AI explanations in an AI-powered data analytics platform?”. To address this question, a prototype of such a platform was co-designed and evaluated by 17 experts in truck UX design. Findings highlight that for AI explanations to be perceived as useful, they need to be understandable, contextually relevant, and verifiable, with the ability to dynamically adapt to users’ evolving knowledge and objectives. These findings extend prior research by emphasizing the importance of contextual and human-centered values in designing and developing AI-enabled systems with explainability, and by calling for future transdisciplinary collaboration to address evolving contextual user needs in truck UX design and beyond.

The connection of intelligent devices and agents via the Internet of Things (IoT) provides a foundation for smart health care systems to monitor the status of patients, their activities, and their environments and to provide services that can improve health. These smart health ecosystems connect patients, caregivers, and medical professionals with each other and with data captured by sensors and other devices. Health care applications using this data can store and track relevant metrics, provide alerts when metrics are outside expected ranges, and provide feedback and recommendations to assist in the management of a wide variety of health issues, including weight management, stroke rehabilitation, and glucose monitoring. This chapter provides an overview of different types of IoT‐based patient‐focused health care applications providing these types of services. The chapter concludes with a discussion of the major challenges related to health care technology using the Internet of Things and the future potential of these applications.

Data-driven design is believed to be empowered by machine learning (ML) with advanced pattern classification and prediction. However, research on how ML can be used to support automotive human-machine interface (HMI) design is lacking. We presented a case study of truck HMI design to understand the current data use and expectations of ML in the design process. Findings show decentralized data practices, the role of expertise in decision-making, and the envisioned reactive use of ML, where we underscore the implications for advancing human-ML collaboration in designing future truck HMI systems.

The potential for information and communication technology (ICT) to support the delivery of social services, and the possible benefits afforded, have been acknowledged in numerous studies. The many obstacles to the adoption and integration of ICT into social services have also been documented. This paper provides a summary of those issues as the backdrop to the description of a study conducted to understand the adoption of a specific technology (OmMej) in the context of children’s social care in Sweden. This study looks at the perceived benefits provided through the use of OmMej, particularly in terms of the opportunity for children to have a voice in their care and the impact on this technology on social work practice. The study also identifies barriers to the successful deployment of the tool, and some lessons learned that can inform other implementation efforts. drawing to explore international student experience in Scotland. Historically rich pictures are difficult to interpret and are often used to gain a holistic understanding of a system of concern and thus are disregarded in terms of providing in-depth qualitative data. We will explore the use of inter-coder content analysis to gain a deep understanding of group thinking. In the context of this study, using content analysis, our findings revealed a detailed understanding of Scottish culture and traditions from the perspective of international students. We determine that visuals have a vast capacity to communicate, irrespective of possible language, culture and education barriers, and thus offer unique insight into a complex system of stakeholder understanding. 

We have investigated machine learning based cheating behaviour detection in physical activity-based smart-phone games. Sensor data were acquired from the accelerometer/gyroscope of an iPhone 7 during activities such as jumping, squatting, stomping, and their cheating counterparts. Selected attributes providing the most information gain were used together with a sequential model yielding promising results in detecting fake activities. Even better results were achieved by employing a random forest classifier. The results suggest that machine learning is a strong candidate for detecting cheating behaviours in physical activity-based smartphone games.

Building on existing research and experiences regarding the use of supportive and assistive technology -- called welfare technology -- in elderly care, we have developed a framework to represent a holistic view of the complex tangle of factors contributing to the sustainable integration of these technologies into the elder care context. The framework is described here for the purpose of initiating a conversation regarding the framework with interested researchers. At the same time discussions are also being conducted with managers, caregivers, and other stakeholders involved in welfare technology deployment in eldercare in Sweden. Our ultimate goal with the framework is to provide general guidelines that municipalities and care organizations can use to improve the quality of life for elderly citizens through the successful selection, rollout and use of welfare technology that meets the needs not only of the elderly citizens needing support but also of the care providers and organizations. 

We seek to investigate possibilities of extending the emotional and cognitive experience of using products or services through the cross-modality of vision with other senses (synesthesia). Through multi-sensory, interactive environments, consumers become more engaged in the use of a product or service and may, in fact, participate as co-creators of their own experiences. To achieve the highest level of spontaneity and provoke human activation to enable us to study this, we suggest an experimental context based on interactive technologies, aesthetics and design. For this purpose, we use an artistic environment in the form of an interactive installation. Two examples of such experimental interactive art installations, Art Machine: Mindcatcher and Re-Digital, are described in this paper.

Överallt samlar sensorer data som analyseras för att räkna ut hur man sparar energi, hur mycket insulin som ska injiceras, var den närmaste hyrbilen finns, hur många människor som fortfarande är kvar inne i en brinnande byggnad... Denna snabba spridning av teknik kallas för Sakernas Internet, eller IoT. Människor har makten, eller har vi verkligen det? Hur mycket värderar vi vår integritet? Vilka internetanslutna gadgets hjälper oss att leva ett hälsosamt och hållbart liv - och vilka prylar kommer bara att öka vår stressnivå? När blir användningen missbruk? Utställningen undersöker hur IoT påverkar människor, samhälle och industri. Forskningsprojekt i utställningen: Emergent Configuration for IoT Systems (ECOS+), Smart energy management and security (SEMS), Fair Data, Walk the ward, Dynamic Intelligent Sensor-Intensive Systems (DISS), PELARS-projektet och Busrunner presenteras i "IOTAP-labbet"

All around us sensors collect data, which is analyzed to figure out how to save energy, how much insulin to inject, where the closest rental bike is located, how many people are still inside a building that is on fire… This fast-spreading technology is called the Internet of Things, or IoT for short. People have the power, or do we really? How much do we value our privacy? What internet connected gadgets will help us lead a healthy, sustainable life – and what gadgets will only increase our stress level? When does use become abuse? This exhibition explores how IoT affects people, society and industry. You are welcome to try out IoT through demos and hands-on experiences based on research projects at Malmö University. Research projects in the exhibition: Emergent Configuration for IoT Systems (ECOS+), Smart energy management and security (SEMS), Fair Data, Walk the ward, Dynamic Intelligent Sensor-Intensive Systems (DISS), PELARS project and Busrunner are presented in the "IOTAP-lab"