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Abstract This study compares the use of a marker-based AR instruction with a paper instruction commonly used in manual assembly. Hypotheses were tested as to whether the instruction type affects assembly time, number of errors, usability, and employee strain. Instead of student participants and artificial assembly tasks (e. g. Lego assemblies), the study was conducted with 16 trainees in a real workplace for the assembly of emergency door release handles in rail vehicles. Five assembly runs were performed. Assembly times and assembly errors were determined from recorded videos. Usability (SUS) and strain (NASA-TLX) were recorded with questionnaires. After a slower assembly at the beginning, the AR group assembled significantly faster in the fifth run. The comparable number of errors, usability and strain make marker-based AR applications interesting for knowledge transfer in manual assembly, especially due to the easy entrance and low costs.

Abstract Smart Home technologies have the potential to increase the quality of life, home security and facilitate elderly care. Therefore, they require access to a plethora of data about the users’ homes and private lives. Resulting security and privacy concerns form a relevant barrier to adopting this promising technology. Aiming to support end users’ informed decision-making through addressing the concerns we first conducted semi-structured interviews with 42 potential and little-experienced Smart Home users. Their diverse concerns were clustered into four themes that center around attacks on Smart Home data and devices, the perceived loss of control, the trade-off between functionality and security, and user-centric concerns as compared to concerns on a societal level. Second, we discuss measures to address the four themes from an interdisciplinary perspective. The paper concludes with recommendations for addressing user concerns and for supporting developers in designing user-centered Smart Home technologies.

Abstract The Internet of Things in the home is a design space with huge potential. With sensors getting smaller and cheaper, smart sensor equipped objects will become an integral, preinstalled part of the future home. With this article we will reflect on Sensing Home, a design tool to explore sensors in the home together with people. Sensing Home allows people to integrate sensors and connectivity into mundane domestic products in order to make them smart. As such, it can be used by people to experience and explore sensors in the home and daily life. They may explore possible use cases, appropriate sensor technology, and learn about this technology through use. At the same time people may also be empowered to understand the issues and implications of sensors in the home. We present the design rationale of Sensing Home, five usage examples of how Sensing Home allowed people to explore sensor technology, and the deployment of Sensing Home together with a self-developed group discussion method to empower people to understand the benefits and pitfalls of sensors in their home. The article ends with a brief reflection whether Sensing Home is a probe or a toolkit.

Zusammenfassung Das Internet der Dinge ist schon jetzt allgegenwärtig und Apps beschränken sich nicht mehr auf traditionelle PCs und mobile Geräte. Eine SMS schickende Kuh, der Nachrichten austauschende Müllwagen und das telefonierende Projektmanagement-Werkzeug sind nur einige Beispiele. Sowohl industrielle Lösungen als auch Alltagsgegenstände werden immer interaktiver und vernetzter, so dass der Nutzer nicht mehr nur mit einem einzelnen Gerät interagiert, sondern sich inmitten einer interaktiven Umwelt bewegt. Unternehmen und Entwickler müssen sich dieser Herausforderungen stellen und unterschiedlichste Geräteformen, Interaktionsformen und Netzwerke miteinander kombinieren. Doch noch wichtiger ist es, überhaupt erst einmal neue Ideen und Szenarien für diese Anforderungen zu entwickeln. Hier sind Entwickler und Gestalter zentrale Innovationstreiber, weshalb viele Unternehmen ihre bestehenden Dienste möglichst entwicklerfreundlich und standardisiert als APIs öffnen.