As public libraries adopt social robots to enhance visitor interactions, understanding factors driving user acceptance is crucial. Based on the Technology Acceptance Model (TAM), present study investigates how perceived usefulness (PU), perceived ease of use (PEOU), social influences, and perceived enjoyment shape the acceptance of social robots in public libraries. 65 participants interacted in a field study held in two public libraries with the Pepper robot for book presentations. Following a qualitative approach, the influence of TAM constructs on the user experience (UX) with Pepper was explored. Results show participants valued pragmatic properties such as efficiency and task fulfillment, underscoring PU. However, transparency issues impaired usability. Social influences shaped users‘ attitudes, and perceived enjoyment emerged as an important factor, with mixed responses to the robot’s emotional engagement. Insights were used to derive 20 recommendations for improving Human-Robot Interaction (HRI) in public libraries.

The integration of AI-powered drone monitoring with thermal imaging cameras enhances wildlife protection by enabling autonomous animal detection and classification. This paper presents a system based on YOLOv8 that processes thermal data from drones, allowing single-operator usage and eliminating the need for an on-site video analyst. Through collaboration with wildlife conservation experts, we identified key requirements for real-time data processing and developed a user-centric smartphone application for instant data visualization. This study advances current methodologies by demonstrating the practical application of AI and drone technology in wildlife conservation.

Smart home systems contain plenty of features that enhance wellbeing in everyday life through artificial intelligence (AI). However, many users feel insecure because they do not understand the AI’s functionality and do not feel they are in control of it. Combining technical, psychological and philosophical views on AI, we rethink smart homes as interactive systems where users can partake in an intelligent agent’s learning. Parallel to the goals of explainable AI (XAI), we explored the possibility of user involvement in supervised learning of the smart home to have a first approach to improve acceptance, support subjective understanding and increase perceived control. In this work, we conducted two studies: In an online pre-study, we asked participants about their attitude towards teaching AI via a questionnaire. In the main study, we performed a Wizard of Oz laboratory experiment with human participants, where participants spent time in a prototypical smart home and taught activity recognition to the intelligent agent through supervised learning based on the user’s behaviour. We found that involvement in the AI’s learning phase enhanced the users’ feeling of control, perceived understanding and perceived usefulness of AI in general. The participants reported positive attitudes towards training a smart home AI and found the process understandable and controllable. We suggest that involving the user in the learning phase could lead to better personalisation and increased understanding and control by users of intelligent agents for smart home automation.

In this paper, we describe how mobile learning sets new impulses for teaching and learning in project-oriented higher education. In our project clavis, we support the self-directed learning, deepening and application of knowledge and skills in project phases of the master program of “Applied Computer Science and Systems Engineering” (AI-SE) at the University of Duisburg-Essen. Therefore, we want to provide practical examples and relevant learning units in a mobile multimedia toolbox. Students can come back to the small learning chunks during their master projects regardless of time and place. The development of our learning platform is an agile and iterative process model that is tailored to the needs of the target group. To ensure user-friendly implementation and to increase the acceptance, we involve members of the target group continuously throughout the development and implementation process. We raised the requirements in workshops with the participation of future users and the development team. Based on the findings we became aware of the requirements related to the content, didactic methods and technical concepts, that form the basis for the implementation. In this article, we provide a brief insight into our approach, the concept and the students' requirements for the development of the micro learning units and mobile learning platform.