Visual analysis of sensor logs in smart spaces: Activities vs. situations

Models of human habits in smart spaces can be expressed by using a multitude of representations whose readability influences the possibility of being validated by human experts. Our research is focused on developing a visual analysis pipeline (service) that allows, starting from the sensor log of a smart space, to graphically visualize human habits. The basic assumption is to apply techniques borrowed from the area of business process automation and mining on a version of the sensor log preprocessed in order to translate raw sensor measurements into human actions. The proposed pipeline is employed to automatically extract models to be reused for ambient intelligence. In this paper, we present an user evaluation aimed at demonstrating the effectiveness of the approach, by comparing it wrt. a relevant state-of-the-art visual tool, namely SITUVIS

A Role-Based Approach for Orchestrating Emergent Configurations in the Internet of Things

The Internet of Things (IoT) is envisioned as a global network of connected things enabling ubiquitous machine-to-machine (M2M) communication. With estimations of billions of sensors and devices to be connected in the coming years, the IoT has been advocated as having a great potential to impact the way we live, but also how we work. However, the connectivity aspect in itself only accounts for the underlying M2M infrastructure. In order to properly support engineering IoT systems and applications, it is key to orchestrate heterogeneous 'things' in a seamless, adaptive and dynamic manner, such that the system can exhibit a goal-directed behaviour and take appropriate actions. Yet, this form of interaction between things needs to take a user-centric approach and by no means elude the users' requirements. To this end, contextualisation is an important feature of the system, allowing it to infer user activities and prompt the user with relevant information and interactions even in the absence of intentional commands. In this work we propose a role-based model for emergent configurations of connected systems as a means to model, manage, and reason about IoT systems including the user's interaction with them. We put a special focus on integrating the user perspective in order to guide the emergent configurations such that systems goals are aligned with the users' intentions. We discuss related scientific and technical challenges and provide several uses cases outlining the concept of emergent configurations.Comment: In Proceedings of the Second International Workshop on the Internet of Agents @AAMAS201

Position paper on realizing smart products: challenges for Semantic Web technologies

In the rapidly developing space of novel technologies that combine sensing and semantic technologies, research on smart products has the potential of establishing a research field in itself. In this paper, we synthesize existing work in this area in order to define and characterize smart products. We then reflect on a set of challenges that semantic technologies are likely to face in this domain. Finally, in order to initiate discussion in the workshop, we sketch an initial comparison of smart products and semantic sensor networks from the perspective of knowledge technologies

A literature synthesis of personalised technology-enhanced learning: what works and why

Personalised learning, having seen both surges and declines in popularity over the past few decades, is once again enjoying a resurgence. Examples include digital resources tailored to a particular learner’s needs, or individual feedback on a student’s assessed work. In addition, personalised technology-enhanced learning (TEL) now seems to be attracting interest from philanthropists and venture capitalists indicating a new level of enthusiasm for the area and a potential growth industry. However, these industries may be driven by profit rather than pedagogy, and hence it is vital these new developments are informed by relevant, evidence-based research. For many people, personalised learning is an ambiguous and even loaded term that promises much but does not always deliver. This paper provides an in-depth and critical review and synthesis of how personalisation has been represented in the literature since 2000, with a particular focus on TEL. We examine the reasons why personalised learning can be beneficial and examine how TEL can contribute to this. We also unpack how personalisation can contribute to more effective learning. Lastly, we examine the limitations of personalised learning and discuss the potential impacts on wider stakeholders