Mateusz Mikusz

Repurposing Web Analytics to Support the IoT

Internet of Things analytics engines are complex to use and often optimized for a single domain or limited to proprietary data. A prototype system shows that existing Web analytics technologies can successfully be repurposed for IoT applications including sensor monitoring and user engagement tracking.

Collecting Shared Experiences through Lifelogging: Lessons Learned

The emergence of widespread pervasive sensing, personal recording technologies, and systems for the quantified self are creating an environment in which one can capture fine-grained activity traces. Such traces have wide applicability in domains such as human memory augmentation, behavior change, and healthcare. However, obtaining these traces for research is nontrivial, especially those containing photographs of everyday activities. To source data for their own work, the authors created an experimental setup in which they collected detailed traces of a group of researchers over 2.75 days. They share their experiences of this process and present a series of lessons learned for other members of the research community conducting similar studies.

Are You Feeling Lucky?: Lottery-based Scheduling for Public Displays

Scheduling content onto pervasive displays is a complex problem. Researchers have identified an array of potential requirements that can influence scheduling decisions, but the relative importance of these different requirements varies across deployments, with context, and over time. In this paper we describe the design and implementation of a lottery-based scheduling approach that allows for the combination of multiple scheduling policies and is easily extensible to accommodate new scheduling requirements.

ENGAGE: Early Insights in Measuring Multi-Device Engagements

Users are increasingly accessing content through a complex device eco-system involving both public and private screens. Traditional research into display eco-systems has focused on developing new multi-screen applications and on techniques for understanding how interactions and activities such as shopping flow across screens and devices. There has been relatively little research into the more fundamental question of how users actually engage with multiple screens and in particular how levels of engagement can be systematically monitored. In this paper we describe our early experiences with ENGAGE -- a toolkit designed to help researchers explore user engagement across multiple devices.

Audience monitor: an open source tool for tracking audience mobility in front of pervasive displays

Understanding an audiences behavior is an important aspect of evaluating display installations. In particular, it is important to understand how people move around in the vicinity of displays, including viewer transitions from noticing a display, through approach, to final use of the display. Despite the importance of measuring viewer mobility patterns, there are still relatively few low-cost tools that can be used with research display deployments to capture detailed spatial and temporal behavior of an audience. In this paper, we present an approach to audience monitoring that uses an off-the-shelf depth sensor and open source computer vision algorithms to monitor the space in front of a digital display, tracking presence and movements of both passers-by and display users. We believe that our approach can help display researchers evaluate their public display deployments and improve the level of quantitative data underpinning our field.

Memorability of cued-recall graphical passwords with saliency masks

Cued-recall graphical passwords have a lot of potential for secure user authentication, particularly if combined with saliency masks to prevent users from selecting weak passwords. Saliency masks were shown to significantly improve password security by excluding those areas of the image that are most likely to lead to hotspots. In this paper we investigate the impact of such saliency masks on the memorability of cued-recall graphical passwords. We first conduct two pre-studies (N=52) to obtain a set of images with three different image complexities as well as real passwords. A month-long user study (N=26) revealed that there is a strong learning effect for graphical passwords, in particular if defined on images with a saliency mask. While for complex images, the learning curve is steeper than for less complex ones, they best supported memorability in the long term, most likely because they provided users more alternatives to select memorable password points. These results complement prior work on the security of such passwords and underline the potential of saliency masks as both a secure and usable improvement to cued-recall gaze-based graphical passwords.

Demo: An Ecosystem for Open Display Networks

While traditional displays networks are typically closed systems, researchers are now beginning to explore the notion of open display networks in which content can be obtained from a wide range of sources. Open display networks have very different properties to closed networks as they need to deal with multiple management domains and conflicting content and scheduling requirements from different stakeholders. A key challenge is to provide an appropriate software infrastructure to support openness at all stages (e.g. content distribution, schedule creation, media playback). In this work we demonstrate a suite of software components that together provide a comprehensive eco-system for open pervasive display networks.

Using Pervasive Displays to Aid Student Recall -Reflections on a Campus-Wide Trial

University campuses are rapidly transitioning to environments that are rich in technology designed to support learning throughout the day and in diverse forms. Traditional lectures and seminars are supplemented with rich WiFi coverage, integrated learning environments, video lectures, public display networks and other innovations. Of these diverse technologies, the role and potential of public display networks in higher education is currently least understood. Indeed, most campus displays are merely used as means of information dissemination or as tools to support collaboration. In this paper, we explore the potential of pervasive display technologies as active contributors to university teaching and learning. We describe a real-world explorative study in which campus displays we used to stimulate student recall of lecture material. Our experiences demonstrate that public displays can be leveraged to provide prompts at opportune moments and invites further research in designing memory prompts to leverage the learning potential of pervasive displays in campus settings. The insights we garnered form a solid foundation and highlight opportunities and challenges in the field.

IoT-Enabled Highway Maintenance: Understanding Emerging Cybersecurity Threats

IoT technologies are increasingly being deployed to support the operation and maintenance of complex highway infrastructure assets. However, the use of interconnected cyber-physical systems in such critical infrastructure raises important privacy, security, and safety issues. While these issues are well studied in IoT transportation systems and autonomous vehicles, little research relates to highway maintenance systems. In this article, we introduce the problem domain, evince the lack of prior research, and discuss example threats based on a real-world case study.

Design considerations for multi-stakeholder display analytics

Measuring viewer interactions through detailed analytics will be crucial to improving the overall performance of future open display networks. However, in contrast to traditional sign and web analytics systems, such display networks are likely to feature multiple stakeholders each with the ability to collect a subset of the required analytics information. Combining analytics data from multiple stakeholders could lead to new insights, but stakeholders may have limited willingness to share information due to privacy concerns or commercial sensitivities. In this paper, we provide a comprehensive overview of analytics data that might be captured by different stakeholders in a display network, make the case for the synthesis of analytics data in such display networks, present design considerations for future architectures designed to enable the sharing of display analytics information, and offer an example of how such systems might be implemented.