I-Interaction: An Intelligent In-Vehicle User Interaction Model

The automobile is always a point of interest where new technology has been deployed. Because of this interest, human-vehicle interaction has been an appealing area for much research in recent years. The current in-vehicle design has been improved but still possesses some of the design from the traditional interaction style. In this paper, we propose a new user-oriented model for in-vehicle interaction model known as i-Interaction. The i-Interaction model provides user with an intuitive approach to interact with the In-Vehicle Information System (IVIS) by the keypad entry. It is the intent that the proposed usability testing for this model will help improve the way research and development is implemented from this topic. This model does not only provide the user with a direct interaction in vehicles but also introduce a new prospective that other research has not addressed.Comment: 11 pages, 4 figure

PISTIL : Persuasive Interaction for Sus TainabILity

International audienc

Data work: how energy advisors and clients make IoT data accountable

We present fieldwork findings from the deployment of an interactive sensing system that supports the work of energy advisors who give face-to-face advice to low-income households in the UK. We focus on how the system and the data it produced are articulated in the interactions between professional energy advisors and their clients, and how they collaboratively anticipate, rehearse, and perform data work. In addition to documenting how the system was appropriated in advisory work, we elaborate the ‘overhead cost’ of building collaborative action into connected devices and sensing systems, and the commensurate need to support discrete workflows and accountability systems to enable the methodical incorporation of the IoT into collaborative action. We contribute an elaboration of the social, collaborative methods of data work relevant to those who seek to design and study collaborative IoT systems

Eyewear Computing \u2013 Augmenting the Human with Head-Mounted Wearable Assistants

The seminar was composed of workshops and tutorials on head-mounted eye tracking, egocentric vision, optics, and head-mounted displays. The seminar welcomed 30 academic and industry researchers from Europe, the US, and Asia with a diverse background, including wearable and ubiquitous computing, computer vision, developmental psychology, optics, and human-computer interaction. In contrast to several previous Dagstuhl seminars, we used an ignite talk format to reduce the time of talks to one half-day and to leave the rest of the week for hands-on sessions, group work, general discussions, and socialising. The key results of this seminar are 1) the identification of key research challenges and summaries of breakout groups on multimodal eyewear computing, egocentric vision, security and privacy issues, skill augmentation and task guidance, eyewear computing for gaming, as well as prototyping of VR applications, 2) a list of datasets and research tools for eyewear computing, 3) three small-scale datasets recorded during the seminar, 4) an article in ACM Interactions entitled \u201cEyewear Computers for Human-Computer Interaction\u201d, as well as 5) two follow-up workshops on \u201cEgocentric Perception, Interaction, and Computing\u201d at the European Conference on Computer Vision (ECCV) as well as \u201cEyewear Computing\u201d at the ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp)

Human-centered machine learning through interactive visualization

The goal of visual analytics (VA) systems is to solve complex problems by integrating automated data analysis methods, such as machine learning (ML) algorithms, with interactive visualizations. We propose a conceptual framework that models human interactions with ML components in the VA process, and makes the crucial interplay between automated algorithms and interactive visualizations more concrete. The framework is illustrated through several examples. We derive three open research challenges at the intersection of ML and visualization research that will lead to more effective data analysis

A Case for Making Web Accessibility Guidelines Accessible: Older Adult Content Creators and Web Accessibility Planning

This paper presents our experiences supporting web accessibility planning among a group of older adult online content creators. We highlight challenges we encountered meeting the web accessibility informational needs of our partners and helping this group of creators become aware and put in place measures to address accessibility issues. Our reflections highlight opportunities for future efforts to improve web accessibility support for everyday content creators and support for helping those less familiar with web accessibility options

Mobile assistive technologies for the visually impaired

There are around 285 million visually impaired people worldwide, and around 370,000 people are registered as blind or partially sighted in the UK. Ongoing advances in information technology (IT) are increasing the scope for IT-based mobile assistive technologies to facilitate the independence, safety, and improved quality of life of the visually impaired. Research is being directed at making mobile phones and other handheld devices accessible via our haptic (touch) and audio sensory channels. We review research and innovation within the field of mobile assistive technology for the visually impaired and, in so doing, highlight the need for successful collaboration between clinical expertise, computer science, and domain users to realize fully the potential benefits of such technologies. We initially reflect on research that has been conducted to make mobile phones more accessible to people with vision loss. We then discuss innovative assistive applications designed for the visually impaired that are either delivered via mainstream devices and can be used while in motion (e.g., mobile phones) or are embedded within an environment that may be in motion (e.g., public transport) or within which the user may be in motion (e.g., smart homes)