Ubicomp for animal welfare: envisioning smart environments for kenneled dogs

Whilst the ubicomp community has successfully embraced a number of societal challenges for human benefit, including healthcare and sustainability, the well-being of other animals is hitherto underrepresented. We argue that ubicomp technologies, including sensing and monitoring devices as well as tangible and embodied interfaces, could make a valuable contribution to animal welfare. This paper particularly focuses on dogs in kenneled accommodation, as we investigate the opportunities and challenges for a smart kennel aiming to foster canine welfare. We conducted an in-depth ethnographic study of a dog rehoming center over four months; based on our findings, we propose a welfare centered framework for designing smart environments, integrating monitoring and interaction with information management. We discuss the methodological issues we encountered during the research and propose a smart ethnographic approach for similar projects

Arfid: A Reconfigurable Fabric of Input Devices for the Internet of Things

Abstract Low-cost, easily deployable, reconfigurable, movable input devices can enable adaptive workflows in commercial, industrial, and home environments. A key limitation of previous reconfigurable control systems is their high cost or maintenance burden (e.g., battery changes or wiring setup). Our poster presents Arfid, a "fabric" for reconfigurable input devices that connects low-cost, battery-free inputs to arbitrarily specified functions in their surroundings via a buildingwide network of RFID readers. Users can reassign controllers' functions using a simple web interface

Designing specialized technology to aid assistance dogs

Interest is growing in studying canine and human relationships, especially working canines and their role in society. Interest is also growing in designing informed, user centered interactive technologies for animals. Combining these two themes, my doctoral research looks at creating user-centered, ethnographically informed designs for working animals (working dogs). The work examines existing design methodologies and posits new ones to contribute to a wider Animal-Computer Interaction (ACI) framework to design for and with animal users. Here I review the initial findings of the on-going work to develop an emergency alert alarm for assistance dog use

Augmented Reality: Hard Problems of Law and Policy

Augmented reality (AR) technologies are poised to enter the commercial mainstream. Using an interdisciplinary research team, we describe our vision of AR and explore the unique and difficult problems AR presents for law and policy—including around privacy, free speech, discrimination, and safety.https://digitalcommons.law.uw.edu/techlab/1018/thumbnail.jp

Energy advisors at work: charity work practices to support people in fuel poverty

We present an ethnographic study of energy advisors working for a charity that provides support, particularly to people in fuel poverty. Our fieldwork comprises detailed observations that reveal the collaborative, interactional work of energy advisors and clients during home visits, supplemented with interviews and a participatory design workshop with advisors. We identify opportunities for Ubicomp technologies that focus on supporting the work of the advisor, including complementing the collaborative advice giving in home visits, providing help remotely, and producing evidence in support of accounts of practices and building conditions useful for interactions with landlords, authorities and other third parties. We highlight six specific design challenges that relate the domestic fuel poverty setting to the wider Ubicomp literature. Our work echoes a shift in attention from energy use and the individual consumer, specifically to matters of advice work practices and the domestic fuel poverty setting, and to the discourse around inclusive Ubicomp technologies

Energy advisors at work: charity work practices to support people in fuel poverty

We present an ethnographic study of energy advisors working for a charity that provides support, particularly to people in fuel poverty. Our fieldwork comprises detailed observations that reveal the collaborative, interactional work of energy advisors and clients during home visits, supplemented with interviews and a participatory design workshop with advisors. We identify opportunities for Ubicomp technologies that focus on supporting the work of the advisor, including complementing the collaborative advice giving in home visits, providing help remotely, and producing evidence in support of accounts of practices and building conditions useful for interactions with landlords, authorities and other third parties. We highlight six specific design challenges that relate the domestic fuel poverty setting to the wider Ubicomp literature. Our work echoes a shift in attention from energy use and the individual consumer, specifically to matters of advice work practices and the domestic fuel poverty setting, and to the discourse around inclusive Ubicomp technologies

A review of the role of sensors in mobile context-aware recommendation systems

Recommendation systems are specialized in offering suggestions about specific items of different types (e.g., books, movies, restaurants, and hotels) that could be interesting for the user. They have attracted considerable research attention due to their benefits and also their commercial interest. Particularly, in recent years, the concept of context-aware recommendation system has appeared to emphasize the importance of considering the context of the situations in which the user is involved in order to provide more accurate recommendations. The detection of the context requires the use of sensors of different types, which measure different context variables. Despite the relevant role played by sensors in the development of context-aware recommendation systems, sensors and recommendation approaches are two fields usually studied independently. In this paper, we provide a survey on the use of sensors for recommendation systems. Our contribution can be seen from a double perspective. On the one hand, we overview existing techniques used to detect context factors that could be relevant for recommendation. On the other hand, we illustrate the interest of sensors by considering different recommendation use cases and scenarios