Designing and Evaluating Next-Generation Thermographic Systems to Support Residential Energy Audits

Buildings account for 41% of primary energy consumption in the United States—more than any other sector—and contribute to an increasing portion of carbon dioxide emissions (33% in 1980 vs. 40% in 2009). To help address this problem, the U.S. Department of Energy recommends conducting energy audits to identify sources of inefficiencies that contribute to rising energy use. One effective technique used during energy audits is thermography. Thermographic-based energy auditing activities involve the use of thermal cameras to identify, diagnose, and document energy efficiency issues in the built environment that are visible as anomalous patterns of electromagnetic radiation. These patterns may indicate locations of air leakages, areas of missing insulation, or moisture issues in the built environment. Sensor improvements and falling costs have increased the popularity of this auditing technique, but its effectiveness is often mediated by the training and experience of the auditor. Moreover, given the increasing availability of commodity thermal cameras and the potential for pervasive thermographic scanning in the built environment, there is a surprising lack of understanding about people’s perceptions of this sensing technology and the challenges encountered by an increasingly diverse population of end-users. Finally, there are few specialized tools and methods to support the auditing activities of end-users. To help address these issues, my work focuses on three areas: (i) formative studies to understand and characterize current building thermography practices, benefits, and challenges, (ii) human-centered explorations into the role of automation and the potential of pervasive thermographic scanning in the built environment, and (iii) evaluations of novel, interactive building thermography systems. This dissertation presents a set of studies that qualitatively characterizes building thermography practitioners, explores prototypes of novel thermographic systems at varying fidelity, and synthesizes findings from several field deployments. This dissertation contributes to the fields of sustainability, computer science, and HCI through: (i) characterizations of the end-users of thermography, (ii) critical feedback on proposed automated thermographic solutions, (iii) the design and evaluation of a novel longitudinal thermography system designed to augment the data collection and analysis activities of end-users, and (iv) design recommendations for future thermographic systems

“No powers, man!”: A student perspective on designing university smart building interactions

Smart buildings offer an opportunity for better performance and enhanced experience by contextualising services and interactions to the needs and practices of occupants. Yet, this vision is limited by established approaches to building management, delivered top-down through professional facilities management teams, opening up an interaction-gap between occupants and the spaces they inhabit. To address the challenge of how smart buildings might be more inclusively managed, we present the results of a qualitative study with student occupants of a smart building, with design workshops including building walks and speculative futuring. We develop new understandings of how student occupants conceptualise and evaluate spaces as they experience them, and of how building management practices might evolve with new sociotechnical systems that better leverage occupant agency. Our findings point to important directions for HCI research in this nascent area, including the need for HBI (Human-Building Interaction) design to challenge entrenched roles in building management

Towards a Responsible Innovation Agenda for HCI

In recent years responsible innovation has gained significant traction and can be seen to adorn a myriad of research platforms, education programs, and policy frameworks. In this workshop, we invite HCI researchers to discuss the relations between the CHI community and responsible innovation. This workshop looks to build provocations and principles for and with HCI researchers who are or wish to become responsible innovators. The workshop looks to do this by asking attendees to think about the social, environmental, and economic impacts of ICT and HCI and explore how research innovation frameworks speak to responsible HCI innovation. Through the workshop we look to examine 5 questions to develop a set of provocations and principles, which will help encourage HCI and computer science researchers, educators, and innovators to reflect on the impact of their research and innovatio

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Everything in the Forest Is the Forest':A Decade of the Sustainability in (Inter)Action Forum

Design Conceptualization and Communicatio

CTArcade: learning computational thinking while training virtual characters through game play

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Just Do Something: Comparing Self-proposed and Machine-recommended Stress Interventions among Online Workers with Home Sweet Ofice

Modern stress management techniques have been shown to be efective, particularly when applied systematically and with the supervision of an instructor. However, online workers usually lack sufcient support from therapists and learning resources to selfmanage their stress. To better assist these users, we implemented a browser-based application, Home Sweet Office (HSO), to administer a set ofstress micro-interventions which mimic existing therapeutic techniques, including somatic, positive psychology, meta cognitive, and cognitive behavioral categories. In a four-week feld study, we compared random and machine-recommended interventions to interventions that were self-proposed by participants in order to investigate effective content and recommendation methods. Our primary fndings suggest that both machine-recommended and self-proposed interventions had signifcantly higher momentary efficacy than random selection, whereas machine-recommended interventions offer more activity diversity compared to self-proposed interventions. We conclude with refections on these results, discuss features and mechanisms which might improve efficacy, and suggest areas for future work.https://doi.org/10.1145/3544548.358131

Shared Autonomy to Reduce Sedentary Behavior Among Sit-Stand Desk Users in the United States and India: Web-Based Study

BackgroundFitness technologies such as wearables and sit-stand desks are increasingly being used to fight sedentary lifestyles by encouraging physical activity. However, adherence to such technologies decreases over time because of apathy and increased dismissal of behavioral nudges. ObjectiveTo address this problem, we introduced shared autonomy in the context of sit-stand desks, where user input is integrated with robot autonomy to control the desk and reduce sedentary behavior and investigated user reactions and preferences for levels of automation with a sit-stand desk. As demographics affect user acceptance of robotic technology, we also studied how perceptions of nonvolitional behavior change differ across cultures (United States and India), sex, familiarity, dispositional factors, and health priming messages. MethodsWe conducted a web-based vignette study in the United States and India where a total of 279 participants watched video vignettes of a person interacting with sit-stand desks of various levels of automation and answered questions about their perceptions of the desks such as ranking of the different levels of automation. ResultsParticipants generally preferred either manual or semiautonomous desks over the fully autonomous option (P<.001). However, participants in India were generally more amenable to the idea of nonvolitional interventions from the desk than participants in the United States (P<.001). Male participants had a stronger desire for having control over the desk than female participants (P=.01). Participants who were more familiar with sit-stand desks were more likely to adopt autonomous sit-stand desks (P=.001). No effects of health priming messages were observed. We estimated the projected health outcome by combining ranking data and hazard ratios from previous work and found that the semiautonomous desk led to the highest projected health outcome. ConclusionsThese results suggest that the shared autonomy desk is the optimal level of automation in terms of both user preferences and estimated projected health outcomes. Demographics such as culture and sex had significant effects on how receptive users were to autonomous intervention. As familiarity improves the likelihood of adoption, we propose a gradual behavior change intervention to increase acceptance and adherence, especially for populations with a high desire for control