Tracking the Consumption of Home Essentials

Carolina Fuentes, Martin Porcheron, J. Fischer, Enrico Costanza, Obaid Malik, S. Ramchurn
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引用次数: 17

Abstract

Predictions of people's behaviour increasingly drive interactions with a new generation of IoT services designed to support everyday life in the home, from shopping to heating. Based on the premise that such automation is difficult due to the contingent nature of people's practices, in this work we explore the nature of these contingencies in depth. We have designed and conducted a technology probe that made use of simple linear predictions as a provocation, and invited people to track the life of their household essentials over a two-month period. Through a mixed-method approach we demonstrate the challenges of simple predictions, and in turn identify eight categories of contingencies that influenced prediction accuracy. We discuss strategies for how designers of future predictive IoT systems may take the contingencies into account by removing, hiding, revealing, managing, or exploiting the system uncertainty at the core of the issue.
跟踪家庭必需品的消费
对人们行为的预测越来越多地推动着人们与新一代物联网服务的互动,这些服务旨在支持从购物到供暖的日常家庭生活。基于这种自动化由于人们实践的偶然性而难以实现的前提,在这项工作中,我们深入探讨了这些偶然性的本质。我们设计并进行了一项技术调查,利用简单的线性预测作为一种挑衅,并邀请人们在两个月的时间里跟踪他们的家庭必需品的生活。通过混合方法,我们展示了简单预测的挑战,并反过来确定了影响预测准确性的八类偶然事件。我们讨论了未来预测性物联网系统的设计者如何通过消除、隐藏、揭示、管理或利用问题核心的系统不确定性来考虑突发事件的策略。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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