Future Everyday Interaction with the Autonomous Internet of Things

未来与自主物联网的日常互动

• 批准号: EP/N014243/1
• 负责人: Enrico Costanza
• 金额: $ 102.73万
• 依托单位: University of Southampton
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2016
• 资助国家: 英国
• 起止时间: 2016 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FN014243%2F1
• 关键词: Future; Everyday; Interaction; Autonomous; Internet

This project seeks to investigate the design of interaction mechanisms and user interfaces for a future Autonomous Internet of Things (A-IoT): a system of interconnected devices that reaches beyond most current incarnations of the IoT to include aspects of autonomy or automation as a key feature. Nascent instantiations of the A-IoT range from smart thermostats that learn to autonomously control central heating systems based on the presence of users and their routine, to washing machines that order detergent for delivery when it runs out. In other words, this A-IoT can proactively respond to sensed environmental changes, effectively doing work on behalf of users, with the promise of a more efficient use of resources (e.g. to use less energy for heating) or increased convenience (e.g. to always have detergent available). The wealth (or "deluge") of data produced by the IoT is likely to keep growing beyond human capacity to turn it into meaningful information that can be acted on. Therefore, it will require future interactive systems to increasingly support the delegation of granular decision making over large and complex data to autonomous computational agents, allowing users to make informed choices about their general needs and comfort. In an Autonomous IoT; data and decisions will be, in part, 'actively' managed by the devices and their software, drawing upon machine learning techniques and optimization algorithms.However, recent studies examining the real-world acceptance of a commercial smart thermostat highlighted how errors, limited legibility of the system operation, and excessive user expectations caused frustration and led to some users abandoning the technology. Our own prior work revealed people distrust a potential smart energy infrastructure due to lack of accountability of the ownership, intent, and permitted activities of the autonomous technology. These results suggest that the design of A-IoT systems needs to address several challenges to be made accountable; including, on the system side, designing autonomous decision-making to take into account the uncertain nature of contingent human behaviour; and on the user side, the need to make these systems legible and usable in everyday life. Indeed there is an inherent tension between making a system's operation legible and not overwhelming users with the technical complexity of artificial intelligence algorithms. To date, the methodologies to design such systems are rather sparse and not specific to A-IoT systems (spanning HCI, AI, and Ubicomp) and hence a more focused approach is required to determine the core design principles and methods for the implementation of A-IoT systems.Our goal is thus to establish the scientific underpinnings of user interactions with A-IoT systems, in a domestic everyday context, with the aim of elucidate the following research questions: to what extent may users be willing to delegate agency to A-IoT systems in everyday contexts? How should interactions with A-IoT systems be engineered to support rather than hinder users' daily activities? What capabilities are essential for intelligent agents to manage such A-IoT systems? How can we design such systems so that they allow users to delegate control, yet easily regain it? Unless such questions are fully addressed, A-IOT systems are likely to frustrate users, resulting in significant waste of time and resources.Hence, we will address these challenges through a combination of techniques, including the study of existing practices, the iterative development of novel A-IoT prototypes and their evaluation in-the-wild. Such a multidisciplinary approach is made possible by a team that brings together internationally-leading researchers in human-computer interaction, artificial intelligence and design ethnography.

该项目旨在研究未来自主物联网 (A-IoT) 的交互机制和用户界面的设计：一个互连设备系统，超越了物联网的大多数当前版本，将自主或自动化方面作为关键特征。 A-IoT 的新兴实例包括从智能恒温器到根据用户的存在及其日常活动自动控制中央供暖系统的智能恒温器，到在洗涤剂用完时订购洗涤剂交付的洗衣机。换句话说，这种 A-IoT 可以主动响应感知到的环境变化，有效地代表用户工作，并承诺更有效地利用资源（例如，使用更少的能源用于供暖）或增加便利性（例如，始终有可用的清洁剂）。物联网产生的数据财富（或“海量”）可能会持续增长，超出人类将其转化为可采取行动的有意义信息的能力。因此，未来的交互系统将越来越多地支持将针对大型复杂数据的精细决策委托给自主计算代理，从而使用户能够根据自己的一般需求和舒适度做出明智的选择。在自主物联网中；数据和决策将部分地由设备及其软件“主动”管理，利用机器学习技术和优化算法。然而，最近的研究考察了商业智能恒温器的现实世界接受度，强调了错误、有限的易读性如何系统运行的困难，过高的用户期望导致沮丧并导致一些用户放弃该技术。我们自己之前的工作表明，由于缺乏对自主技术的所有权、意图和允许的活动的问责，人们不信任潜在的智能能源基础设施。这些结果表明，A-IoT 系统的设计需要解决几个需要承担责任的挑战；包括在系统方面，设计自主决策以考虑到人类偶然行为的不确定性；在用户方面，需要使这些系统在日常生活中清晰可用。事实上，让系统的操作清晰易读和不让用户因人工智能算法的技术复杂性而感到不知所措之间存在着内在的紧张关系。迄今为止，设计此类系统的方法相当稀疏，并且并非特定于 A-IoT 系统（涵盖 HCI、AI 和 Ubicomp），因此需要更有针对性的方法来确定实现 A-IoT 的核心设计原则和方法。 -物联网系统。因此，我们的目标是在家庭日常环境中建立用户与 A-IoT 系统交互的科学基础，旨在阐明以下研究问题：用户在多大程度上愿意将代理权委托给 A-IoT 系统-日常生活中的物联网系统上下文？应如何设计与 A-IoT 系统的交互以支持而不是阻碍用户的日常活动？智能代理管理此类 A-IoT 系统需要哪些能力？我们如何设计这样的系统，以便允许用户委派控制权，但又可以轻松地重新获得控制权？除非这些问题得到充分解决，否则A-IOT系统很可能会让用户感到沮丧，从而导致时间和资源的大量浪费。因此，我们将通过组合技术来应对这些挑战，包括对现有实践的研究、迭代开发新颖的 A-IoT 原型及其野外评估。这种多学科方法是由一个汇集了人机交互、人工智能和设计人种学领域国际领先研究人员的团队实现的。

项目成果

Understanding the Shared Experience of Runners and Spectators in Long-Distance Running Events

了解长跑赛事中跑者和观众的共同经历

• DOI: http://dx.10.1145/3290605.3300691
• 发表时间: 2019
• 作者: Bi T

Poster: An Exploration Into Tracking the Use of Consumer Goods with RFID

海报：利用 RFID 追踪消费品使用情况的探索

• DOI: http://dx.10.1145/3494322.3494344
• 发表时间: 2021
• 作者: Berumen G

On the distinctiveness of the electricity load profile

论电力负荷曲线的特殊性

• DOI: http://dx.10.1016/j.patcog.2017.09.039
• 发表时间: 2018
• 期刊: Pattern Recognition
• 影响因子: 8
• 作者: Bicego M

"I can't get round" Recruiting Assistance in Mobile Robotic Telepresence

“我绕不过去”移动机器人远程呈现招聘协助

• DOI: http://dx.10.1145/3432947
• 发表时间: 2021
• 期刊: Proceedings of the ACM on Human-Computer Interaction
• 作者: Boudouraki A

Evaluating Saliency Map Explanations for Convolutional Neural Networks: A User Study

评估卷积神经网络的显着图解释：用户研究

• DOI: http://dx.10.48550/arxiv.2002.00772
• 发表时间: 2020
• 作者: Alqaraawi A