A wide variety of simple sensors, e.g. for temperature, light, or humidity, is finding its way into smart homes. There are special features to consider with regard to the data collected by these sensors: a) the nature of the measured data as "thin but big data" that needs to be contextualized and interpreted, b) which both algorithms and humans are capable of doing (resulting in comprehensive information in the context of the home, including the recognition of activities, behavior, and health of the residents), and c) uses that lead to interesting positive applications, but also to misuse and implications for privacy. When managing such data, it is necessary to take these special features into account, for which the principles of user experience, human-data interaction, and data protection should be considered together. We present our research tool "Sensorkit" and the participatory research approach used with it to collect sensor data in real homes. In our findings, we present identified challenges and explain how we address them through a) meaningful default settings, b) opportunities for users to interact and intervene, and c) life-cycle management of the data. Important aspects include phases before, during, and after the collection, processing, and use of the sensor data, as well as the provision of user-friendly tools and user involvement. Our findings inform beyond the scope of a research project also the development and use of commercial smart home devices and services.
翻译:各类简易传感器(如温度、光照或湿度传感器)正广泛应用于智能家居。针对这些传感器所采集的数据,需考虑以下特性:a) 测量数据的本质属于'稀疏但海量数据',需进行情境化解读;b) 算法与人类均具备处理能力(从而在家庭环境中形成涵盖居民活动、行为与健康识别的综合信息);c) 其应用既可催生积极用例,亦可能引发隐私滥用与伦理问题。管理此类数据时,必须兼顾这些特性,并综合用户体验、人机数据交互及数据保护原则。本文介绍研究工具'Sensorkit'及其采用的参与式研究方法,用于真实家居环境中的传感器数据采集。研究成果揭示了若干挑战,并通过以下方式应对:a) 设计具有实际意义的默认设置;b) 为用户提供交互与干预机制;c) 实施数据全生命周期管理。关键环节涵盖传感器数据采集、处理与使用的前中后各阶段,同时需配备用户友好工具并保障用户参与。本研究成果不仅适用于科研项目,亦对商用智能家居设备与服务的开发应用具有指导意义。