CI-ADDO-EN: Smart Home in a Box: Creating a Large Scale, Long Term Repository for Smart Environment Technologies

目前人们对开发智能环境技术有相当大的兴趣。这些努力对不同学科的研究提出了挑战，并整合了来自不同学科的研究成果，包括人工智能、普适计算、机器人、接口、中间件和传感器网络。缺乏来自智能环境的大规模可共享数据集是这一领域快速发展的主要绊脚石。在此背景下，该项目旨在开发和部署智能环境研究社区所需的数据和工具库。该基础设施项目的预期结果包括1)简化的、自制的智能家居套件，2)用于上传、访问和注释智能环境数据的Web界面，3)包括功能评估分数和能源使用情况的元数据，以及4)用于识别、可视化和分析基于家庭的行为的软件工具。调查人员的目标是使用诸如利用储存库的研究人员的数量和多样性、对储存库、与储存库相关的研究、教育和商业进展做出贡献的数据集和工具的数量以及对储存库的出版引用等措施来评估所产生的储存库(CAAS)的影响。该项目的广泛影响包括(I)DIY智能家居工具包、数据集和软件工具，使大量研究人员能够在人工智能、普及计算、机器人、接口、中间件和传感器网络方面的研究和教育工作；(Ii)增加认知心理学、老年学和社会学的研究人员为智能环境中的跨学科研究作出贡献的机会；以及(Iii)为来自代表性不足群体的学生提供更多以研究为基础的培训机会。这项工作产生的数据集、软件工具和教育材料将作为CAAS储存库的一部分在http://ailab.wsu.edu/casas/.上提供

There is considerable current interest in developing smart environment technologies. Such efforts present research challenges in, and integration of research outcomes from, diverse disciplines including artificial intelligence, pervasive computing, robotics, interfaces, middleware, and sensor networks. The lack of availability of large-scale sharable data sets from smart environments is a major stumbling block for rapid advances in this area. Against this background, this project aims to develop and deploy a data and tool repository needed by the smart environment research community.The anticipated results of this infrastructure project include 1) a streamlined, do-it-yourself smart home kit, 2) a web interface to upload, access, and annotate smart environment data, 3) meta data including functional assessment scores and energy usage, and 4) software tools to recognize, visualize, and analyze home-based behaviors. The investigators aim to assess the impact of the resulting repository (CASAS) using measures such as number and diversity of researchers utilizing the repository, number of datasets and tools contributed to the repository, research, education, and commercial advances related to the repository, and publication citations to the repository.Broader impacts of the project include (i) the do-it-yourself smart home toolkit, data sets and software tools that enable research and educational efforts by a large community of researchers in artificial intelligence, pervasive computing, robotics, interfaces, middleware, and sensor networks; (ii) enhanced opportunities for researchers in cognitive psychology, gerontology, and sociology to contribute to interdisciplinary research in smart environments; and (iii) enhanced research-based training opportunities for students from underrepresented groups. The datasets, software tools and educational materials that result from this work will be made available as part of the CASAS repository at http://ailab.wsu.edu/casas/.