SCC-IRG Track 1: Sociotechnical Systems to Enable Smart and Connected Energy-Aware Residential Communities

该项目旨在为智能和互联的住宅社区开发一种新的模式，使居民了解和减少家庭能源使用，同时提高他们的环境意识，对集体目标的响应能力，并提高他们的生活质量。该研究将导致有关个人，团体和住宅社区如何做出与家庭能源消耗相关的决策的发现。基于这些知识，该项目将开发集成到用户交互式智能设备中的反馈机制，以实现最佳的能源管理。印第安纳州住房和社区发展局、几个行业利益攸关方和各种社区行动小组将在项目的整个生命周期内参与这项工作。智能和互联（SC）技术将在多个住宅社区的数百个家庭中实施，这些家庭将被用作研究试验台，并将涵盖广泛的人口统计，位置和建筑。研究成果将被纳入教学模块，支持课程和劳动力发展，以及在工程，社会和经济科学和普渡大学理工学院的能力建设。通过社会技术研究的进步、社区参与和传播，该项目将在住房领域创建一个全国性的“SC能源意识住宅社区”模型，并通过实例将更广泛的研究社区指向增强社区功能和国家繁荣的S CC研究前沿。机器学习和机制设计的根本性进步，沿着人机交互、行为和社会科学以及建筑能源系统的综合研究，将导致挑战我们目前对个人和社区层面的行为和反馈反应的理解的发现。鉴于人口规模大，学习和社区为基础的反馈机制沿着与音频/视频终端用户系统的范围，有关使用定制的反馈和SC技术影响行为的调查结果将导致人类行为的一般原则，可以转移到能源使用以外的领域。研究人员将建立一种基于贝叶斯多尺度聚类算法和博弈论模型的新的社会技术建模方法，该方法将影响不同S CC应用领域的多个学科和研究活动，如能源，水，交通，经济发展，环境质量和城市规划。

This project aims to develop a new paradigm for smart and connected residential communities that engages inhabitants in understanding and reducing their home energy use while increasing their environmental awareness, responsiveness to collective goals, and improving their quality of life. The research will lead to discoveries concerning how individuals, groups, and residential communities make decisions related to their home energy consumption. Based on this knowledge, this project will develop feedback mechanisms integrated into user-interactive smart devices to enable optimal energy management. The Indiana Housing and Community Development Agency, several industry stakeholders and various community action groups will be engaged in this work throughout the lifetime of the project. Smart and connected (S&C) technology will be implemented in several hundred households in multiple residential communities that will be used as research test-beds and will cover a wide range of demographics, locations, and construction. The research outcomes will be integrated in teaching modules that support curriculum and workforce development as well as capacity-building in engineering, social and economic science, and polytechnic schools at Purdue. Through sociotechnical research advances, community engagement, and dissemination, this project will create a national model for "S&C energy-aware residential communities" in the housing sector, and by example point the broader research community toward S&CC research frontiers that enhance community functioning and national prosperity.Fundamental advances in machine learning and mechanism design, along with integrative research in human-machine interaction, behavioral and social sciences, and building energy systems will lead to discoveries that challenge our current understanding of behavior and response to feedback both at the individual and community-level. Given the large population size and the range of learning and community-based feedback mechanisms along with audio/visual end-user systems, the findings pertaining to the use of customized feedback and S&C technology to influence behavior will lead to general principles of human behavior that can be transferred to domains beyond energy use. The researchers will establish a new sociotechnical modeling approach based on Bayesian multi-scale clustering algorithms and game-theoretic models that will impact multiple disciplines and research activities in different S&CC application domains, such as energy, water, transportation, economic development, environmental quality, and urban planning.