HCC-Medium: StepGreen: Mobilizing Social Networks and Context Awareness to Motivate Reduced Energy

HCC-Medium：StepGreen：调动社交网络和情境意识来激励减少能源消耗

• 批准号: 0803733
• 负责人: Jennifer Mankoff
• 金额: $ 45万
• 依托单位: Carnegie-Mellon University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-09-01 至 2012-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0803733&HistoricalAwards=false
• 关键词: HCC; Medium; StepGreen; Mobilizing; Social

In 2005, Americans consumed 100 quadrillion BTUs of energy, or almost six times the world wide average per person. Much of this energy consumption is directly related to personal, individual activities such as lighting, heating and cooling. By making simple modifications to these routine activities individuals can conserve energy and help reduce total CO2 emissions. This project leverages Internet technologies to develop a scalable approach to changing behavior regarding environmental footprint (the amount of natural resources or emissions required to support an individual or household). The intent is to use online social networks, cell phones and other technologies to provide a set of ecologically sound, context-sensitive behavioral recommendations. The ultimate goal is to achieve Internet-scale energy behavior change via behavioral research on successful ways to motivate change, environmental impact analysis, and ubiquitous computing that supports objective measurement and context-sensitive communication. The project will use the existing StepGreen.org website as a testbed for three core activities. First, controlled field studies will be conducted to examine the value of personalization and social influence on motivation to change as well as how motivational strategies can accommodate differences among ethnic and cultural groups. Second, inexpensive sensing techniques will be developed that can unobtrusively extract information about changes in daily behaviors. For example, this will be able to track home heating, cooling and transportation behavior through simple financial monitoring of transactions such as electricity bills and gasoline purchases. Finally, the StepGreen deployment, as a large-scale social intervention, must adapt flexibly to contextual information about people (e.g., favored communication modalities, appropriate timing). The multidisciplinary nature of the proposed work enables innovative changes in several scientific domains. By bringing together technical innovation and social science, the proposed work can test theories of social computing in the field, providing a detailed understanding of how online social networks in combination with behavioral intervention strategies can lead to widespread behavioral change. Simultaneously, this work will explore and innovate solutions for large-scale distributed evaluation of Ubicomp technology. By bringing together environmental science and machine learning, the investigators will create the first objective calculator of individual energy use. Finally, the research will benefit environmental decision making by identifying misconceptions about relationships between behavior and energy consumption, educating a broad populace on individual actions they can take to reduce their consumption, and, ideally, achieving reductions in U.S. energy use.Broader impacts. The proposed research will benefit education through the interdisciplinary training of graduate and undergraduate students and through high school outreach as part of Carnegie-Mellon's Green Design Apprenticeship. The work?s focus on different socioeconomic groups will help to highlight the importance of addressing cross-cultural issues in design and behavioral science. Finally, the project will benefit society by helping to address a critical social issue and by providing results that inform other domains in which societal benefits depend on individual behavior change (e.g., health, littering, community action).

2005年，美国人消耗了100亿亿元的能源，是每人平均水平的六倍。这种能源消耗的大部分与个人活动，例如照明，供暖和冷却直接相关。通过对这些常规活动进行简单修改，个人可以节省能源并帮助减少总CO2排放。该项目利用互联网技术开发一种可扩展的方法来改变环境足迹的行为（自然资源或支持个人或家庭所需的排放量）。目的是使用在线社交网络，手机和其他技术来提供一组生态良好的，上下文敏感的行为建议。最终的目标是通过对成功的方式来激励变化，环境影响分析和无处不在的计算来实现互联网规模的能量行为改变，以支持客观的测量和上下文敏感的交流。该项目将使用现有的stepgreen.org网站作为三个核心活动的测试床。首先，将进行受控的现场研究，以研究个性化和社会对变革动机的影响的价值以及动机策略如何适应种族和文化群体之间的差异。其次，将开发出廉价的传感技术，可以毫不客气地提取有关日常行为变化的信息。例如，这将能够通过简单的财务监控（例如电费和汽油购买）来跟踪家庭供暖，冷却和运输行为。最后，作为大规模社会干预的继绿色部署必须灵活地适应有关人的上下文信息（例如，有利的沟通方式，适当的时机）。拟议工作的多学科性质使几个科学领域的创新变化。通过汇集技术创新和社会科学，拟议的工作可以测试该领域的社会计算理论，从而详细了解如何结合在线社交网络与行为干预策略相结合可以导致广泛的行为改变。同时，这项工作将探索和创新解决方案，以进行大规模的Ubicomp技术分布式评估。通过汇集环境科学和机器学习，研究人员将创建个人能源使用的第一个客观计算器。最后，这项研究将通过确定对行为与能源消耗之间关系的误解，对他们可以采取的个人行为进行误解，从而使环境决策受益，并在美国能源使用量减少美国的能源降低。拟议的研究将通过对研究生和本科生的跨学科培训以及高中宣传来使教育受益，这是卡内基 - 梅隆绿色设计学徒制的一部分。这项工作的重点是不同的社会经济群体，将有助于强调解决设计和行为科学中跨文化问题的重要性。最后，该项目将通过帮助解决一个关键的社会问题，并提供有关社会利益取决于个人行为改变的其他领域的结果（例如，健康，乱扔垃圾，社区行动）来使社会受益。