SCC-IRG Track 2: Smart Air: Informing Driver Behavior through Dynamic Sensing and Smart Messaging

SCC-IRG 轨道 2：智能空气：通过动态传感和智能消息传递告知驾驶员行为

• 批准号: 1952008
• 负责人: Kerry Kelly
• 金额: $ 120万
• 依托单位: University of Utah
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-10-01 至 2025-09-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1952008&HistoricalAwards=false
• 关键词: SCC; IRG; Track; Smart; Air

High concentrations of energy use from fossil fuels can lead to poor air quality, resulting in adverse health effects as well as economic consequences. A prime example is found where large numbers of idling vehicles congregate (e.g., schools and hospital drop-off/pick-up zones), leading to microclimates of unhealthy air. Workers, such as valet parking attendants, can spend their entire workday in these microenvironments, and children passing through these zones can experience up to 60% higher levels of pollution than adults, because of their height. These vehicle-caused, poor-air-quality microclimates offer a compelling opportunity for communities to engage with emerging technologies to take ownership of their air and the behaviors that impact its quality. This project sociotechnical approach, called SmartAir, will synergistically integrate dynamic air-quality information with social-norm feedback to positively influence decisions that affect the well-being of vulnerable individuals working in or passing through polluted microenvironments. The feedback approach for decreasing idling mirrors the feedback provided by digital speed displays, which has been shown to positively influence driver behavior (reduced speeding) and thus reduce health-impacts of that behavior (reduced traffic accidents). The proposed pilot demonstrations will take place in Northern Utah, a region that periodically experiences the poorest air quality in the country. The project SmartAir employs a comprehensive community engagement approach — from the development of the sensing and display technologies to cocreation of culturally sensitive messaging, cooperatively conducted pilot studies, and efficacy evaluation.SmartAir will produce novel technological and behavioral-science developments. First, this project will develop wearable, calibrated, low-cost air quality sensing nodes that will support members of smart and connected communities to minimize pollution exposure. Second, this project will enable the rapid integration of sensor measurements with local meteorological information and data-screening algorithms to dynamically provide feedback to individuals about idling behavior and to workers that seek to minimize pollution exposure. Third, the SmartAir system will be integrated into behavior-change experiments and the co-creation of community-crafted messaging to influence individual choices. Comprehensive involvement of the community partners will be critical to co-develop and pilot solutions to address poor air quality and ultimately ensure a highly scalable and sustainable system. The broader impacts of this work are multifold, including the following. SmartAir will serve as a framework for closing the loop between air quality measurements and individual decision making. It will also help drive institutional decisions that reduce worker pollutant exposure and improve worker performance, career longevity, and job satisfaction. Anonymized data will be made available to support numerous personal and community-driven needs, such as health-effects studies, anti-idling campaigns, school drop-off policies, and urban/traffic planning. Additionally, this project will have a substantial outreach effort that involves community members in message crafting, data collection, and interpretation.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

大量闲置车辆聚集的地方（例如学校和医院接送/接送）就是一个典型的例子。工作人员（例如代客泊车服务员）可能会在这些微环境中度过整个工作日，而经过这些区域的儿童所经历的污染程度可能比成人高出 60%。这些由车辆造成的空气质量不佳的小气候为社区提供了一个绝佳的机会，让他们能够与新兴技术相结合，以掌控自己的空气以及影响空气质量的行为。这个项目的社会技术方法（称为 SmartAir）将协同动态。空气质量信息与社会规范反馈可以对影响在受污染的微环境中工作或经过的弱势个体的福祉产生积极影响的决策减少空转的反馈方法反映了数字速度显示器提供的反馈。研究表明，该项目能够对驾驶员行为产生积极影响（减少超速行驶），从而减少该行为对健康的影响（减少交通事故）。 SmartAir 采用全面的社区参与方法——从传感和显示技术的开发到文化敏感信息的共同创造、合作进行的试点研究和功效评估。SmartAir 将产生新颖的技术和行为科学发展。可穿戴、校准、低成本空气质量传感节点，将支持智能互联社区成员最大限度地减少污染暴露。其次，该项目将使传感器测量与当地气象信息和数据筛选算法快速集成，以动态提供反馈。第三，SmartAir 系统将被纳入行为改变实验中，并共同创建社区精心设计的信息，以影响个人的选择。对共同开发和试点解决方案，以解决空气质量问题，并最终确保建立一个高度可扩展和可持续的系统。SmartAir 将作为空气质量测量和个人之间闭环的框架。它还将有助于推动减少工人污染物暴露并提高工人绩效、职业寿命和工作满意度的机构决策。将提供匿名数据来支持众多个人和社区驱动的需求，例如健康影响研究、反空转运动、学校此外，该项目还将开展大量的外展工作，让社区成员参与信息制作、数据收集和解释。该奖项反映了 NSF 的法定使命，并通过评估被认为值得支持。利用基金会的智力优势和更广泛的影响审查标准。

项目成果

Technical note: Identifying a performance change in the Plantower PMS 5003 particulate matter sensor

技术说明：识别 Plantower PMS 5003 颗粒物传感器的性能变化

• DOI: 10.1016/j.jaerosci.2023.106256
• 发表时间: 2023
• 期刊: Journal of Aerosol Science
• 影响因子: 4.5
• 作者: Searle, N.;Kaur, K.;Kelly, K.
• 通讯作者: Kelly, K.