CAREER: Scalable Sensor Infrastructure for Sustainably Managing the Built Environment
CAREER: Scalable Sensor Infrastructure for Sustainably Managing the Built Environment
批准号:
1824277
负责人:
Prabal Dutta
金额:
$21.82万
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2017
资助国家:
美国
项目状态:
已结题
起止时间:
2017-01-01 至 2020-01-31
中文摘要
美国的经济增长、能源安全和环境管理取决于可持续能源政策,该政策促进所有主要部门的节能、效率和电气化。建筑是最大的部门,因此是这些努力的一个有吸引力的目标:目前的联邦可持续发展目标要求到2050年,50%的美国商业建筑成为净零能源。实现这一目标有一系列的选择,但财务问题需要一个数据驱动的,经过验证的方法。然而,在能源和水测量技术以及室内气候控制科学方面存在着关键的差距,需要对竞争选项进行基准测试,优先考虑效率投资,并确保居住者的舒适度。为了应对这些挑战,该项目提出了一种新型的“剥离-粘贴”传感器,可以贴在日常物品上,以推断它们对整个建筑资源消耗的贡献。要使用传感器,住户或建筑管理人员只需标记终端负载,如天花板灯,淋浴喷头或范围顶部。传感器监测负载周围的环境条件,并使用统计方法将这些条件与现有电表、燃气表或水表的读数相关联,从而提供单独的估计值,而无需进行侵入式计量。这些传感器是由集成电路技术层压到智能标签中制成的,因此它们体积小,价格便宜,易于部署。传感器由它们感测到的相同环境信号供电,无需定期更换电池或墙壁电源。总的来说,这些特性解决了成本和覆盖范围的挑战,并实现了可扩展的部署和广泛采用。(和其他资源)通常发射能量,通常在不同的域中,并且这种发射的能量通常足以间歇地为简单的,能量收集传感器,其占空比与被传输或使用的能量成比例。因此,仅仅是传感器的激活率就可以发出潜在的能量使用信号。当与最先进的毫米级纳米功率芯片和全屋或面板级仪表相结合时,使用活动和侧信道收集之间的功率比例关系使得能够实现小型且廉价的传感器标签,这些标签以无限的寿命广泛分布。但是,将它们联网和分配任务,并理解它们的数据,需要从根本上重新思考低功耗通信、控制和数据融合,将间歇性、不可靠和嘈杂的传感器基础设施抽象为可操作的信息。该项目的更广泛影响源于一个集教育、研究、和推广,(i)创建一个智能对象为重点的课程,其课堂项目是由研究需求的动机,(ii)为本科生和代表性不足的少数民族提供研究经验,(iii)指导学生从阐明假设到同行评审论文的成功研究的各个方面,(iv)传播嵌入式系统和研究教学法的教学材料,(v)培养跨学科的学生,在测量科学,信息技术和可持续性政策的交叉点上运作,以及(vi)通过行业外展和实习,将科学发现和技术知识转化为有益的商业产品,及(vii)与国家实验室合作,以确保研究解决紧迫的问题。该奖项反映了NSF的法定使命,并被认为值得支持通过使用基金会的知识价值和更广泛的影响审查标准进行评估。
英文摘要
U.S. economic growth, energy security, and environmental stewardship depend on a sustainable energy policy that promotes conservation,efficiency, and electrification across all major sectors. Buildings are the largest sector and therefore an attractive target of these efforts: current Federal sustainability goals mandate that 50% of U.S.commercial buildings become net-zero energy by 2050. A range of options exists to achieve this goal, but financial concerns require a data-driven, empirically-validated approach. However, critical gaps exist in the energy and water measurement technology, and indoorclimate control science, needed to benchmark competing options, prioritize efficiency investments, and ensure occupant comfort.To address these challenges, this project proposes a new kind of "peel-and-stick" sensor that can be affixed to everyday objects to infer their contributions to whole-building resource consumption. To use the sensors, occupants or building managers simply tag end loads like a ceiling light, shower head, or range top. The sensors monitor the ambient conditions around a load and, using statistical methods,correlate those conditions with readings from existing electricity, gas, or water meters, providing individual estimates without intrusive metering. The sensors are built from integrated circuit technology laminated into smart labels, so they are small, inexpensive, and easy-to-deploy. The sensors are powered by the same ambient signals they sense, eliminating the need for periodic battery replacement or wall power. Collectively, these properties address cost and coverage challenges, and enable scalable deployment and widespread adoption.The intellectual merit of this proposal stems from the insight that the transfer and use of energy (and other resources) usually emits energy, often in a different domain, and that this emitted energy is often enough to intermittently power simple, energy-harvesting sensors whose duty cycle is proportional to the energy being transferred or used. Hence, the mere activation rate of the sensors signalsthe underlying energy use. The power-proportional relationship between usage activity and side channel harvesting, when coupled with state-of-the art, millimeter-scale, nano-power chips and whole-house or panel-level meters, enables small and inexpensive sensor tags that are pervasively distributed with unbounded lifetimes. But, networking and tasking them, and making sense of their data, requires a fundamental rethinking of low-power communications, control, and data fusion to abstract the intermittent, unreliable, and noisy sensor infrastructure into actionable information.This project's broader impact stems from an integrated program of education, research, and outreach that (i) creates a smart objects focused curriculum whose classroom projects are motivated by research needs, (ii) provides research experiences for undergraduates andunderrepresented minorities, (iii) mentors students on all aspects of successful research from articulating hypotheses to peer-reviewing papers,(iv) disseminates teaching materials on embedded systems and research pedagogy, (v) produces students who bridge disciplines,operating at the intersection of measurement science, information technology, and sustainability policy, and (vi) translates scientific discovery and technical knowledge into beneficial commercial products through industry outreach and internships, and (vii) engages with the National Labs to ensure that the research addresses pressing problems.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.
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会议论文
Synergy: Collaborative: CPS-Security: End-to-End Security for the Internet of Things
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批准号:1822332
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项目类别:Continuing Grant
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资助金额:$19.36万
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财政年份:2017
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负责人:Prabal Dutta
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依托单位:
Synergy: Collaborative: CPS-Security: End-to-End Security for the Internet of Things
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批准号:1505684
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项目类别:Continuing Grant
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资助金额:$37.5万
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财政年份:2015
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负责人:Prabal Dutta
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依托单位:
CAREER: Scalable Sensor Infrastructure for Sustainably Managing the Built Environment
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批准号:1350967
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项目类别:Continuing Grant
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资助金额:$45.2万
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财政年份:2014
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负责人:Prabal Dutta
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依托单位:
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批准号:1239031
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项目类别:Standard Grant
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资助金额:$30.0万
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负责人:Prabal Dutta
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依托单位:
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批准号:0964120
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项目类别:Continuing Grant
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资助金额:$31.5万
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财政年份:2010
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负责人:Prabal Dutta
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依托单位:
国内基金
海外基金
Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis
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项目类别:合作创新研究团队
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资助金额:--
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批准年份:2024
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负责人:姚韬
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依托单位: