SCC-IRG Track 1: Smart Aging: Connecting Communities Using Low-Cost and Secure Sensing Technologies
SCC-IRG Track 1: Smart Aging: Connecting Communities Using Low-Cost and Secure Sensing Technologies
批准号:
1951880
负责人:
Fan Ye
金额:
$170.01万
依托单位:
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
项目状态:
已结题
起止时间:
2020-10-01 至 2024-09-30
中文摘要
点击翻译按钮获取中文摘要
英文摘要
The rapid growth of our aging population, nicknamed the "silver tsunami", causes both social and economic challenges. Without the appropriate tools to support independence, individuals age 65+ will overwhelm the limited resources of families, providers, and other supporting stakeholders nationwide. This project will engage diverse stakeholder groups to develop holistic technological and social solutions to address these challenges and promote the welfare, quality of life, autonomy, and dignity of older adults aging at home. The project develops technologies that can detect emergency, emergent, transitional and long-term changes in individuals’ physical, social and cognitive states at times where prevention/early intervention can have the greatest benefits. These technologies will be paired novel social approaches that foster technology adoption by diverse populations. Overall, the approach will bring effective, cost-saving solutions at scale to many communities. The team will train students for interdisciplinary careers, cultivate the next generation of technology-savvy healthcare workers, and transfer the project findings to communities across the nation.This project will: (1) engage older adults, family and non-family caregivers, supporting institutions, and professionals within Suffolk County, Long Island, New York to identify health and social challenges that aging adults face; (2) design, develop, pilot test, and evaluate robust, secure, and affordable continuous health data collection and analysis solutions to automate health change detection, classification, and prediction (e.g., disease onset/progression/resolution); (3) develop social solutions and best practices that foster greater adoption of sensing technologies, share data effectively with stakeholders, and measure social determinants of health using a quantitative, data-driven approach; and (4) co-develop and co-evaluate the technical and social solutions with diverse community stakeholders---and educate/train students, residents, and providers end-to-end for technology assisted aging in place. The results will include novel technologies targeting challenges of older adults and best social practices in technology adoption to maximize the benefits for all stakeholders.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.
期刊论文(14)
专著(0)
科研奖励(0)
会议论文
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DOI:
10.1145/3580252.3586988
发表时间:
2023-06
期刊:
2023 IEEE/ACM Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE)
影响因子:
--
作者:
[Zongxing Xie;Ava Nederlander;Isac Park;Fan Ye]
通讯作者:
Zongxing Xie;Ava Nederlander;Isac Park;Fan Ye
Poster: Quantifying Signal Quality Using Autoencoder for Robust RF-based Respiration Monitoring
海报:使用自动编码器量化信号质量以实现稳健的基于射频的呼吸监测
DOI:
--
发表时间:
2023
期刊:
Systems and Engineering Technologies
影响因子:
--
作者:
[Xie, Zongxing, Nederlander, Ava, Park, Isac, Ye, Fan]
通讯作者:
Ye, Fan
DOI:
--
发表时间:
2022
期刊:
影响因子:
--
作者:
[I. Akgun;Santiago Vargas;Michael Arkhangelskiy;Andrew Burford;Michael McNeill;A. Balasubramanian;Anshul Gandhi;E. Zadok]
通讯作者:
I. Akgun;Santiago Vargas;Michael Arkhangelskiy;Andrew Burford;Michael McNeill;A. Balasubramanian;Anshul Gandhi;E. Zadok
Poster: Towards Robust, Extensible, and Scalable Home Sensing Data Collection
海报:实现稳健、可扩展和可扩展的家庭传感数据收集
DOI:
--
发表时间:
2023
期刊:
Systems and Engineering Technologies
影响因子:
--
作者:
[Elbadry, Mohammed, Liu, Mengjing, Hua, Yindong, Xie, Zongxing, Ye, Fan]
通讯作者:
Ye, Fan
DOI:
10.1145/3568429
发表时间:
2022-11
期刊:
ACM Transactions on Storage
影响因子:
1.7
作者:
[I. Akgun;A. S. Aydin;Andrew Burford;Michael McNeill;Michael Arkhangelskiy;E. Zadok]
通讯作者:
I. Akgun;A. S. Aydin;Andrew Burford;Michael McNeill;Michael Arkhangelskiy;E. Zadok
共 14 条
Collaborative Research: PPoSS: LARGE: Principles and Infrastructure of Extreme Scale Edge Learning for Computational Screening and Surveillance for Health Care
-
批准号:2119299
-
项目类别:Continuing Grant
-
资助金额:$212.72万
-
财政年份:2021
-
负责人:Fan Ye
-
依托单位:
III: Small: Opportunistic Learning on Wheels: Peer-wise Training of Machine Learning Models among Connected Vehicles
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批准号:2007715
-
项目类别:Standard Grant
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资助金额:$49.96万
-
财政年份:2020
-
负责人:Fan Ye
-
依托单位:
Collaborative Research: PPoSS: Planning: Principles for Edge Sensing and Computing for Personalized, Precision Healthcare at National Scale
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批准号:2028952
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项目类别:Standard Grant
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资助金额:$14.92万
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财政年份:2020
-
负责人:Fan Ye
-
依托单位:
CAREER: Software Hardware Architecture Co-Design for Smart Environment Operation and Management
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批准号:1652276
-
项目类别:Continuing Grant
-
资助金额:$45.0万
-
财政年份:2017
-
负责人:Fan Ye
-
依托单位:
SHF: Small: Designing Expandable and Cost-Effective Server-Centric Interconnects for Data Centers
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批准号:1526162
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项目类别:Standard Grant
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资助金额:$46.0万
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财政年份:2015
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负责人:Fan Ye
-
依托单位:
CSR: Medium: Collaborative Research: A Data-Centric Architecture for Pervasive Edge Computing in Heterogeneous Extensible Distributed Systems
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批准号:1513719
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项目类别:Continuing Grant
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资助金额:$54.15万
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财政年份:2015
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负责人:Fan Ye
-
依托单位:
SHF: Small: Towards Cost-Efficient Guaranteed Performance Multicast in Fat-Tree Data Center Networks
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批准号:1320044
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项目类别:Standard Grant
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资助金额:$45.0万
-
财政年份:2013
-
负责人:Fan Ye
-
依托单位:
国内基金
海外基金
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