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EAGER: Collaborative Research: Modernizing Cities via Smart Garden Alleys with Application in Makassar City

EAGER: Collaborative Research: Modernizing Cities via Smart Garden Alleys with Application in Makassar City
EAGER:合作研究:通过智能花园巷实现城市现代化并在望加锡市应用
批准号:
2025377
负责人:
Walid Saad
金额:
$7.5万
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:
2020-07-15 至 2023-06-30

项目摘要

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中文摘要
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英文摘要
This activity is in response to the NSF Dear Colleague Letter: Supporting Transition of Research into Cities through the US ASEAN (Association of Southeast Asian Nations Cities) Smart Cities Partnership (NSF 20-024), in collaboration with the US Department of State. This research seeks to integrate innovations in smart and connected communities with creative gardens within the city alleys of Makassar City, Indonesia via a synergistic collaboration between US and Indonesian teams and a close partnership with Makassar City. Makassar is striving to become a livable world class city for a fast-growing, diverse population of 1.7 million people. The ongoing “Garden Alley” project in the city aims to improve the “livability” of the city, measured by factors including air-quality, heat index, food security, and social interactions. To date, Makassar has implemented 40 gardens within 15 of the city’s sub-districts, covering a sizable portion of the city’s alleys. The goal of this research is to catalyze the transformation of Makassar City’s garden alleys into smart environments by deploying a sensor network at representative green allies and conventional allies to collect data related to air quality, microclimates, and other factors, to analyze the heterogeneous data using machine learning techniques, and to then share the data and its insights with city representatives and specific communities within the city.This transformative research will provide the foundational science and knowledge that are needed to design, optimize, and deploy S&CC technologies within the ASEAN region and beyond. This interdisciplinary research will yield several major innovations: 1) New low-cost, durable, and mobile sensor networks will be designed for air quality and microclimate monitoring in the hot and humid climate in southeast Asian cities. 2) Suitable machine learning techniques will be employed to exploit the multi-dimensional and heterogeneous data collected from both existing infrastructures and new mobile test platforms in Makassar and create intelligent spatio-temporal operational maps of Makassar’s alleys that can be used for various design, planning, and operational decisions by the city. 3) Data-driven city-scale smart operating schemes involving feedback loops will be explored through close engagement with the Indonesian partners. The developed solutions will be highly dynamic yet robust and have the potential to be scaled, as well as transferred to other cities. Additionally, this project will initiate a new collaboration between the US and Indonesia, improving the quality of life in an emerging southeast Asian city, but with potentially broad applicability, and provide a broad range of dissemination activities, involvement of students in international activities, as well as active engagement with local communities and researchers in Indonesia.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(3)
专著(0)
科研奖励(0)
会议论文
DOI: 10.1109/tits.2021.3084907
发表时间: 2020-05
期刊: IEEE Transactions on Intelligent Transportation Systems
影响因子: 8.5
作者: [Zineb Mahrez;Essaid Sabir;E. Badidi;W. Saad;M. Sadik]
通讯作者: Zineb Mahrez;Essaid Sabir;E. Badidi;W. Saad;M. Sadik
A Transdisciplinary Blueprint for Energy Markets Modelled after Mycorrhizal Networks
以菌根网络为模型的能源市场跨学科蓝图
DOI: 10.22545/2023/00226
发表时间: 2022
期刊: Transdisciplinary Journal of Engineering & Science
影响因子: --
作者: [Gould, Zachary, Day, Susan, Reichard, Georg, Shealy, Tripp, Saad, Walid]
通讯作者: Saad, Walid
DOI: 10.3390/en16104081
发表时间: 2023-05
期刊: Energies
影响因子: 3.2
作者: [Z. Gould;V. Mohanty;Georg Reichard;Walid Saad;Tripp Shealy;Susan G. Day]
通讯作者: Z. Gould;V. Mohanty;Georg Reichard;Walid Saad;Tripp Shealy;Susan G. Day
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Collaborative Research: CNS Core: Small: Hierarchical Federated Learning Over Wireless Edge Networks: Performance Analysis and Optimization
SII Planning: ARIES: Center for Agile, RelIablE, Scalable Spectrum
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