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: Virginia Polytechnic Institute and State University
• 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: 2020-07-15 至 2023-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2025377&HistoricalAwards=false
• 关键词: EAGER; Collaborative; Research; Modernizing; Cities

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.

这项活动是为了响应 NSF 亲爱同事的信：与美国国务院研究合作，通过美国东盟（东南亚国家城市联盟）智慧城市伙伴关系支持研究向城市的转变（NSF 20-024）。寻求通过美国和印度尼西亚团队之间的协同合作以及与望加锡市的密切合作，将智能互联社区的创新与印度尼西亚望加锡市城市小巷内的创意花园相结合。望加锡正在努力成为一个适合 170 万快速增长的多元化人口的宜居世界级城市，该市正在进行的“花园巷”项目旨在提高城市的“宜居性”，衡量指标包括空气质量。迄今为止，望加锡已在该市 15 个分区内建设了 40 个花园，覆盖了该市相当大的一部分地区。这项研究的目标是通过在代表性绿色盟友和传统盟友部署传感器网络来收集与空气质量、微气候和其他因素相关的数据，以分析异质性，从而促进望加锡市花园小巷向智能环境的转变。使用机器学习技术获取数据，然后与城市代表和城市内的特定社区分享数据及其见解。这项变革性研究将提供设计、优化和部署 S&CC 技术所需的基础科学和知识这项跨学科研究将产生几项重大创新：1) 将设计新型低成本、耐用的移动传感器网络，用于东南亚城市炎热潮湿气候下的空气质量和微气候监测2。 ）将采用适当的机器学习技术来利用从望加锡现有基础设施和新移动测试平台收集的多维和异构数据，并创建望加锡小巷的智能时空操作地图。 3) 将通过与印度尼西亚合作伙伴的密切合作，探索涉及反馈循环的数据驱动的城市规模智能运营方案。此外，该项目将启动美国和印度尼西亚之间的新合作，改善新兴东南亚城市的生活质量，但具有广泛的适用性，并提供广泛的传播活动，学生的参与该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

Smart Urban Mobility: When Mobility Systems Meet Smart Data

• 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

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
• 作者: Gould, Zachary;Day, Susan;Reichard, Georg;Shealy, Tripp;Saad, Walid
• 通讯作者: Saad, Walid

A Mycorrhizal Model for Transactive Solar Energy Markets with Battery Storage

• 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