The spread of COVID-19 has broad implications both for human health and economies around the world. This Smart and Connected Communities project will monitor the spread of COVID-19 by collecting real-time information on active COVID-19 cases, understand how transportation has driven the spread of the virus, and quantify how travel restrictions have limited the spread of the virus. The data collection will gather and store real-time information on the spread of COVID-19 and a timeline of travel restrictions for three sets of communities. This data will then be employed to model how the virus propagates between communities via transportation using various network-dependent epidemic models. Finally, using the collected data and the calibrated epidemic models, analysis will be conducted to understand how effective the different modifications of the transportation network structure, such as travel restrictions in each set of communities, are at slowing the spread of COVID-19, while factoring in the economic effects. Understanding how the transportation network between communities acts as a propagator of the virus, and how control actions taken by local and national governments to limit or block travel within and between regions slow the spread of the virus will provide the framework for the development of mitigation strategies for the COVID-19 pandemic, as well as other possible outbreaks in the future. These strategies will limit the loss of human life and reduce the economic impacts of the virus. The methods developed as a result of this work will also be beneficial in the future for battling subsequent outbreaks.

This project will apply network modeling techniques to understand how different control actions on the transportation network influence the spread of the virus between communities. The understanding gained herein will inform decision makers during this and future outbreaks as to which transportation-related mitigation strategies are best to use in different situations and at what point in the outbreak to use them in order to minimize both the spread of virus as well as the economic impact. The research will draw on and contribute to wide-ranging and fundamental results in statistical data analysis, mathematical modeling and analysis of epidemic processes, mathematical programming, network analysis, and control theory. The resulting study of problems will contribute to advancement of mathematical modeling and analysis of infectious diseases, and mitigation optimization algorithms and heuristics.
 

The vision of a smart city is underpinned by its ability to collect, manage, and use data. However, data access remains a fundamental challenge across city agencies, public institutions, and community stakeholders. This project is championing a paradigm shift in data sharing by implementing a new data access framework that allows users to share access to data in-situ instead of sending copies of data around. This project builds on the new data access paradigm to deploy a city Data Access Network (City-DAN) to support city managers get timely access to important data for fast decision and response. City-DAN is piloted first in Ho Chi Minh City, Vietnam and then scaled to other ASEAN cities. This activity is in response to NSF Dear Colleague Letter Supporting Transition of Research into Cities through the US ASEAN ((Association of Southeast Asian Nations Cities) Smart Cities Partnership in collaboration with NSF and the US State Department. The research team (University of Virginia) is working closely with stakeholders in Ho Chi Minh City including city managers, departments, and community organizers as well as Vietnam National University – International University to transition technology into practice.

The proposed distributed, peer-to-peer data access framework represents an ambitious vision of the next generation data ecosystem. This project establishes a foundational data platform to underpin smart cities by addressing issues of data integrity, provenance, control, and timely access. This project takes advantage of the unique deployment opportunity to pursue a vibrant research agenda on grid computing. Specific research areas include advanced cyber infrastructure, cybersecurity, networking, and persistent identifiers. This project will especially focus on identity and access management (IAM) in the context of unreliable infrastructure and weak level-of-assurance (identify proofing) baselines. The project will examine new approaches for enhancing reliability while balancing with transparency and QoS. Lessons learned also can be adopted to advance the smart and connected community research community in the US and other countries.
 

This activity is in response to NSF Dear Colleague Letter Supporting Transition of Research into Cities through the US ASEAN (Association of Southeast Asian Nations Cities) Smart Cities Partnership in collaboration with NSF and the US State Department. Ho Chi Minh City (HCMC), an ASEAN city in Vietnam, is well-known for its traffic congestion and high density of vehicles, cars, buses, trucks, and a swarm of motorbikes (7.3 million motorbikes for more than 8.4 million residents) that overwhelm city streets. Large-scale development projects have exacerbated urban conditions, making traffic congestion more severe. Additionally, traffic congestion is one of the leading contributors to noise and dust pollution in the city. Altogether, traffic congestion poses major barriers to urban quality of life, but the solutions are complex. There are two main problems with traffic in HCMC. First, HCMC, like other dense urban areas, needs significant financial and technical resources to solve its traffic and infrastructure problems. Second, given that traffic monitoring is carried out by a limited number of staff who watch traffic activities from thousands of camera feeds on multiple screens, there are limits to the number and effectiveness of responses that personnel are able to offer in response to real-time traffic problems.

The goal of this project is to use visual crowd AI sensing for the HCMC planning simulator. The project will make use of the city camera system (crowd-AI sensing) for traffic analysis in real-time. It seeks to detect “anomaly events” such as traffic violations, traffic jams, and accidents, with reduced intervention from monitoring staff, allowing staff, in turn, to better respond to traffic problems as they arise. A city planning simulator will be developed upon the analyzed traffic data. The simulator will be used to support metropolitan transportation planning. Project findings will not only address specific urban challenges and the innovative technical solutions needed to solve them in HCMC, but also will provide models use in other contexts, including U.S. cities where traffic, congestion, and urban infrastructure challenges can benefit from AI.

The project will be validated by professionals in HCMC who can evaluate its effectiveness for detecting anomaly events with reduced human observation, who are better able to respond to traffic problems as a result of implementing aspects of the project, and who can make use of the project data for traffic analysis.
 

This project responds to COVID-19 by investigating an effective and efficient community-based approach in Baltimore City, Maryland to deploying free, broadband Internet and creating trusted open-access online education, career, and communication resources for low-income populations in the face of large-scale emergencies. This approach builds on existing research on the importance of equitable broadband Internet access and the potential of community-based solutions to bridging the digital divide. Project findings will inform the creation and use of community-led approaches to meet the technical and informational needs of vulnerable populations during and immediately following times of crisis. Specifically, it will research the creation of a trusted technical infrastructure that leverages local partnerships to provide free or low-cost Internet to communities. It will also inform how to maximize the potential of Internet connectivity to maintain continuity of education and employment activities and reduce social isolation among low-income populations.

This project will create a Community Wireless Networks (CWNs) through the deployment in Baltimore City, Maryland of a series of Point-to-Point (PtP) and Point-to-Multipoint (PtMP) connections over the 5GHz spectrum. These Multiple-Input Multiple-Output (MIMO) radios mounted on Points of Presence (PoP) at partner sites will provide free and secure, high throughput links to families in need. As this access is created, the project will then curate and provide support resources to facilitate the continuity of education, the expansion of teleworking career opportunities, and virtual socialization methods. The impact of these interventions will be studied through pre- and post-intervention surveys as well as remote interviews with stakeholders to evaluate the impact of having free high-bandwidth Internet on low-income families’ access to online educational, employment, and social resources both during and after the COVID-19 pandemic. Additionally, at the conclusion of the project participating families and community partners will offer reflections and suggestions for the future implementation of similar projects in a community focus group. Project findings seek to further inform how to meet the informational needs of vulnerable populations using a grass-roots, community-based, technology-access approach during and immediately following times of crisis. This project is highly relevant to Smart and Connected Communities program as it demonstrates tight integration of social and technology research and strong community engagement will be able to have significant impact improving quality of life in vulnerable communities in this and potentially other crises.
 

The COVID-19 pandemic has not only disrupted the lives of millions but also created exigent operational and scheduling challenges for public transit agencies. Agencies are struggling to maintain transit accessibility with reduced resources, changing ridership patterns, vehicle capacity constraints due to social distancing, and reduced services due to driver unavailability. A number of transit agencies have also begun to help the local food banks deliver food to shelters, which further strains the available resources if not planned optimally. At the same time, the lack of situational information is creating a challenge for riders who need to understand what seating is available on the vehicles to ensure sufficient distancing. In partnership with the transit agencies of Chattanooga, TN, and Nashville, TN, the proposed research will rapidly develop integrated transit operational optimization algorithms, which will provide proactive scheduling and allocation of vehicles to transit and cargo trips, considering exigent vehicle maintenance requirements (i.e., disinfection). A key component of the research is the design of privacy-preserving camera-based ridership detection methods that can help provide commuters with real-time information on available seats considering social-distancing constraints. The datasets and algorithms developed through this program will be swiftly released to the research community in order to encourage a wider collaborative effort that will help other transit agencies that face similar challenges.

The intellectual merit of the proposed research lies in the design and evaluation of integrated operational optimization for both fixed-line and on-demand transit (including paratransit) under atypical capacity constraints, which requires maximizing transit access but minimizing contact. The challenge for optimization is the uncertainties that arise due to the atypical travel time and travel demand distribution, both of which need to be learned online again due to the changed scenarios. While it is possible to optimize these transit modes separately as prior work has done, integrated optimization can lead to significantly better results. However, this is difficult as the solution space of these problems is very large. The approach is based on rapidly composing and comparing the effectiveness of principled decision-theoretic approaches such as Monte Carlo tree search, optimal trip assignments using integer programming and problem-specific heuristics, and demand aggregation for on-demand transit. To develop a model for varying travel demand, the research uses novel neural network architectures to estimate usage and seating patterns in real-time from cameras that are already installed within transit vehicles. This will enable transit agencies to obtain travel demand even when they are running fare-free operations to minimize contact with drivers. Working with partner transit agencies, the researchers will be able to make the services more accessible for the community during these challenging times. This project directly relates to Smart and Connected Communities program as it demonstrates the importance of integration of technical and social research with strong community engagement in improving resilience of transit systems due to pandemics and other crises.
 

Early evidence suggests that the COVID-19 crisis is accelerating the rate of adoption of e-commerce with more people ordering online and using delivery services to meet their needs. The embrace of e-commerce and delivery during the crisis and recovery are likely uneven, as opportunities and barriers to accessing transportation, local retailers, online technologies, and delivery services vary across the population. This study will collect critical and time-sensitive information to evaluate the extent to which people modify their shopping behavior during the pandemic and the lasting effects of technological adoption during recovery and beyond. It will reveal important trends in consumer behaviors and gaps in access that can aid planners in preparation for ongoing recovery and future emergencies. Findings will promote the health and well-being of the community by identifying opportunities to meet household needs while minimizing risk.

Using a representative sampling frame for three states, this project will survey consumers in a repeated cross-sectional online survey over the next year to understand how their shopping strategies have changed, their use of online retailing and delivery services, and their challenges in accessing food and household goods. This project will also collaborate with delivery platform firms with the goal of being able to marry trend data and information about the demand for their services before the crisis, during it, and in the recovery phase. Together, these novel and timely data will be used to examine trends in online and in-store household provisioning, identify barriers to shopping, and develop models of technology adoption. This project is highly relevant to the Smart and Connected Communities program at NSF as it explores the impact of shocks such as pandemics on communities and strongly integrates technical and social dimensions. Research results from this proposal will help better inform communities of behavioral changes in crises and potentially develop resilient controls.
 

Situated on opposite sides of the Pacific Ocean, the US Pacific Northwest Region and Japan face significant earthquake risks from similar geophysical conditions. The Pacific Northwest is considered overdue for a Cascadia Subduction Zone 8.0–9.2 magnitude megaquake. When it happens, the estimated direct fatalities for Oregon and Washington states are up to 10,000, with economic losses of more than $80 billion. For the comparably sized region of Japan facing a Nankai megathrust earthquake, estimated fatalities are 80,000–323,000 lives and about $900 billion in economic loss. In the immediate aftermath of a megaquake, most of the disaster response agencies and personnel, if not all, will be overwhelmed and many neighborhoods in the region will need to rely on themselves to maintain essential activities for a prolonged period. To support these essential activities, communications will need to be robust enough to function under highly uncertain circumstances, and to enable real-time and reliable information sharing for efficient resource allocation and matching. This proposal represents the US portion of a planning grant for a collaboration with researchers from multiple Japanese Universities as part of the NSF/JST collaboration for the Smart and Connected Community Program.

This planning grant builds the capacity of a partnership of engineers and planners on both sides of the Pacific Ocean (Seattle area and Japan) to developing these critically needed communications and information-sharing technologies. The joint team will partner with three communities in Washington State and the city of Nagoya in Japan, to ensure that initial technical prototype ideas have real, place-specific relevance and applicability. Focus groups and community workshops will identify specific community needs, values, resources and concerns, and provide a feedback loop for evaluating the prototypes. It is expected that by working with these communities, the technological tools to be developed will be socially integrated, not only helping communities to address the critical need to prepare for a possible mega-earthquake but also to enhance resilience in the face of a wide range of life uncertainties and disruptions, and to improve communities’ daily quality of life.

This activity is in response to NSF Dear Colleague Letter Supporting Transition of Research into Cities through the US ASEAN ((Association of Southeast Asian Nations Cities) Smart Cities Partnership in collaboration with NSF and the US State Department. Prairie View A&M University (PVAMU) will be partnering with University Tenaga Nasional (UNITEN) at Kuala Lumpur (KL), Malaysia, to develop renewable energy sources for bike lanes in KL. Kuala Lumpur is the largest city in Malaysia, and it is home to approximately 1.808 million people. The city has an 11 km long dedicated bicycle lane to reduce traffic congestion. The partnership between PVAMU and UNITEN will accelerate innovation in bike lane energy technologies. The vision of the project is to develop composite power generating cells that will generate power when bikes are ridden on the power generating cells. The energy will be harvested from composite power generating cells and will be laid on the bike lanes. The harvested energy will be used for emergency lamps along the bikeways to give more safety to the bikers or provide electric power for electronic signs installed alongside the bikeways. In addition, the harvested energy will be used for charging gadgets and provide purified water for bikers or pedestrians. The multi-sourced energy system will have applications in supplying power for (i) rainwater purification through reverse osmosis systems, (ii) emergency lights, and (iii) charging stations in the bike lanes in the city of Kuala Lumpur, Malaysia. The system will be initially tested at PVAMU and will then be integrated with UNITEN and piloted in Kuala Lumpur. The project will have a huge impact on the green lifestyle of the people at Kuala Lumpur. Moreover, the research matured in this project may be suitable for use in other ASEAN cities as well as many cities and towns in the United States to provide renewable energy sources for their bike lanes.

The main goals of the project are: (i) develop a composite power generating cells that generate power under pressure, (ii) design charge collection electronic circuits to store the generated power, (iii) fabricate an integrated pad system with power generating cells, charge collection circuits, battery storage, and paint, (iv) install and test the integrated pad system at Kuala Lumpur, Malaysia. The activity will leverage research at Prairie View A&M and UNITEN. To enable the use in bike lanes, thin-film PZT cells with optimized thickness will be developed. The energy and thickness of the film will be determined for each type of nanomaterial of the PZT cell. Experiments will be conducted to determine cells’ edge-to-edge distances, total energy output, the thickness of the PZT, and time responses of energy accumulation. A microcontroller-based energy monitoring system will manage the energy production and consumption for mobile charging applications. The cells will be configured with a matrix of paint strips on bike lanes. In addition to the composite power generating cells, solar panels will be combined in various places throughout the bike lanes to the energy-collection-rail, thus creating the sustainable multi-sourced energy system for the bike lanes. Various experiments will be performed to optimize the energy process from the bike lane. The design will be tested at PVAMU and then integrated into a bike lane infrastructure in Kuala Lumpur. The PVAMU and UNITEN team will be collaborating with city planning personnel to validate the concept and support evaluation as part of KL smart city activities.
 

Food deserts, generally defined as areas in which it is difficult to buy an affordable, high-quality fresh food, are not exclusive to urban or rural areas, but more indicative of under-served communities, low-income households, and minority neighborhoods. Food deserts are not only a health issue but also a community development and equity issue. Access to safe and nutritious food is a fundamental individual right. This project aims to address the food desert problem in Greater Richmond area, by engaging a wide range of food access-related stakeholders and utilizing the power of data analytics and advanced smart technologies to achieve sustainable food access program, leading to higher levels of quality of life and health for the city citizens.

Utilizing smart technologies to improve food access for a large segment of the community is not a straightforward task. There are many questions to be answered in order to realize the potential of these technologies, including: (1) what are the data needed to better understand and help address the food desert problem. (2) What are the social and economic impacts of food deserts? (3) What are the main factors contributing to limited food access in certain geographical areas? (4) What are the technologies and cyber-infrastructure that can help address the food access problem? (5) How to encourage micro-businesses to help tackle limited food accessibility? (6) How to present food desert data efficiently to help in decision-making?

This planning project will assemble a core group of scientists in engineering, life sciences, social work and government policy colleges to engage with community leaders and stakeholders, to identify through both quantitative and qualitative assessment the key challenges to sustainable food access in Richmond and its adjoining communities, and create the knowledge and tools for community-based sustainable food access program. This will be achieved by (1) developing a fundamental understanding of challenges facing communities due to food desert problem, (2) developing a better understanding of the factors contributing to food access problem, (3) recognizing various types of data collection in communities for addressing food access challenge, (4) deriving data-analytics techniques that can help identify effective solutions and evaluate their impacts, and (5) facilitate customized sensing, data-management, cyber-infrastructure and smart technologies solutions to develop a robust program for sustainable food access. The proposed plan will offer a research and development model that can be extended to other cities and communities.
 

Seniors (i.e., adults aged 65+) are the most rapidly growing segment of the U.S. population and have an increased risk of social isolation due to changes in lifestyle and physical health. Social connectedness, which involves establishing, sustaining, and increasing the quality of social relationships, is key to preventing or mitigating social isolation. Technology can foster social connectedness through online services and mobile applications. However, several factors, including lack of technological skills and awareness, accessibility issues, and privacy concerns may limit seniors’ use of technology-enabled services and resources, creating a generational digital divide that may contribute to social isolation. The Smart Social Connector (SSC) project addresses social isolation due to age-related barriers by creating informed strategies for seniors to learn and adopt technology and aligning resources with community needs. As such, this project promotes meaningful social connectedness among seniors that creates a sense of belonging within their community, advancing their health and welfare. Specifically, the SSC project provides a foundation for reconnecting senior residents in El Paso, Texas, a majority-Hispanic bicultural community with a growing senior demographic. This interdisciplinary, collaborative project has the potential to shift attitudes and behaviors toward seniors by restoring their visibility, value, and equitable participation in their community. With the involvement of students who are primarily from underrepresented groups, the SCC project contributes to broadening participation and preparing the next generation of professionals who possess the technical skills and knowledge required to address societal problems, specifically those relevant to senior populations.

In a strategic partnership among The University of Texas at El Paso, El Paso Community College, and the City of El Paso, the project is driven by integrative and interdisciplinary research among social sciences (i.e., anthropology and cognitive psychology); computer science; engineering (i.e., systems engineering and civil engineering); and scholarship of engagement (i.e., awareness and education). The SSC goal is to develop and sustain social connectedness of seniors to improve their quality of life through the intersection of technology, community engagement, and social sciences. In collaboration with community stakeholders, this community-based participatory research project has two main objectives: (i) advance knowledge on the systemic and behavioral factors that increase social connectedness and bridge the generational digital divide in seniors; and (ii) increase social and technological connectedness for seniors through Smart City solutions. The research team will utilize a variety of methods and instruments, including assessments of computer self-efficacy and cognitive ability, team-performance measurements, virtual/physical social-network analysis, and user-centered iterative design and testing of Smart City solutions. The SSC will involve the creation of a human and technological infrastructure, including a Living Lab environment, to support service delivery and the iterative development and piloting of Smart City solutions that integrate people, technology, and information. The SSC project will support seniors in strengthening their social connectedness, increasing their technology self-efficacy, and contributing to their community. The outcomes and lessons learned from the SCC project have the potential to be applied in other cities that need to address the generational digital divide to improve seniors’ quality of life.