Advancing Human-Centered Sociotechnical Research for Enabling Independent Mobility in People with Physical Disabilities
Lead PI:
Carol Menassa
Co-Pi:
Abstract

This Smart and Connected Communities (S&CC) project will advance methods to improve end-to-end mobility for people with physical disabilities who rely on wheelchairs in their daily activities and encounter several barriers to their movement in the built environment. A typical mobility scenario involves navigation (i.e., finding accessible routes) and maneuvering tasks (i.e., parking wheelchair in confined spaces). These scenarios demand substantial effort and pose safety and anxiety risks for people with physical disabilities adversely affecting their quality of life. This project engages a broad group of stakeholders with converging disability perspectives (e.g., veterans with disabilities), patient care expertise, and experience in public service to create a user-centered autonomy that will enable people with physical disabilities to independently control their travel needs. The project scope will focus on individuals without any significant impairment in upper extremity function and/or sensory and cognitive domains, opening the door for future translational research that will extend research outcomes to other groups with diverse abilities.

This integrative research project addresses critical knowledge gaps and leverages a participatory design process to: 1) Discover determinants for successful end-to-end mobility system performance from the perspective of people with physical disabilities; 2) Integrate new navigation and maneuvering algorithms to support end-to-end personal mobility of people with physical disabilities; 3) Investigate mechanisms to enhance a symbiotic relationship between users and the end-to-end mobility system; and 4) Explore psychological, social, and economic factors conductive to promoting widespread adoption in communities. A cohort of people with physical disabilities embedded within the research team will continually inform the project activities for its entire duration. In addition, two study groups recruited in coordination with the project stakeholders will participate in human factors studies conducted in both laboratory and naturalistic field environments to test and evaluate the implementation of the end-to-end mobility system in the Ann Arbor-Ypsilanti area of southeast Michigan. The evaluation plan includes assessment of economic and social-psychological factors affecting adoption of the system in the community of people with physical disabilities. The project outcomes have no limitation in terms of population size or travel distances and can be applied in mobility scenarios that include transportation modes such as shuttle bus, rail, on-demand vehicles, or soon, shared driverless vehicles, as well as scale across a broad range of constructed facilities and urban communities. Cities aspiring to become smart, connected, and inclusive urban communities will benefit from the results of this research by informing the integration of mobility needs of people with physical disabilities into their master plans.

Carol Menassa
Carol C. Menassa is a Professor and John L. Tishman Faculty Scholar in the Department of Civil and Environmental Engineering at the University of Michigan (U-M). Carol directs the Intelligent and Sustainable Civil Infrastructure Systems Laboratory at U-M. Her research focuses on understanding and modeling the interconnections between human experience and the built environment. Her research group designs autonomous systems that support the well-being, safety, and productivity of office and construction workers, and provides them opportunities for lifelong learning and upskilling. Carol has more than 120 peer-reviewed publications. Carol currently serves as a member of the Board of Governors of the ASCE (American Society of Civil Engineers) Construction Institute. She previously served as chair of the ASCE Construction Research Congress Executive Committee. Carol is an Associate Editor for the ASCE Journal of Computing in Civil Engineering and Assistant Specialty Editor for the ASCE Journal of Construction Engineering and Management. Carol is the recipient of the 2022 ASCE Walter Huber Civil Engineering Research Prize, the 2021 ASCE Arthur M. Wellington Prize, the 2021 ASCE Collingwood Prize, the 2017 ASCE Daniel Halpin Award, 2017 ASCE Alfred Noble Prize, 2017 Outstanding Early Career Researcher from Fiatech, 2015 CII Distinguished Professor Award, and 2014 NSF Career award. She also received several best paper awards.
Performance Period: 10/01/2022 - 09/30/2026
Institution: University of Michigan
Award Number: 2124857
Qoyangnuptu: Smart, Connected, and Culturally-centered System to Support the Well-being of Hopi/Tewa Youth
Lead PI:
Morgan Vigil-Hayes
Co-Pi:
Abstract

Across the nation, behavioral health concerns for youth are on the rise. In this context, American Indian and Alaska Native (AIAN) youth experience behavioral health disparities at some of the highest rates in the United States. Even as behavioral health services are becoming more available through mobile health and telehealth interventions, the lack of ubiquitous, high-speed Internet connectivity in rural tribal communities prevents many AIAN youths from accessing these critical services. It is in this context that we have partnered with the Hopi community to propose the Qöyangnuptu Intervention (QI), a sociotechnical system of care that integrates mobile healthcare (mHealth), relational support systems, and cultural ways of well-being. This project will combine community expertise with the expertise of clinical psychologists, education researchers, and computer scientists to pilot the QI. Importantly, this project will engage Hopi community members as co-researchers who will help shape our research design and pilot as we carry out the project. This project anticipates research outcomes will be helpful to many different communities who experience pernicious health and digital disparities, including other tribal communities, migrant communities, and rural communities.

The QI Pilot will allow us to answer the research questions that drive our social science and technological Research. These questions include: (1) In AIAN communities with unique cultural characteristics, how should a youth-focused sociotechnical behavioral health intervention be designed to encourage sustained engagement and positively impact indicators of mental health?; and (2) How can interactive technical interventions be designed to best support sustained community engagement in a challenged network environment? This project will utilize an interdisciplinary approach to designing, piloting, and evaluating the QI; we integrate research expertise from clinical psychology, special education, human-computer interaction, computer networking, and public health. This project will take a participatory action research approach to ensure that our research is community-driven. This project will produce five key research outcomes: (i) QI App that enables Hopi youth to engage with culturally-tailored interactive experiences to build social and emotional resilience; (ii) a cross-age peer mentorship program facilitated through the QI App; (iii) family resilience workshops that raise awareness and literacy about behavioral at a community level; (iv) a community-curated database of behavioral health resources that help guide Hopi youth and families to relevant and accessible resources; and (v) digital skills workshops focused on training Hopi youth in the technical dimensions of app development.

Morgan Vigil-Hayes
I am an associate professor of computer science in the School of Informatics, Computing, and Cyber Systems at Northern Arizona University. My research uses network analysis and participatory design to inform the design and evaluation of community-centric networked systems that operate in resource-limited environments. I teach courses on social computing, cyber ethics, computer networks, and network analysis.
Performance Period: 10/01/2022 - 09/30/2026
Institution: Northern Arizona University
Award Number: 2224014
Preparing for Future Pandemics: Subway Crowd Management to Minimize Airborne Transmission of Respiratory Viruses (Way-CARE)
Lead PI:
Sharon Di
Co-Pi:
Abstract

This Smart and Connected Communities (S&CC) project focuses on strengthening the preparedness and resilience of transit communities facing public health disasters through the development of a sociotechnical system for crowd management. Following the substantial drop in public transportation ridership across the globe during the pandemic, how can subway systems respond to and recover from a future pandemic? Mass transit, especially subways, are essential to the economic viability and environmental sustainability of cities. This research will elevate U.S. leadership and economic competitiveness in recovery from pandemics, and will improve the social, economic, and environmental well-being of those who live, work, and travel within cities. The goal of this study is to equip public transit communities (i.e., agencies, workers, and riders) with a sociotechnical system, “Way-CARE" (Subway Crowd Management to Minimize Airborne Transmission of REspiratory Viruses) that: 1) enables transit riders to make informed decisions and adapt travel behavior accordingly; and 2) provides transit agencies engaged in planning and policymaking with recommendations for mitigating virus transmission risks to riders and workers. People in low-income communities are among the most impacted and are in a disadvantaged position due to reduced accessibility to perceived safer travel modes. As such, the broader impacts of this study include helping identify needs, target resources, and develop more effective approaches to better ensure health and wellness, accessibility and inclusivity, and economic vitality for residents of low-income communities. The accompanying educational plan aims to broaden participation in engineering of underrepresented groups via outreach programs, including programs for Harlem public school teachers and K-12 students, as well as annual student data science challenges.

True health risks inside subway systems and future commuting patterns are unknown after the pandemic. The technological propeller of the project is the integration of sensing, crowd and airflow modeling, and public health knowledge on a microscale applied to subway crowd management. Coupled airborne dispersion and epidemiological models will be developed that account for microscale processes (transport of droplets and aerosols) affecting respiratory virus transmission opportunities. The social catalyst of the award is the integration of behavioral science evidence to inform travel choices and policy making. The Metropolitan Transportation Authority (MTA) and two local rider communities (Harlem and Columbia) will be engaged in the development and assessment of the sociotechnical dimensions of the project. To assure project success, a 2-phase evaluation plan is presented to pilot the system and the technologies. Transferability and scalability will be investigated with input from the engaged communities.
 

Sharon Di
Balancing theory and application, Xuan (Sharon) Di studies travel behavior and transportation systems, both of which are being transformed by emerging communications and sensing technologies. Her research helps transportation planners and managers maximize efficiency and sustainability. In particular, her work on travel behavior during disrupted networks, such as after a hurricane or structural failure, contributes to the design of resilient infrastructure. Di applies optimization, game theory, and data analytics to large data collected from various types of traffic sensors, including individual tracing devices such as GPSs. Her studies of travel behavior focus on such factors as travel demand, high-occupancy travel lanes, and the effects of ride-hailing services like Uber, as well as on the future role of connected and automated vehicles. Di is also a committee member of the Center for Smart Cities, at Columbia’s Data Science Institute. Di received a BS in traffic engineering, summa cum laude, in 2005 and an MA in transportation information and control engineering in 2008 from Tongji University, China. She received a PhD in civil, environmental, and geo-engineering from the University of Minnesota, Twin Cities, in 2014. Di received a Chan Wui & Yunyin Rising Star Workshop Fellowship for Early Career Professionals from the Transportation Research Board in 2016. As a graduate student, she developed an interactive multi-player game, Multi-Agent Route Choice, for undergraduate transportation engineering students.
Performance Period: 01/01/2023 - 12/31/2026
Institution: Columbia University
Award Number: 2218809

Smart Cities for ASEAN

The Inaugural International ASEAN Smart City Symposium: Experiences and Innovations (ISSCEI 2022) on December 19th and 20th, 2022 in Pullman Danang Beach Resort, Danang City, Vietnam convenes thought leaders, practitioners, and researchers to discuss smart city challenges in the ASEAN context, and identify applicable technology advances that could underpin sustainable solutions.
Enabling Smart Cities in Coastal Regions of Environmental and Industrial Change: Building Adaptive Capacity through Sociotechnical Networks on the Texas Gulf Coast
Lead PI:
Michelle Hummel
Co-Pi:
Abstract

The Coastal Bend Region (CBR) of Texas is vulnerable to acute and chronic environmental stressors stemming from natural and industrial sources, including flooding and erosion from high tides, storm surge events, and ship traffic, as well as higher levels of air and water pollution due to expansion of nearby industrial operations. Despite the multitude of environmental hazards facing the region, formal monitoring systems are limited and provide an incomplete view of local-level conditions. In addition, networks for communication and decision-making are often localized and/or fragmented. As a result, CBR communities lack the comprehensive data and decision-making structures needed to plan for, respond to, and mitigate the impacts of potential hazards. This project will advance the understanding of how smart and connected technologies can be integrated into and support regional communication networks to build adaptive capacity in the face of cumulative impacts from climate change and industrial expansion, using the CBR as an exemplar. Research activities will be co-developed and coordinated with residents, community-based organizations, elected officials, and city/county staff to strengthen multidisciplinary, cross-sector partnerships, enhance public engagement with science and technology, and broaden participation by underrepresented groups and frontline communities in the scientific process.

This project will apply a mixed-methods approach to assess how sociotechnical networks can be leveraged to increase knowledge and awareness of environmental and industrial hazards and to build community adaptive capacity equitably among diverse residents of the CBR. This project's main objectives are to (1) evaluate the structure and evolution of regional communication, information-sharing, and policy-making networks focused on environmental change and industrial expansion using grounded theory, (2) develop and leverage real-time sensing technologies, machine learning models, and data dissemination tools to monitor, predict, and communicate local-level environmental conditions, and (3) integrate the social and technical components through usability testing, tabletop exercises, and longitudinal questionnaires to assess how the generated data can be effectively interpreted and presented to various stakeholders to increase knowledge of environmental hazards, strengthen regional decision-making processes, and build adaptive capacity. Community workshops and symposia will provide opportunities to refine the study needs and objectives, obtain feedback on the sensor network and data products, share project results, co-develop a vision for long-term sustainability of the project, and discuss opportunities for integration with other regional efforts.

Michelle Hummel
My research focuses on understanding the impacts of natural hazards and climate change on water resources, critical infrastructure, and communities using a combination of physical, statistical, and geospatial modeling tools.
Performance Period: 10/01/2022 - 09/30/2026
Institution: University of Texas at Arlington
Sponsor: NSF
Award Number: 2231557
Reducing the Vulnerability of Disadvantaged Communities to the Impacts of Cascading Hazards under a Changing Climate
Lead PI:
Farshid Vahedifard
Abstract

Community resilience is frequently defined as the ability of a community to prepare, respond, and recover from natural and human-caused hazards. Preparedness is a vital aspect of community resilience, but our existing frameworks and emergency guidelines generally focus on response, rather than seeking to understand the connection between events and preparing for subsequent hazards. The majority of disasters involve a chain of events occurring in a cascading manner. The importance of preparedness against cascading hazards has been demonstrated by recent events, such as the Mendocino complex and Campfires in California, where all reports suggest that the lack of an integrated framework connecting decision-makers and residents exacerbated the devastating consequences of the fires. There is an urgent need for evaluating the vulnerability and preparedness of disadvantaged communities with access and functional needs (AFN) against cascading hazards. This Smart & Connected Communities (SCC) planning grant aims to reduce the vulnerability of disadvantaged communities to the impacts of cascading hazards in a changing climate. We seek to develop an effective warning system by integrating environmental-socio-technological monitoring and risk communications to serve disadvantaged communities. The overarching goal is to bridge the gap between the engineering, scientific, and social dimensions that have been striving to reduce the consequences of extreme events but are commonly evaluated in isolation of one another. The project will broaden the participation of local citizens in participatory risk management, as well as advance participatory, multi-scenario, multi-objective decision support that will make data and tradeoffs transparent and accessible.

Cascading hazards place disadvantaged communities at risk for disastrous outcomes, which are projected to worsen with climate variability and change. This project supports a multidisciplinary planning effort toward mitigating the impacts of cascading hazards from social science, climate, engineering, and decision-making perspectives. This project provides a capacity-building opportunity to better assess and quantify how the sequence of drought, wildfires, landslides, and flooding may drive one another and how the consequences of these cascading hazards may scale in both time and space. This project will provide insights into: (1) the science of cascading hazards and their tempo-spatial characteristics and impacts in a changing climate, (2) social and physical vulnerability in disadvantaged communities against the risk of cascading hazards, as opposed to a single hazard, and (3) an efficient strategy to communicate the risks of cascading hazards, which are inherently different in their devastation and scale. The project will also seek to build the capacity for advancing crisis communications by demonstrating how diverse sources of data (of disparate time scales, dimensionalities, and noise levels) can be integrated to improve decision-making and community engagement in remote and disconnected environments. The project involves collaboration with California Office of Emergency Services (CalOES) and will focus on Lake County, CA, a disadvantaged community with dwindling resources and growing multi-hazard threats. While applied to a sequence of drought, wildfires, landslides, and flooding, this framework is directly translatable to any set of cascading hazards and will advance the state-of-knowledge to go beyond hazard evaluation that typically focuses on a single event.

Farshid Vahedifard
Geotechnical engineering; Analytical and numerical methods in geomechanics; Thermo-Hydro-Mechanical modeling of geo-materials, quantitative assessment of resilience of critical infrastructure to extreme events under a changing climate, geo-energy modeling (e.g., carbon sequestration, and CO2-EOR); Induced seismicity; Reinforced earth structures; Geosynthetics; Variably saturated earth structures; Remote sensing and GIS applications in natural and man-made hazard assessment and health monitoring of geo-systems (e.g., dams, levees); Micromechanical modeling of granular materials; Design of embankment dams and levee systems, mobility modeling in soil.
Performance Period: 09/01/2020 - 08/31/2022
Institution: Mississippi State University
Sponsor: NSF
Award Number: 2125610
Co-Producing Community - An integrated approach to building smart and connected nutrient management communities in the US Corn Belt
Lead PI:
Andrew Margenot
Co-Pi:
Abstract

Farmers in the United States (US) Corn Belt produce ~30% of the world’s corn and soybean, which depends on the use of fertilizers containing both nitrogen (N) and phosphorus (P). However, due to a lack of consistent and reliable information, these farmers tend to over-apply fertilizer. This practice directly affects farmers, as they are paying higher fertilizer costs than necessary, and negatively impacts environmental sustainability. Yet, farmers’ perceptions of nutrient management challenges vary widely as does their willingness to adopt novel nutrient management approaches. Working collaboratively with the Illinois Farm Bureau, the University of Illinois Extension, and engaging farmers directly through the these partnering organizations, the team of academic and community partners aims to build a smart and connected "Nutrient Management Community (NuMC)" to help farmers adopt effective and trusted nutrient management tools to address critical water quality issues stemming from nutrient runoff while reducing farm nutrient application costs. The project is built on the premise of voluntary adoption of nutrient management practices and includes social science questions to assess the reasons and strategies for encouraging adoption of voluntary “best practices.”

Enabling farmers to manage N and P with greater precision is needed to increase farmer profitability and decrease off-farm losses of nutrients, which can compromise water resources. The objective of this research is to develop science-driven recommendations on N and P management that can be tailored to different farmers’ needs, focusing on the heart of the US Corn Belt: Illinois. This work has three objectives: (1) identify major constraints on how Illinois farmers manage N and P management, and determine to what extent these constraints vary among farmers; (2) determine how much N and P are stocked in soils across a diversity of Illinois farm (including through the use of soil sensors and satellite observations), and how this soil nutrient capital contributes to crop growth in order to model field-specific fertilizer needs; and (3) develop smart and connected technology solutions that enable constrained farmers to join a Nutrient Management Community (NuMC). This work will advance understanding of agricultural management by and for farming communities by providing insights on interrelated social science, biogeochemistry, and technology dynamics. The proposed approach will produce a community-based cyberinfrastructure that will address an urgent need: providing Illinois farmers direct access to high-quality and unbiased information on management nutrients.

Andrew Margenot
Dr. Margenot addresses the literal foundation of all cropping systems: soils. His research team evaluates how human activities can enhance or compromise soil services to society, with an emphasis on food security from urban and rural agroecosystems in the US Midwest and East Africa. The goal of these efforts is to help advance how we monitor and manage soils as natural capital.
Performance Period: 10/01/2021 - 09/30/2025
Institution: University of Illinois at Urbana-Champaign
Sponsor: NSF
Award Number: 2125626
Food Information Networks (FINs):Building data-driven supports for increasing access and healthy food choices in low-income neighborhoods
Lead PI:
Ronald Metoyer
Abstract

Food access is an unfortunate but very real problem for the many Americans that live in food deserts where the combination of distance to full service supermarkets and access to transportation makes healthy, affordable food less attainable. Today's technological innovations have the potential to address this problem, however they must be adapted to apply to the challenging socio-economic conditions of these communities. The proposed work will explore the development of heterogeneous network models, information visualization, and delivery services for addressing the problem of food access in two low-income communities in South Bend, Indiana and Detroit, Michigan. The proposed work will deeply integrate social research with technological innovation in a user-centered design-thinking framework in order to identify, understand, and meet the needs of the community stakeholders. In particular the proposed work addresses four overarching questions:What are the critical-user needs for a technology-enabled food recommender and access system?How do we model the complex food information landscape and make context-relevant recommendations for target users living under the constraints of povertyHow do we present accessible explanations of recommendations made over this complex landscape of determinants including, for example, preference, cost, and nutritional value.How feasible is a delivery hub model for addressing bridging the physical access gap?Through a series of iterative use research and design/development activities with community partners and community members, the project will develop a prototype recommendation engine that takes into account the broader context of poverty to make stakeholder-relevant recommendations for meal planning. This system will be evaluated using a mixed methods approach to understand the effects of the intervention on healthy food choice.

Ronald Metoyer
Ronald Metoyer is a Professor of Computer Science and Engineering at the University of Notre Dame. He earned his B.S. in Computer Science and Engineering at the University of California, Los Angeles (1994) and his Ph.D. in Computer Science from the Georgia Institute of Technology (2002). His primary research interest is in human-computer interaction and information visualization, with a focus on multivariate data visualization, decision making, and narrative. He has published over 65 papers and is the recipient of a 2002 NSF CAREER Award. He also serves as Associate Dean in the College of Engineering at the University of Notre Dame.
Performance Period: 12/01/2021 - 05/31/2024
Institution: University of Notre Dame
Sponsor: NIFA
Award Number: 1952175
AN INTEGRATED AND SMART SYSTEM FOR IRRIGATION MANAGEMENT IN RURAL COMMUNITIES
Lead PI:
Jun Wang
Abstract

Irrigation plays an important role for agricultural sustainability in U.S. and around the globe. In particular, the agricultural economy in the state of Nebraska, the largest U.S. state in terms of irrigated area, highly relies on irrigation in the growing season. With insufficient precipitation that has never met the demand for crop growth, the rural areas in Nebraska faces a central challenge to best utilize limited underground water in the Ogallala Aquifer for irrigation to sustain the growth of economy in the state. While irrigation can often help increase crop production, its cost and environmental effects are significant, especially during drought years. Furthermore, excessive irrigation can decrease harvestable yield, increase the coast for farming, and contribute to environmental degradation (such as nitrate leaching and soil erosion). Hence, irrigation scheduling is a key component for agricultural sustainability and growth in many rural areas in Nebraska.This proposed project will establish a smart and connected system to help rural communities' irrigation scheduling in Nebraska. The system will include intensive low-cost and smart sensor networks to measure soil moisture and 2-meter meteorological parameters in Scotts Bluffs county in western Nebraska, respectively. A citizen-science network with the same set of smart sensors will also be established by engaging with citizens outside of intensive network. The data collected from these sensors will be seamlessly assimilated into a modeling system that integrates weather forecast model, crop model, and irrigation scheduling optimization algorithm to assist farmers to maximize their crop profits, as well as to reduce excess water use. Observation data and model outputs will be delivered to the rural communities through smart-phone apps and on-demand web services that enable the users to access and visualize these data (including recommendations for irrigation schedule) to serve their customized needs (for any particular farm). By engaging communities through our proposed smart and connected system and planned activities, this project will help rural communities to embrace the opportunity of using smart technologies to address their economic challenges.Intellectual Merits:A smart and connected system is proposed that combines recent advances in environmental sensing and modeling to provide the recommendation of irrigation scheduling on the daily basis for farmers in two rural areas in Nebraska. This system will be used to test the hypothesis that data-driven approach and dedicated engagement with communities can be integrated to increase farms' profit and reduce engineering and environmental costs through optimizing irrigation scheduling in rural communities. A positive feedback loop is also hypothesized in which the smart-connected system can augment existing engagement and social acceptance of smart systems within the rural communities, and such augment in turn further strengthen the data-driven approach for improving system smartness, robustness, and the connections between communities. By providing solutions for seamless environmental sensor array design and communications, weather forecast with assimilation of sensor data at regional scale, and irrigation scheduling optimized for farm profits, the system in this project can be viewed as a prototype for future precision farming in many rural areas over the Southern Great Plains where the regional economy heavily depends on irrigation.Broader ImpactsThe proposed project will have broader impacts to rural communities by functioning as an accessible resource through our collaboration partners to outreach citizens in Nebraska, Iowa, and Illinois. This project will also provide training to students via updated courses and labs for interdisciplinary research that intersects biological science and engineering, environmental science and engineering, computer science and engineering, and social science. Research findings and data will be disseminated broadly at scientific meetings, public lectures, in publications, web sites, smartphone apps, and community engagement activities, thereby further broadening impacts of this project globally, especially for the regions where irrigated agriculture is dominant.

Jun Wang
Jun Wang is a Professor in the University of Iowa (UI), with joint appointments in the Department of Chemical and Biochemical Engineering and the Iowa Informatics Initiative, and secondary affiliation with the Center for Global and Regional Environmental Studies, Department of Civil and Environmental Engineering, Department of Physics and Astronomy, and Center for Computer-Aided Design. Prior to joining UIowa in 2016, he worked in University of Nebraska – Lincoln for nine years, first as Assistant Professor and then Associate Professor. His current research focuses on the integration of satellite remote sensing and chemistry transport model to study air quality, wildfires, aerosol-cloud interaction, and land-air interaction. Having worked as a short-term visiting scientist/faculty in NASA GSFC, NOAA STAR, and NCAR, he also enjoys interdisciplinary research and has worked in in areas related to public health, agriculture, climate change, renewable (solar and wind) energy, supercomputing, visualization, data mining, and education in Earth Science. Jun Wang has authored or co-authored 100+ citable works in the peer-reviewed literature. He has been a science team member of several NASA satellite missions. His projects have been funded by NASA, NOAA, DoD, USDA, NSF, state agencies, and private industries. In 2005, Jun Wang received his Ph.D. degree in Atmospheric Sciences from University of Alabama –Huntsville. In 2005-2007, he was a postdoctoral researcher in Harvard University. He also holds a B.S. in Meteorology from Nanjing Meteorology Institute (now Nanjing University of Information Science and Technology) and a M.S. in Atmospheric Sciences in Institute of Atmospheric Physics, Chinese Academy of Sciences. He was a recipient of NASA Earth System Science Graduate Student Fellowship in 2004, NOAA Climate and Global Change Postdoctoral Fellowship in 2005, NASA New Investigator Award in 2008, and NASA’s group achievement award for TEMPO satellite in 2013 and SNPP satellite in 2014. He also sits in “Atmospheric Environment” editorial advisory board and served as the section editor for its “New Directions” column in 2012 - 2017. Since 2018, he serves as an associate editor for Atmospheric Measurement Technique, and as an editor for Earth-Science Reviews. Jun Wang grew up in a small village near the Yangze river’s entry to the ocean. Since his childhood, Jun Wang is always fascinated by different weather phenomena, and recognizes the importance of weather for the crop yield. This childhood experience has shaped Jun Wang's research projects that always strive to link the ending points (of research) toward real applications. A recent manifestation in this regard is his team’s latest development of real-time weather and quality forecast for the mid-west region (http://esmc.uiowa.edu), which has aided farmers in their decision planning for irrigation, fertilization, aerial pesticide application, and harvesting. Jun Wang enjoys working with students and young scientists. In his view, One of the most joyful things for a faculty, is to see the students' progresses, achievements, and successes. His students have won various awards from different organizations at local, state, and national levels, and have gained valuable working experiences in national labs. They also traveled many places to present their exciting research results. In 2009, he received “Academic Star” award from University of Nebraska - Lincoln for “taking the art of mentoring to new height”
Performance Period: 03/01/2019 - 02/28/2023
Institution: University of Iowa
Sponsor: National Institute of Food and Agriculture
Award Number: 1831639
The “Community Tech Workers”: A Community-Driven Model to Support Economic Mobility and Bridge the Digital Divide in the U.S.
Lead PI:
Tawanna Dillahunt
Co-Pi:
Abstract

Information and communication technologies allow individuals to apply for benefits like health care and housing, to have groceries delivered to their homes, to schedule/attend healthcare appointments, and to apply for employment. However, digital inequalities in terms of access, use, and self-efficacy reflect offline socioeconomic inequalities and pose a serious threat to today's increasingly tech-reliant society. The digital divide is a multidimensional phenomenon that refers to three levels of differences: first, in who has access to the Internet; second, who has skills to use the Internet; and third, how the Internet is actually used. Many efforts to bridge the digital divide have failed because they only address the first level (e.g., providing public Wifi, computers, computer labs) without continued onboarding and training support. This project aims to address digital disparities in Southeast Michigan by leveraging and building the digital literacy of local experts (level 2) to provide digital support to communities (levels 2 and 3). Inspired by the transformative Community Health Worker model, this work proposes "Community Tech Workers" (CTW), a community-driven, "train the trainer" approach that promotes digital literacy in communities. Participants include a public housing authority in Detroit's Eastside neighborhood, a refugee resettlement agency that serves refugees in a public housing community in Ypsilanti, an advisory board consisting of local workforce development agencies and industry representation, and a steering committee of individuals who are involved in outreach, education, and interventions related to increasing digital proficiency and public health.

The research will (1) develop and validate a survey instrument measure to assess community digital capacity; (2) develop an initial CTW training program; (3) assess the training, learning experience, and impact of the CTWs within each community; and (4) capture and evaluate the economic value of the CTW model. The survey instrument will extend existing assessments for measuring individual digital capacity to create a novel instrument that measures digital capacities at a community grain size. This instrument will be validated across two communities, and then be used to measure the impact of the CTW activities on the two communities over time. CTW training activities will be evaluated via interviews with participants and observations of the training sessions. Recommendations for a credentialing system to document CTW proficiency and for a marketplace system to promote employment opportunities will be elicited via participatory co-design sessions, information which can be used to inform integration with or development of job recommendation and gig work applications. Finally, data on costs will be collected to generate a cost-benefit analysis of the CTW model, to explore its further scalability. Secondary outcomes of the work include providing local residents with free training to obtain the necessary skills to become a CTW, and in the future, temporary employment for selected tech workers and connections to local IT employment opportunities. Incorporating the model across multiple communities will help uncover generalizable requirements for creating equitable socio-technical infrastructures that support community digital capacity and expand local opportunities. This systemic perspective on the development and deployment of the CTW model aligns well with the goal of the NSF Smart and Connected Communities (S&CC) program, which is to accelerate the creation of the scientific and engineering foundations that will enable smart and connected communities to bring about new levels of economic opportunity and growth, safety and security, health and wellness, accessibility and inclusivity, and overall quality of life. This project is also supported by the Improving Undergraduate STEM Education program, which seeks to support projects that have high potential for broader societal impacts, including improved diversity of students and instructors participating in STEM education, professional development for instructors to ensure adoption of new and effective pedagogical techniques that meet the changing needs of students, and projects that promote institutional partnerships for collaborative research and development.

Tawanna Dillahunt
I completed my Ph.D. at the Human-Computer Interaction Institute (HCII) at Carnegie Mellon University under the advisement of Dr. Jennifer Mankoff. I received a Bachelors of Science degree in Computer Engineering from North Carolina State University and started my career as a software engineer with Intel Corporation. I developed desktop and network products for Original Equipment Manufacturers. While at Intel, I received a Masters of Science in Computer Science from the Oregon Graduate Institute at the Oregon Health and Science University before leaving to pursue my Ph.D. I was a recipient of the IBM Ph.D. Fellowship (2011, 2012), the Fran Allen IBM Ph.D. Fellowship Award (2011), and served on the program committee for FLAIRS in 2011. I hold three patents with IBM Research.
Performance Period: 01/01/2022 - 12/31/2024
Institution: Regents of the University of Michigan - Ann Arbor
Award Number: 2125012
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