Communities are adversely affected by social harm events such as crime, traffic crashes, medical emergencies, and drug usages. This proposal aims to develop algorithms and software systems for the collection, analysis, and dynamic prediction of social harm events to facilitate appropriate government interventions to improve the quality of life in communities.

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.

Uncertainties during global pandemics, such as the novel Coronavirus disease (COVID-19), can generate fear and anxiety, resulting in panic-buying and overreactive consumer behavior. Information from a multitude of sources may further exacerbate the situation, leading to shortages of critical disease prevention products for emergency managers and those in dire need. The consumer response may also vary based on population demographics and community interactions.

This goal of this project is to optimize processes for remote delivery of meals to persons in need. The COVID-19 pandemic has fundamentally disrupted processes of food delivery to economically depressed and vulnerable segments of the US population. With the closing of schools and the advent of social distancing practices, over 13 million low-income students who have historically relied on their school to provide daily meals are now without important nutritional support, and centralized school summer meal distribution programs are no longer viable.

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.

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 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.