Agent-based Scenario Planning for a Smart & Connected Community against Sea Level Rise in Tampa Bay
Lead PI:
Yasin Yilmaz
Co-Pi:
Abstract
Sea-level rise and flooding pose significant risks to communities and infrastructure in Florida and many other coastal states. The work in this proposal seeks to engage a variety of stakeholders in the Tampa Bay region, from citizens to businesses to government agencies, in exercises grounded in Big Data analytics and agent-based modeling that simulates the dynamics and uncertainty of responses to sea level change. The ultimate objective is to create a more connected community by convening these stakeholders and having them work together towards crafting resilient responses to the possible outcomes of sea level rise scenarios. In addition to bringing together scientists, government officials, and business owners, we will also inform the general public, educate K-12 students, outreach to the minority groups about the challenges resulting from sea level rise and coastal flooding due to extreme weather events and natural disasters such as hurricanes and flash floods through a simplified version of the developed software, which is fostered by attractive visual features.

The prospective research proposed in this work will provide the much needed foundational science and technology for tackling the potentially disastrous effects of coastal flooding. It will develop novel Big Data analysis techniques and game-theoretic frameworks to deliver an agent based decision-making model which will underlie a scenario planning software for facilitating the community engagement. The proposed decision-making model will integrate fundamental disciplines including oceanic, atmospheric, and marine sciences, civil and environmental engineering, urban planning, and the social sciences into the multi-disciplinary scenario planning framework. The community engagement will be handled from an integrated systems perspective.
Yasin Yilmaz
Dr. Yilmaz received his Ph.D. in 2014 from the Electrical Engineering Department at Columbia University, New York, NY. His research interests are in machine learning and statistical signal processing with applications in computer vision, cybersecurity, biomedical systems, IoT networks, smart grid and energy systems, intelligent transportation systems, social and environmental systems, and wireless communications.
Performance Period: 09/01/2017 - 08/31/2019
Institution: University of South Florida
Award Number: 1737598