FUTURe CITy Fostering Smart Urban Transformation and Ubiquitous Resilience with Connected Infrastructure and Technology
- Dr. Mohamed Abdel-Aty, PE
Trustee Chair Pegasus Professor and Dept Chair Civil, Environmental and Construction Engineering
Ubiquitous Resilience with Connected Infrastructure and Technology - - PowerPoint PPT Presentation
FUTURe CITy Fostering Smart Urban Transformation and Ubiquitous Resilience with Connected Infrastructure and Technology Dr. Mohamed Abdel-Aty, PE Trustee Chair Pegasus Professor and Dept Chair Civil, Environmental and Construction Engineering
Trustee Chair Pegasus Professor and Dept Chair Civil, Environmental and Construction Engineering
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What makes a City?
Infrastructure
Operations
People
Cities and Urban Areas
1913: 10% of world’s population lived in cities
2013: 50% and 2050: 70% of world’s population in cities
80% of Americans reside in Urban areas (2010 Census)
Urban areas and metropolitan regions account for 76% of all economic activity and 85% of all scientific innovation.
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Integrating wide-ranging technological advances
Improving quality of life and economic vitality
Center of excellence for technologically, socially and organizationally balanced urban transformation
Improve quality of life for its citizens through technology, ultimately creating a sustainable environment
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Smart Infrastructure Urban Operations People – Public Policy and
(1) To build expertise in deployment of sensing, communication and data transfer network for the interconnected smart city infrastructure
(2) To employ expertise for advanced urban computing data analytics, information technology networks for smart city operations
(3) To develop proficiency in coordinating between technology development and policy formulation, social programs and their implementation
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Our initiative is supported by the following with strong recommendation
Transit Kiosk
Connected Vehicle Technology
Safety and Mobility Applications
Solar Energy
Real-Time Multimodal Data
Bus Automated Vehicle Location
Parking Availability
Travel Times
Ride Share Availability
Transit Demand
Leveraging Aspects of
Developing Mobility on
Trying to pave way for
Evaluation and Value Addition Big data analytics and IOT Connected and Autonomous Vehicles
Smart City Simulation and Visualization Develop an autonomous vehicle for garage
Clean data from a person with multiple
Develop algorithms for assigning the
New forward compatible
Demonstration of benefits Coordinated decision making Latest technology deployed
Enhancement mobility and
Applications for Smart Phone
Parking, drive time vs
More efficient transit service,
Automated vehicle connecting
Connection ready for
New Standard in Signal Technology Modular Software
Route and Mode Choice Engine Can be used connect LYNX, Votran,
OBU software Can be integrated into existing Apps to
ITS Traffic Detection
Strength of ITS
Congestion
Safety
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Analytics Insights
Mobility Innovation
urban mobility & congestion
response
delivering critical urban services
UCF Civil, Environmental, and Construction Engineering
Kevin Mackie Andrew Yun Omer Tatari Necati Catbas Boo Nam
CITRS Group
Reliability and probabilistic assessment Sustainable and green structures Novel and nanotech- based materials for civil infrastructure bridges, buildings, highway structures, pavements, roads, stadiums, convention centers, airports, ports, dams, tunnel, lifelines Structural health monitoring and identification with novel sensing, analysis, and predictive analysis approaches Material-, component-, and large-scale testing
Non-destructive evaluation Advanced modeling and analysis, multiple hazard assessment Life-cycle assessment and life-cycle cost
FULLY AUTOMATED ANALYSIS FOR SAN ANTONIO ROAD NETWORK BASED ON ASTM D 6433-11 Multi-purpose road survey vehicle equipped with LRIS, right-of-way digital cameras, laser surface profiler, GPS, DMI, and on- board computer GPU-BASED HIGH-PERFORMANCE COMPUTING
NVIDIA TITAN X was used to process a high-volume image data at high speed (< 5 sec/ image) (PASCAL architecture, 3584 CUDA cores, 12GB GDDR5X) MULTI-SCALE CONVOLUTIONAL NEURAL NETWORK (CNN) is a Deep Learning algorithm developed to deal with various scale issues to detect 13 different road surface objects, such as crack, patch, manhole, marking, pothole, etc.
RAW PROCESSED
NOVEL DIELECTRIC CONSTANT IDENTIFICATION ALGORITHM FOR VERY HIGH SPATIAL RESOLUTION
RETRACTABLE AIR-COUPLED 3D GPR CONTROLLING DECK MULTI-PURPOSE ROAD INSPECTION VAN
3D GPR HIGH-SPEED ROAD SURFACE IMAGING DEVICE
Connected, heterogeneous sensor network
Multi-pollutants, multi-platform, address specific community needs
Kelly Kibler, PhD
Hydraulic Modeling
Assessment
Talea Mayo, PhD
Development
Quantification
Steven Duranceau, PhD, PE
Treatment
Reuse
Byproducts
Dingbao Wang, PhD
Groundwater Modeling
Systems
Transport Modeling
Arvind Singh, PhD
Transport
Dynamics
A H M Anwar Sadmani, PhD
& Hybrid Processes
Pollutants of Concern
Applications
Sources
Stephen Medeiros, PhD, PE
Hydraulics
Hydrodynamics
& Lidar
Industry / Business
Instrumentation
Thomas Wahl, PhD
storm surges
erosion risk
analysis
In Situ Sensors for Water Quality Monitoring Renewable Energy Production from Wastewater
Heavy metal sensor for drinking water and groundwater quality monitoring Point-of-use sensor for drinking water Algal farming using CO2 from power plants Harmful algal blooms (HAB) monitoring sensors Oil spill & chemical detection microsensor Carbon sequestration
In situ heavy metal detection microsensor
Biomass production SMART wastewater treatment Renewable energy production (H2, biofuel, electricity) No mechanical aeration
Algae farm using CO2 from Stanton Energy Center (Orlando, FL)
Nutrient (N & P) recovery
Microbial fuel cells (MFCs) for electricity generation from wastewater
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