United States Department of Transportation (USDOT), National Academies of Science (NAS) National Cooperative Highway Research Program (NCHRP), Georgia Department of Transportation (GDOT), National Science Foundation

Smart City Infrastructure

Goals

To develop smart city infrastructure health condition monitoring, detection and diagnosis with the use of emerging technologies (e.g. smart phones, 2D imaging, 3D laser, LiDAR, UAV, GPS/GIS, crowdsourcing, voice recognition, etc.) with artificial intelligence, machine learning, computer vision, pattern recognition, signal processing, and multi-source/scale/frequency/resolution data fusion, and spatial-temporal analyses for innovatively providing smart location-based services. To identify roadway asset deficiencies, such as potholes, cracking, etc., and dangerous roadway spots/sections that require safety improvement, etc. To cost-effectively and sustainably preserve and manage the infrastructure assets (pavements, signs, etc.) at the right time, right location, and right method by analysis of multiple sensors at multiple scales.

Issues Involved or Addressed

Big data analysis, including multi-source/scale/frequency/resolution data fusion and spatial-temporal data analysis for infrastructure health condition monitoring, detection and diagnosis, Study of fundamental characteristics of different sensing data, including smart phone accelerometer data, 3D laser, mobile LiDAR, GPS/IMU, etc.; Innovative integration of hardware, algorithms, and procedures to develop innovative solutions (e.g. mobile applications/tools); Real-world and real-time infrastructure behavior study of its health condition and deterioration behavior in support of smart and resilient cities development.

Methods and Technologies

  • Smart phones/tablet PC
  • Cloud Computing
  • Parallel Computing
  • Image/Signal Processing
  • Computer Vision
  • Machine Learning
  • Spatial Analysis
  • Non-Destructive Testing

Academic Majors of Interest

  • Electrical Engineering
  • Computer Engineering
  • Computer Science
  • Mechanical Engineering
  • Civil Engineering
  • Environmental Engineering
  • Industrial Engineering

Preferred Interests and Preparation

Meeting Schedule & Location

Time: 

9:05-9:55

Day: 

Wed

Location: 

Klaus 1440

Team Advisors

Sponsor(s)

United States Department of Transportation (USDOT), National Academies of Science (NAS) National Cooperative Highway Research Program (NCHRP), Georgia Department of Transportation (GDOT), National Science Foundation