Carnegie Mellon University

Advanced Infrastructure Systems (AIS)

The infrastructure systems of tomorrow will combine traditional physical assets with cyber-technologies like computers, networks and sensors. AIS researchers work to develop novel technological solutions to problems involving the planning, design, construction, and management/operation of built environment and infrastructure for smart and connected communities.


Our research projects are primarily problem-driven and can be catalogued by arranging them along three dimensions, namely:

  1. Targeted infrastructure systems, such as buildings, bridges, transportation, pipelines, and power grid.
  2. Methods used to solve the problem, such as artificial intelligence, system engineering, economics, and public policy.
  3. Societal needs that are addressed, such as citizens’ quality of life, efficient governance, social equity, and economic prosperity.

Examples of AIS research projects:

Occupant Tracking and Characterization through Activity-Induced Structural Vibrations

This project uses sensing and machine learning in structures to better manage the quality of life of building occupants in a non-intrusive and maintainable way.

Based on the fact that many occupant activities, including walking, cooking, washing, etc. induce vibrations in ambient structures, we sense and analyze those minute vibration signals to indirectly understand occupant activities and their characteristics (e.g., location, identity, activity level, physical/mental health status, etc.).

  • Structural Systems
  • Machine Learning
  • Sensing
  • Quality of Life

Structural Health Monitoring of Windmills

This project leverages improved probabilistic modeling methods to ensure the integrity of windmills for electricity generation, in order to promote decreased dependence on fossil fuels and sustainability.

  • Structural Systems
  • Probabilistic Modeling
  • Sustainability

Transportation Data Analytics

This project leverages data on vehicle ownership and perioding safety and emissions inspections to produce high-resolution estimates of how vehicles are driven and maintained in order to promote a safer passenger transportation system.

  • Transportation Systems
  • Data Analytics
  • Safety
Detailed view of a manufactured hybrid car engine

Autonomous Vehicle Systems Analysis

This project uses systems modeling methods to consider the safety and sustainability implications of the transition to autonomous vehicles in the passenger transportation system.

  • Transportation Systems
  • Systems Modelng
  • Sustainbility
  • Safety
car

Multi-modal Transportation System Modeling and Decision Making

This interdisciplinary project uses economics theories, data mining models, and engineering methods, to learn travelers’ behavior, understand inter-relations among roadway, public transit, and parking systems, and ultimately facilitate the optimal decision making for transportation systems, such as pricing, operation, and planning.

  • Human Behavior
  • Data Analytics
  • Economics
  • Optimization
  • Network Theory
  • Efficiency
  • Safety
  • Sustainability
  • Social Welfare

Optimal Design of Shared Mobility Services in Transportation Networks

This project uses network flow theory, game theory and data analytics methods to optimally price and schedule shared mobility service (such as public transit, accessible transportation, first/last mile micro transit) to enhance safety, efficiency and reliability of passenger transportation systems.

  • Transportation Systems
  • Human Behavior
  • Data Analytics
  • Economics
  • Optimization
  • Network Theory
  • Efficiency
  • Safety
  • Sustainability
  • Social Welfare

Intelligent Transpottation System

Fault Detection and Diagnosis

  • Machine Learning

  • Software Verification

  • Information Modeling

  • Efficiency

  • Cost- reduction

Drone-Based Inspection of Bridges

This project uses BIM and drone techonolgy to improve bridge inspection processes.