Infrastructure Systems Interdependency


Interdependencies across urban systems are increasingly acknowledged by city managers and planners. MAC focuses its research on utilizing data to understand the interdependency among three infrastructure systems, transportation systems, energy systems and water/sewer systems. The proposed research, if successful, creates a new paradigm for utilizing the complex nature of interrelationships among various urban systems to assist predicting and decision making.  At the same time, this research gains a better understanding of the interdependency of roadway, transit, parking and building systems, etc. through holistically mining the massive data of all those systems.


Interdependency among urban infrastructure systems

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Team: Sean Qian (PI), Xuesong Liu (Co-PI, CMU), Mario Berges (Co-PI, CMU)
Funding source: National Science Foundation
Start/End time: 2016-2018

We propose an approach that utilizes processed probe request log dataset collected through Wi-Fi network for occupancy estimation and HVAC system control. Occupancy detection approaches are explored and compared to illustrate that the WiFibased approach fit the requirements of HVAC controls. WiFi-based occupancy detection and prediction approaches are investigated using a real-world case study, and an integrated framework for occupancy-based predictive HVAC optimization is proposed for future application.


  • Xuan Li, Pine Liu, Sean Qian (2017), “Towards An Occupancy-enhanced Building HVAC Control Strategy Using Wi-Fi Probe Request Information”, Proceedings of the 2017 International Workshop on Computing in Civil Engineering. [URL]

Award: NSF Award page