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Research Sensors

Center for Multidisciplinary Research Excellence in Cyber-Physical Infrastructure Systems (MECIS) College of Engineering and Computer Science

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Center for Multidisciplinary Research Excellence in Cyber-Physical Infrastructure Systems (MECIS)

Overview - Related Links

  • Autonomy
  • Sensors
  • Artificial Intelligence

Contact Us

Center for Multidisciplinary Research Excellence in Cyber-Physical Infrastructure Systems (MECIS)
EPOB4 13
Email: mecis@utrgv.edu
Phone: (956) 665-3070
Phone Alt: (956) 665-8878

Quick Links

  • NSF
  • NSF Award 4900
  • University of California, Riverside
  • University of Illinois Chicago
  • University of Illinois

Sensors

The development of novel materials for sensing is of great importance for critical applications in cyber-physical infrastructure systems, including: (i) effective health monitoring of moving (railcar rolling asset) and static (pavements) infrastructure, which is an essential process to ensure the continued reliability and cost-effective, proactive maintenance of infrastructure; and (ii) reliable operations of autonomous vehicles (AVs) and unmanned aerial vehicles (UAVs), which require information from various sensors to safely navigate during night-time to precisely measure the distance to the surrounding objects, among others. In addition to sensing, novel materials and manufacturing technologies are also needed for sustainable and cost-effective design of large, yet lightweight structures for next-generation UAVs.

The MECIS Center will design, fabricate, test, and deploy a variety of sensors and new 3D printing technology for direct printing of lightweight UAV structures. The design process encompasses computational simulation of sensor materials, chemical synthesis of sensor materials, 3D printing of sensors, and 3D printing of lightweight UAV structures. Once deployed, the collected sensor data will be analyzed building on our proposed generic, data-driven framework for infrastructure health prognostics and optimization, which will assist asset managers in identifying deteriorating infrastructure components and scheduling proactive maintenance.

mecis-sensors

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