CETI Award Recipients

2010

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Dr. Mario Bergés

Instrumenting Civil Infrastructure to Increase Its Resilience, Adaptiveness, and Self-Monitoring Capabilities

Dr. Bergés is interested in making use of cost-effective sensor systems to automatically create models and generate insights that can be used to improve the behavior of infrastructure systems, prevent failures, and better plan for the future. He has been working on three different approaches related to this: appliance-level energy feedback through minimally intrusive strategies, sharing sensing and actuation resources at Internet scales, and unsupervised sensor fusion for proactive energy management

2007

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Korea Institute of Construction Technology: Bridge and Road Condition Monitoring Using Wireless Sensor Network

The concept of using a wireless sensor network (WSN) for civil infrastructure monitoring is not new. No one, however, has successfully developed a fully functioning WSN system for civil structures. Dr. Cho and his team have successfully developed two applications in WSN civil infrastructure management: (1) Bridge SHM (Structural Health Monitoring) and (2) Road Surface Condition Monitoring using a WSN with independent power supply, solar batteries.

2006

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Intel: Emerging Platforms Lab, Low Power Wireless Sensor Networks - Benefits Analysis in an Industrial Environment

Through the hard work of the Sensor Networks team, Intel Solutions Services, and Corporate Services, the wireless sensor network deployment in Hillsboro, Oregon, is showing promising results. Although wireless networks for predictive maintenance are in their infancy, several companies and research institutions are making the hardening of these technologies a high priority. Wireless is a good solution to address the needs of maintenance managers, who are trying to control costs and have control of their machinery. Wireless sensor networks provide a relatively low entry cost with many of the benefits of a more costly online wired system. It provides a path for plants to convert from the cumbersome, labor-intensive, walk-around methods to plant reliability by capturing data more frequently at a lower operating cost.