Sensor Data Driven Proactive Management of Infrastructure Systems

The U.S. infrastructure is a trillion dollar investment, defined broadly to include road systems and bridges, water distribution systems, water treatment plants, power distribution systems, telecommunication network systems, commercial and industrial facilities, etc. In spite of the enormous investments made in these systems and their importance to the US economy, we (as in government, industry and academia) are not being very good stewards of this infrastructure. By their nature, infrastructure systems are large-scale, networked systems with physical components that may be themselves networks of systems and whose health, due to use, environment, and abuse, can significantly deteriorate. Because of expense and growing local demand, these systems have expanded over decades in a more or less ad hoc fashion. Because of their size and highly interconnected nature, the operating conditions of the overall network are difficult to assess from local data. Often, local actions may give rise to unexpected global behavior. The objectives for this position paper are: 1) to illustrate the need for such sensor-data driven proactive infrastructure management; 2) to discuss the major research questions or challenges that need to be addressed to achieve this vision; and to discuss an approach we are taking at Carnegie Mellon to explore these topics.