URI professors developing ‘smart city’ based on human nervous system

UNIVERSITY OF RHODE ISLAND ASSISTANT professor Tao Wei and student Brian Chen set up a sensor system in their engineering laboratory as part of their research on a smart city network. / COURTESY URI/MICHAEL SALERNO
UNIVERSITY OF RHODE ISLAND ASSISTANT professor Tao Wei and student Brian Chen set up a sensor system in their engineering laboratory as part of their research on a smart city network. / COURTESY URI/MICHAEL SALERNO

SOUTH KINGSTOWN – Three University of Rhode Island engineering professors are using the human nervous system as inspiration for a “smart city” sensor network.

The professors, Tao Wei, an assistant professor of electrical engineering, and engineering professors Qing Yang and Haibo He, received an $850,000 grant from the National Science Foundation to begin developing sensors and computer architecture for future “smart cities.”

The researchers are working on a prototype for their smart city, focusing on a municipal gas pipeline system.

Smart cities, according to Wei, have their entire municipal infrastructure, such as power grids, communication networks, water and wastewater systems, public transportation, health care and security, linked by a computer, with a sensor system for real-time monitoring.

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A recent report, by consultants Frost and Sullivan, said the market for smart-city development is expected to reach $1.5 trillion by 2020.

“We want to come up with the computer architecture that can manage to collect all of this data from all the individual components and use it for diagnostics applications,” Wei said in a statement. “If there were a fire somewhere, the system would immediately point out where it is and quickly evaluate its severity to determine how best to respond.”

The project is inspired by the human nervous system, as neuromuscular reactions and instinctive motions respond to urgent situations without requiring direct brain intervention.

Wei used the example of touching something hot. One immediately pulls their hand back, without waiting for a signal from the brain.

The smart city would have “thousands of sensors or nodes,” he said.
“The nodes can talk with each other and decide whether it is a huge event that needs to be reported to the upper level nodes or whether they can respond without further assistance,” he said. “At the top of the structure is a supercomputer or cloud computer that can handle a huge amount of data. The beauty of the system is that we don’t necessarily have to bother the brain every time.”

At the end of the four-year grant, Wei and his colleagues expect to have a working prototype that will be able to process data and respond to various disturbances. Then they will apply the system to existing infrastructure, possibly one building.

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