Data collected by mobile phones could be used to assess the structural integrity of bridges, suggests a new study, informing potential maintenance requirements and keeping them in action for 30% longer.

Using the Golden Gate Bridge in San Francisco as an example, researchers showed that smartphones can capture the same kind of information about bridge vibrations picked up by stationary sensors

The findings suggest that crowdsourced monitoring could be a cheap and convenient way to monitor the structural integrity of transportation infrastructure worldwide, and could potentially increase the lifespan of bridges by up to 30%.

There is a global need for infrastructure monitoring to improve the resilience and longevity of bridges, buildings, and other structures—it’s pretty much a guaranteed applause-grabber in political debates in America, because the need is so great.

The structural health of bridges is usually visually assessed by engineers on-site, which is often time consuming and infrequent, or measured using static sensors incorporated into the bridge, which are expensive.

Measuring the vibrational frequencies of bridges has previously been used to identify bridge damage and deterioration, but the data to support this approach have been limited.

Publishing their work in the journal Nature Communications Engineering, a team at MIT developed an Android-based app that collects data while travelling across a bridge which they compared with traditional bridge-based sensors.

“As data from multiple trips over a bridge are recorded, noise generated by engine, suspension and traffic vibrations, [and] asphalt, tend to cancel out, while the underlying dominant frequencies emerge,” said Dr. Paulo Santi.

In the case of the Golden Gate Bridge, the researchers drove over it 102 times with their devices running and they used 72 trips by Uber drivers with activated phones as well.

They then compared the resulting data to what had been collected by 240 sensors that had been placed on the Golden Gate Bridge for three months.

Results showed that data from the phones converged with that from the bridge sensors. For 10 particular types of low-frequency vibrations the engineers measured, there was a close match, and in five cases there was no discrepancy between the methods at all.

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However, because most bridges are not suspension bridges the researchers decided to test their method on smaller and more common concrete span bridges.

To do so, they studied a bridge in Ciampino, Italy, comparing 280 vehicle trips over the bridge to six sensors that had been placed on the bridge for seven months.

Here there was a 2.8% divergence between what was recorded with the stationary sensors and the smartphone data, while shorter trip numbers created more divergence, suggesting more trips would create less.

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Architecture Professor at MIT Carlo Ratti said there are ways to refine and expand the research, for example by accounting for the effects of the smartphone mount in the vehicle and the influence of the vehicle type on the data.

“We still have work to do, but we believe that our approach could be scaled up easily — all the way to the level of an entire country,” said Ratti.

“It might not reach the accuracy that one can get using fixed sensors installed on a bridge, but it could become a very interesting early-warning system. Small anomalies could then suggest when to carry out further analyses.”

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