How MTI tracks social distancing efforts with the AWS Cloud and big data

Maryland Transportation Institute (MTI), an interdisciplinary research and education organization based out of the University of Maryland, focuses on solving complex transportation problems. For the last five years, MTI has leveraged anonymized smartphone data to understand how Americans move, including mapping public transportation usage and monitoring traffic and congestion.

When COVID-19 hit, MTI was presented with an urgent new problem. Traveling had become a public health risk—and transportation data could reveal the impact of stay-at-home orders on viral transmission. Suddenly, the organization was tasked with gathering, processing, and reporting daily transportation data from nearly 65% of the US population. To keep the public safe, they needed more computing power—quickly. They turned to the Amazon Web Services (AWS) Cloud for a solution.

Using travel data to measure the effectiveness of social distancing

MTI has a long history of delivering mobility data to both the Maryland and the US Department of Transportation (DOT) as part of its mission to help government officials make better investment ­­­decisions around transportation and infrastructure. But COVID-19 presented a new and much more complex transportation challenge. With strict social distancing guidelines in place in many states, the DOT needed to know whether people were complying with regulations to stay at home, and how travel impacted COVID-19 case counts.

“We suddenly needed a way to compute the data metrics very quickly,” said Dr. Chenfeng Xiong, big data and cloud lead for MTI’s COVID-19 Impact Analysis Platform. “And our stakeholders’ needs were very urgent and short-term. Where are people traveling to? What if there is a big sporting event? How does this impact COVID-19 outbreaks?”

To solve this, Xiong and his team envisioned a platform that would deliver mobility data to their analysts in real-time. They already had access to privacy-protected raw data from mobile devices, but processing hourly location data from nearly 200 million people is a challenge. The new project would require MTI to analyze trillions of records every day, and their current on-premises servers weren’t up to the task. To realize the COVID-19 Impact Analysis Platform, MTI began researching new, cloud-based solutions that could scale to meet their requirements—and which they could build fast.

Launching the COVID-19 Impact Analysis Platform with AWS

The COVID-19 Impact Analysis Platform required three things: data transfer, data processing, and time. The organization had to transfer trillions of anonymized cellphone data records quickly and seamlessly from their data vendors each day, and then create an infrastructure with the processing power to analyze those records in real-time. While other cloud providers were able to handle several of the challenges, AWS offered the fastest turnaround with the best outcome.

“Our project was time-sensitive,” said Xiong. “We needed to get the analysis out as quickly and accurately as possible. And if we stacked other devices to do this on-premises, it would take lots of time and be very clunky.” Xiong estimated that processing that much data would have taken months in their on-premises system—something that takes only days with AWS. “We explored many options, and AWS was the quickest and easiest solution to create a robust computing platform,” Xiong noted.

Xiong and his team relied on Amazon Simple Storage Service (Amazon S3) to build their platform, which can scale virtually infinitely to meet their expanding data requirements. And because MTI’s data vendors also rely on Amazon S3, the team was able to build a data pipeline that filtered raw data directly from their vendors into their data analysis system. Once they had the raw data in hand, the team then used Amazon Elastic MapReduce (Amazon EMR) to process the information quickly and cost-effectively. The organization also leveraged Amazon’s spot-pricing system to optimize their costs—an essential consideration for a publicly-funded research organization. As an additional benefit, the team knows it can now scale its infrastructure to accommodate future projects in the cloud.

Monitoring international travel

Since its launch, the COVID-19 Impact Analysis Platform has been instrumental in helping decision-makers and government leaders keep the American public safe. Thanks to the platform, officials have been able to track how social distancing compliance is impacting hospital capacity, unemployment rates, and even case counts for vulnerable populations like senior citizens.

Recently, MTI received a grant from the National Institute of Health (NIH) to bring similar mobility informatics to African countries. In their partnership with NIH, the data-processing platform will be used to understand international travel and mitigate the spread of infectious diseases. The team also plans to embrace cloud computing technology to help the Maryland DOT investigate a recent increase in pedestrian and bike fatalities. Their data would focus on “vulnerable road users,” including walkers and bikers, to help municipalities determine how new infrastructure—like crosswalks, bike paths, and traffic lights—can improve safety.

With so much processing power at their disposal, Xiong and the MTI team can focus on their mission to leverage transportation data to improve quality of life and conduct other groundbreaking research. And that research is driving further cloud adoption. The team is currently expanding their cloud infrastructure so they can replace the DOT’s household trip data, which was previously gathered via time-consuming manual surveys, with cellphone mobility data.

“No one in academia has done this kind of work before,” said Xiong. “This development goes way beyond just transportation research. It is highly multidisciplinary. This technology could benefit public health, the social sciences, economics, and many other fields. I am looking forward to learning how other AWS tools can continue to expand our knowledge—and our capabilities.”

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