Preparing for the Next Hurricane Irma, or Harvey: How Analytics and Smart Cities Will Help

11/07/2017 10:17 am ET
Smart cities could use IoT data to mitigate weather events and climate change.

The United States has sustained 15 separate billion-dollar natural disasters in 2017, proving to be one of the costliest recovery years on record. How can cities make sure that going forward, their citizens remain safe and their odds of expensive disaster mitigation go down?

In the age of smart cities, the answer is data.

Information streaming from more than 1.6 billion smart devices and a wealth of relevant open-source data sets on weather, location and energy use are available to cities today. The problem is that many times this data lives in siloes — unable to be easily blended together to prepare and respond to disasters. To be effective, these silos need to be broken and the data made fluid and accessible.

If managed properly, smart cities can use this data to manage disasters after they happen and mitigate the effects of future disasters before they occur.

Enabling Real-Time Decisions

For centuries, cities have relied upon decades-old static maps to gain an understanding of which parts of a city might flood, says Javier de la Torre, CEO of CARTO, a location intelligence company. But now nearly everyone has some sort of location-identification device in their pockets — be it a cell phone or a chip on a credit card. This information, coupled with data like Google Earth, which is at most three years old, could help cities get a more up-to-date idea of how to either respond to a natural disaster or mitigate the effects of one before it occurs.

“We understand a hurricane map needs to be updated in real time so we know exactly where it’s going to hit, but that doesn’t happen on the preparedness side,” says de la Torre. “Instead of basing your analysis on where the vulnerable communities were 10 years ago, you can use yesterday or today’s data to get a better answer to the questions that you are asking.”

Having real-time generated reports can help cities determine where their citizens have relocated after an incident and also provide valuable information in the weeks and months after a disaster strikes, like which parts of town have increased commerce versus which areas have been economically erased.

The key to getting people to understand the value of location information in a disaster is how it’s visualized, says de la Torre. It can help policymakers determine which parts of a city are more at risk, so they can better outfit future building projects with the necessary equipment and technology in those regions. It can also help insurance companies better gauge what premiums are appropriate for which neighborhoods.

“It’s fundamental for people to be able to take action. It lets you be transparent, respected and supported,” says de la Torre.

Managing Smart City Data to Mitigate Future Disasters

But getting actionable insights from data is a challenge. As smart city devices continue to come online, potentially growing to nearly 10 billion by 2020, according to Gartner, understanding how to manage the myriad data sets involved will take explicit planning.

Cheryl Wiebe, a practice lead for advanced analytics at Teradata, says when disparate data sets can’t properly interplay, it often leads to real-world disconnects in how the city manages its assets. For example, a city could neglect to allow data that is used from operating its smart trash collection to blend with information on disaster-related road closures, which could lead to bottlenecks, or even dangerous situations.

“Unfortunately, cities have not taken a system-of-systems approach to plan for integrated, so they have siloed data,” she says.

For cities to successfully plan out their data architecture, Wiebe recommends a sandbox approach, where data scientists take a mix of data sets to extrapolate how to best blend them while remaining sensitive to data security and privacy. The sandbox could be the first piece to a tiered strategy, where private or personally identifiable information sits walled off in the middle, surrounded by proprietary or owned data that is then encapsulated in public-sector or open-source data — the sandbox.

The resulting blended data can not only help city administrators make decisions based on real-time data, but also allow them to predict how future scenarios will play out.

“When we have a pattern, we can collect all aspects of data and do a forensic study,” Wiebe says. “That’s a valuable asset to train models and predict things in the future.”

As cities continue to adopt Internet of Things devices at a rapid pace, they will have to create a strong governance system around the data streams they use, so as to treat the data as an asset. If done properly, it will enable them to take advantage of powerful new data sets, like location data, so these smart cities can make real-time, informed decisions. In light of the many disasters in the past few months, both in the United States and around the world, cities that partner with companies specializing in extracting actionable insights from data will be in the position to protect their cities and citizens when they are most vulnerable.

Follow Alisa Valudes Whyte on Twitter: www.twitter.com/MerrittGroup

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