Aug 30, 2012 - 1:00PM PT

Managing sewage like traffic thanks to data

By Derrick Harris
GigaOm.com

http://gigaom.com/data/managing-sewage-like-traffic-thanks-to-data/


If you don’t spend a lot of time thinking about the design of your 
city’s sewer system, you’re not alone. If you’ve lived in South Bend, 
Ind., though, it might be a different story. There, heavy rain has sent 
sewage overflowing into the St. Joseph River and backing up into 
basements in the old part of town. Until data came to the rescue.

However, South Bend’s sewer situation is just a microcosm of the woes 
facing cities as they continue to grow — the planet is estimated to have 
9 billion people by 2050, and much of that growth will happen in urban 
areas. Traffic congestion, air pollution, crime and just general 
inefficiency are among a host of problems that plague growing cities and 
that, data suggests, actually grow at a faster rate than cities 
themselves. As we’ve reported numerous times over the past few months, 
however, big data — from Xerox’s traffic-management systems in Los 
Angeles to disease-predicting models in New York — is increasingly 
looked at as part of the answer to many of these problems.


South Bend’s sewage problem

South Bend’s problems stem from its outdated combined sewer system that 
mixes rainwater and sewage in the same pipes. Heavy rains mean waste 
isn’t easily diverted away from the river and to the sewage treatment 
plant; backups occur when large streams of water hit bottlenecks in the 
system. (A rather detailed explanation of the system, straight from the 
city (and written before the IBM engagement), is available here.)

Fixing the problem meant either spending $120 million on rebuilding the 
sewer system to add capacity, or spending a fraction of that, $6 
million, on several dozens sensors and a new software service to make 
sense of the constant data they’re putting off. South Bend chose the 
latter option, and it has proven to be a wise decision thus far.

According to South Bend Director of Public Works Gary Gilot, the project 
not only saved the city $114 million, but it also has reduced the number 
of sewage overflow incidents to 1 per year from 27 per year. The 
solution was a system that married 116 sensors (developed at the nearby 
University of Notre Dame), strategically dispersed throughout the 
500-mile sewer system, with IBM’s cloud-based Intelligent Operations 
Center software. The reduction in overflows also saved the city another 
approximately $600,000 in government fines.

With the sensor network and cloud software in place, the city can see in 
real time where problems are arising, as well as where there’s excess 
capacity. Armed with this information, city employees can intelligently 
divert sewage flows to ensure as much as possible makes its way to the 
treatment plant and as little as possible finds its way into people’s homes.

Gilot analogizes South Bend’s sewer evolution to the change from timed 
traffic signals to today’s signals that alter the timing of lights based 
on the flow of traffic: “We’re essentially taking something that’s been 
used for decades [in traffic management] and applying it to sewage 
instead of the flows of cars and trucks.”


Opening communication channels for data

But, like most cities, South Bend’s problems aren’t limited to sewers, 
and Gilot said he’d like to use data to solve some of the other ones. 
For example, he wants to connect data from the city’s water works 
department — which keeps tabs on which properties have water service 
turned on or off — with code- and law-enforcement data to cut down on 
vandalism and other crimes associated with abandoned properties. Knowing 
which areas have a disproportionate percentage of water-less properties 
will let those departments know where to focus their efforts, Gilot said.

Craig Hayman, general manager of IBM Industry Solutions, said his team 
is working with all sorts of cities to help solve their specific 
problems. In Rio de Janeiro, IBM is helping the city try to predict 
mudslides and prepare for both the 2016 Olympics and World Cup. In New 
York, IBM and the City University of New York are using the IOC software 
to analyze and monitor the city’s efforts around solar energy 
production. Elsewhere, IBM’s Smarter Cities team is working on 
everything from crime prevention to social services to, of course, 
predicting traffic.

Still, while big projects get the attention, citizens might feel the 
effects of municipal analytics efforts in much more mundane ways. Try 
going to city hall and getting a permit or doing anything that requires 
dealing with multiple departments, Hayman explained, and it can be a 
nightmare because most still operate in silos, disconnected both 
physically and digitally.

“This is very similar to the early days of the internet,” he said, 
referring to the pre-Web 2.0 and social web eras when data didn’t flow 
so freely between sites, service providers and applications. In five to 
10 years, though, Hayman thinks cities will operate much like the web 
does today, so while cities are saving money on operations, you’ll be 
saving time bouncing between departments as you try to get that building 
permit.

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