Sometimes, the most effective urban smart-tech is the least glamorous. Deep below ground in Kansas City, Missouri, technology is helping to upgrade a 150-year-old sewer system to modern standards. The cost is modest, there is no personal data at stake to upset privacy campaigners and the tech company involved is based more than 2,000 miles from Silicon Valley.
The project is a low-key but effective example of the smart-city movement, where modern data science is improving the operation and services of cities for residents. In 2010, after 1,300 illegal overflows in eight years had released untreated sewage from the city’s network into the Missouri River, the federal Environmental Protection Agency lost patience and ordered the city to spend $2.5bn over 25 years to clean up its act.
Andy Shively, the man in charge of the upgrade, is proposing to use spare capacity at times of high rainfall, redirecting water from spots where levels are dangerously high to those where they are low, and reducing the frequency and scale of overflows. This would save the costs of digging additional sewers and pumping facilities.
Turning Shively’s theory into practice is EmNet. Spun off from a research group at the University of Notre-Dame, Indiana, the company is employing military sensor technology that was used for tracking Taliban fighters through caves in Afghanistan, to monitor water levels in sewer networks.
Kansas City’s sewer work is a far cry from the typical smart cities’ project, where inflated promises often deliver questionable benefits. “How many dockless bike-sharing providers does London actually need?” asks Philipp Rode, who runs LSE Cities, a research unit at the London School of Economics.
He points to the boom-bust story of app-enabled bike-sharing in China where 77 companies — some backed by the country’s largest tech firms — had supplied 23m bikes by 2017. For some, the business model — subsidise early users; achieve a dominant market position; ramp up prices to create big profits — has backfired. One company, Bluegogo, shut down in 2017 before being acquired by ride-sharing company Didi Chuxing.
“Cities are becoming graveyards of tech junk that no one could find a business case for,” says Gemma Galdon Clavell, founder of Etticus Research & Consulting, a data ethics consultancy in Barcelona. But real smart-city success is often low-key.
It may mean no more than widening access to services, says Thomas Madreiter, Vienna’s head of city planning. “The real social gains for today’s cities are to be found from the deployment of existing technologies rather than employment of new ones.”
“The tech side is too often hyped,” agrees Rode. “Real innovation happens beyond the engineering: how does the kit connect with people, institutions and our routines?”
In value-for-money terms, it is hard to beat the modest business of LED street lighting. Switching traditional streetlamps to LEDs typically pays back capital investment in around 18 months, says Duncan Wilson, professor of connected environments at University College London. After a little over a decade, the conversion of Los Angeles’ streetlamp network to LEDs is nearly complete, with 90 per cent of the 220,000 lamps transferred, energy use cut by roughly two-thirds, and cost savings running at $10m per year, according to city authorities.
“Network connectivity, so street lights can be controlled centrally, saves roughly 10 to 20 per cent of costs,” says Eric Woods of Navigant Research, an energy research company in London. Much of this comes from maintenance savings, he says — teams need no longer to scour the streets for faulty lamps — as well as the benefits of centralised controls for one-off projects, such as major sporting events.
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Back underground in the US, the Massachusetts Institute of Technology is sending robots into Boston’s sewers to improve the detection and treatment of disease. At wastewater plants, testing detects between 15 and 30 per cent of microbes originating from human waste, says Fábio Duarte of MIT’s Senseable City Lab, who is leading the research. Sending the lab’s robots into a neighbourhood’s local sewer system increases this to 80 per cent, a three-year trial has found.
As well as being more accurate, the data are timelier. A local robot takes days to identify an outbreak of flu; the surge in attendance at local hospitals and surgeries typically takes weeks to register, according to Duarte. And because the information is local, the response can be too — a local vaccination campaign for flu among elderly residents, for example.
If he is right, the benefits would be far from modest: cost savings — and a healthier population.
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