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Singapore's smart city push cannot create Smart Nation without everyone's buy-in

Benjamin Cher and Trinity Chua
Benjamin Cher and Trinity Chua • 8 min read
Singapore's smart city push cannot create Smart Nation without everyone's buy-in
SINGAPORE (July 9): Housewife Doreen Tan is “brushing up on the use of computers” to prepare herself to be part of Singapore’s Smart Nation vision. But she is less comfortable about the zetabytes of data that the government and commercial organisati
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SINGAPORE (July 9): Housewife Doreen Tan is “brushing up on the use of computers” to prepare herself to be part of Singapore’s Smart Nation vision. But she is less comfortable about the zetabytes of data that the government and commercial organisations are collecting to create the smart city, an urban environment enabled by information and communications technology. “Everything they know; not so good,” she says.

Could her reservations prevent her from signing up for some of the schemes that mine her data for, say, improvements in municipal services? What, then, of other programmes making up the Smart Nation infrastructure? In November 2014, Prime Minister Lee Hsien Loong made a bold statement to turn Singapore into a “smart nation” by 2024. “Our vision is… a nation where people live meaningful and fulfilled lives, enabled seamlessly by technology, offering exciting opportunities for all,” Lee said in his speech at the Smart Nation launch.

In the four years since, data-driven proofof- concepts and pilot projects have exploded across the island state, from “smart” dustbins to “smart” streetlights. The latter will be fitted with sensors and cameras that can direct autonomous vehicles, catch errant e-scooters and identify suspicious objects/ people of interest for security reasons.

The Government Technology Agency (Gov-Tech) is developing the Singapore Government Technology Stack for public service agencies to build applications quickly with consistent user experience using a common infrastructure. Data such as utilities usage and housing transaction prices can be collated from applications built on the stack. “Aggregated citizen, business and location data gathered from the various public touchpoints is useful for the government in improving policies, operations and service delivery,” says a Gov- Tech spokesman.

Some of this data, such as the car population and public transport ridership, is available to the public online at data.gov.sg. The government hopes the information will be used in ground-up initiatives to solve national issues.

Meanwhile, local corporations and startups have been getting in on the smart nation action. For instance, Singapore Telecommunications works with HDB to analyse data from sensors on lifts and in common areas across up to 1,000 HDB blocks, to pre-empt maintenance problems.

“Smart Nation is about how we can improve productivity and living [conditions],” says Andrew Chow, president of the Singapore business and software systems group at ST Engineering Electronics. ST Electronics has a number of smart city solutions deployed in Singapore, from autonomous buses in Gardens by the Bay to screens on MRT trains that give updates on current and next stations.

Much to gain with big data

In theory, the collection and analysis of large data can be used to solve or pre-empt major challenges. “When you start collecting data, you get an idea of how the city operates and take away some of the pain points of the citizens.

Then you can think of how to address them,” says Mike Davie, founder of Data- StreamX and Quadrant Protocol. Data StreamX has a two-year partnership with the Infocomm Media Development Authority of Singapore to build a datasource platform for companies to tap. Life expectancies could even be improved by taking away stress points and providing better access to medical services, says Davie. A report by Mckinsey Global Institute, “Smart Cities in Southeast Asia”, found that smart city solutions could save 5,000 lives lost each year to traffic accidents, fires and homicides. Sensors could also save up to eight million manyears in annual commuting time.

That has Amit Divekar, chief technology officer at restaurant analytics platform Mobikon, excited. “Imagine this: You get into your car in the morning to drive to your office. A screen pops up informing you that rain has caused the usual route to become unfavourable, while calculations based on real-time information, on-ground traffic sources suggest an alternative but optimum route. And as you pull into the parking lot, it’s suggested you drive around the corner where lots have opened up, increasing your chances of finding a space,” enthuses Divekar. “On the way home, yet another notification informs you that although you’re not overdue on your annual road tax payment, there’s a drive-through tax station on your route that will save you a dedicated trip just to pay your taxes.”

Such a scenario is not yet possible here. Singapore has laid the foundation for a smart city future with initiatives such as the nationwide fibre network and the linking of all government services under the SingPass platform.

In the 2017 Global Smart City Performance Index commissioned by Intel, Singapore ranks first — ahead of London and New York. But other cities are catching up.

“Whenever I opened a government web page [in South Korea] and clicked on ‘medical’, I could see all my expenses. Within five clicks, I could see all the purchasing I’ve done in the last year that’s known to the government. [As a result,] I can get tax rebates,” Davie says. What does Singapore need to do to stay ahead?

Getting it right

Leslie Ong, country manager for Southeast Asia at data visualisation company Tableau, says the government has been a leader in data collection. He highlights the recently launched Digital Government Blueprint that will use data, connectivity and computing to transform services for citizens, businesses and public officers.

But the key to Singapore’s smart city ambitions is how large data sets are interpreted and used. Jason Loh, head of analytics for Asia-Pacific at SAS, says there is still a lack of local experience to implement major data analytics projects. “While many teams are increasingly equipped to identify potential applications of data analytics within each domain, many lack the experience to successfully implement major data science projects and struggle with the challenges of adapting from legacy technologies and policies,” he says.

The right questions must be asked too, says Loh. “When the real problem is well-defined, finding a solution is a matter of practice. It is important that organisations in today’s digital economy become adept at identifying the right data, asking the right questions and developing the right models,” he says.

There is already a push to equip civil servants with data analytics skills. The government has announced agreements with both Tableau and SAS, for one. “The most common use-case [is] fraud prevention,” Loh says. “A robust fraud analytics engine provides government agencies with the capabilities to detect fraud accurately, in real-time, and reduce fraud losses and false positives, all while decreasing operational costs.” For instance, the government is implementing a data analytics system to detect fraud in SkillsFuture claims.

Graham Ong-Webb, a research fellow at the Nanyang Technological University’s S Rajaratnam School of International Studies, says there must be further integration among data sets. One good example of this is the data sharing adopted by the Ministry of Health and Central Provident Fund Board, which extends healthcare financing and support based on Medisave, MediShield and subsidy levels. Improvements are still needed, though.

“We need [to innovate] to create the predictive analytics software that will allow us to sense new patterns and raise early-warning indicators from big data, which can provide the basis for early mitigation and support by government agencies, social workers and members of the community,” Ong-Webb says. “For the needed breakthroughs to occur, however, the public and private sectors, by themselves, cannot do it alone. It has to be a public-private-partnered-led undertaking,” he adds.

Ong-Webb also highlights ethical issues. “The critical concerns go beyond data collection to the black box of [artificial intelligence]-driven data analytics. As it stands, it remains difficult to audit the decision-making processes that AI software undertake in arriving at their analyses and predictions,” he says. “I am not saying that we should stop our technological initiatives in developing smart cities until the ethical issues are clarified and addressed; what I am saying is that we need to work on both areas in tandem.”

Ultimately, a key piece of the puzzle that the government might be missing from its smart nation initiative could be human rather than technological. “Any data initiative needs a buy-in from citizens. They need to understand the outcomes that can be,” says DataStreamX’s Davie. “It has to be about how the data can improve my life. That is lacking right now.

“As a society, we need to understand the implications of what we do. And as individuals, we need to understand our own actions. Sometimes, data can show us. The government has a responsibility to make the lives of citizens better, and that involves showing the impact of our decisions on ourselves,” he adds.

Singapore’s smart city is still a work in progress. Tangible benefits are not quite evident. Public transport woes still abound, along with increasing incidence of chronic diseases. Some have argued that advances in technology actually exacerbate social inequality, as there is unequal access to the devices that could make life better. Finally, concerns on data privacy, and the lack of transparency around how the data is used, create a one-way street that engenders suspicions and could eventually become a stumbling block to actual progress.

This story first appeared in The Edge Singapore (Issue 838, week of July 9), which is on sale now. To subscribe, click here

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