Data meets Darwin - urban life is evolving

Adaptation runs like a thread through Charles Darwin’s theory of evolution. And by extension, through the history of life. Over the millennia, the species that have survived and thrived are those that have adapted best.

Now cities are evolving too, and technology and data are driving the transformation.

‘Smart city’ is still an elastic term, and there are many definitions.

Yet a common factor is the ability to use technology to exploit data, which provides a robust, resilient and dynamic environment that can adapt to the changes that are likely to be out of our control.

When we think about a smart city, the immediate thought goes to technology – utilising the ‘Internet of Things’ (IoT) for smart cities to gather data to do ‘something’ with. But technology is an unknown; we don’t fully understand what emerging technologies (automation, Artificial Intelligence (AI), robotics, etc) will do for our built environment and how they will affect the way our cities ‘live and breathe’.

Technology will ultimately connect our people to places and spaces, we just can’t accurately define how and what the interaction looks like. So why focus on the unknowns and instead focus on the knowns?

We know that there will be an increased reliance on drinking water and our natural resources, transportation, communications, energy and food. Our world is experiencing more extreme weather which will drive migration; we are living longer yet becoming more sedentary – this determines how a city can truly call itself ‘smart’. Smart is about the ability to be able to support and adapt to these changes, which will undoubtedly require technology and will certainly require data.

Data is a smart city’s lifeblood, collected by thousands of remote sensors dotted across the built environment – placed on everything from roads, runways and railways to bridges and buildings – and connected through the IoT.

Individual smart cities prioritise how their data is used in different ways.

While there are some recurring themes – from improving residents’ quality of life to boosting security and sustainability – no two locations face the same challenges. As a result, one smart city shouldn’t follow another’s model.

One size does not fit all

Technology can deliver multiple benefits at once. One trailblazer, Barcelona, first launched a smart city strategy in 2012, offering global tech companies a testbed for innovation. This approach spurred foreign investment in the city and kick-started the economy, while the data gathered enabled authorities to make better decisions and boost efficiency.

The city’s strategy has now evolved to focus on ground-up innovation to empower citizens and boost living standards. For example, in the densely populated, historic districts that underpin Barcelona’s popularity as a tourist destination, residents’ lives have been dramatically improved by the use of smart bins, which reduce smells and noise pollution, as well as providing real-time data to optimise waste collection.

But that’s just one area and having ‘something’ smart, doesn’t mean it’s a smart city.

Meanwhile, in sparsely populated Iceland, smart technology has been used to strengthen transport connectivity and reduce carbon emissions. The capital, Reykjavik, has added IoT sensors to its entire public transport network and launched a popular car sharing programme, giving inhabitants access to real-time journey information through an app. Again, it’s a start.

Driven by smart city data, today and tomorrow

AI is increasingly being used to process the reams of data smart cities produce – and the results offer a front-row seat on not just current challenges, but future ones too:

• Climate change: Rising temperatures and sea levels, and more frequent extreme weather events, all pose serious risks to technology, transport infrastructure and people. How does our built environment protect itself and provide resilience?
• Migration and demographic change: Rapid population growth will stretch cities’ housing stock and residents’ access to food, water, basic infrastructure and natural resources.
• Health: Ageing populations in the developed world will amplify labour shortages and increase pressure on healthcare providers, mobility and access for all.

The data yielded today is being used to model the way these long-term threats will impact each smart city over decades. Such insights are already informing decisions over capital programmes that will shape the built environment – and its capacity to adapt to change – for generations.

And that’s just the start. Soon AI technology will enable smart infrastructure to respond autonomously to both scheduled and unscheduled events. Eventually, authorities will be able to use the mass of data to build a ‘digital twin’, a 3D, real-time virtual mirror image of the physical city that will allow them to make critical decisions in response to live conditions.

Connectivity between the sensors is key. The first generation of smart cities often relied on fibre-optic cables, but 5G is now emerging as a more economic and scalable alternative. But there is likely to always be a place for fibre. 5G has its limitations which are increased when working in a densely populated built environment.

Soon aspiring smart cities will bristle with 5G repeater transmitters, and network providers are joining forces in innovative partnerships – such as that led by the UK’s Mobile Broadband Network Limited – to accelerate rollout. As our buildings become more efficient to keep them warm or cool, these same requirements can hamper the performance of 5G.

Maximum potential, managed risks

Security is no less important. Utopian dreams of a city’s entire data lake being made available to all, for the common good, need to be weighed against the danger of it being misused.

GPS time, the measure many IoT sensors use to pinpoint their presence at a geographic location at a certain time, can be ‘spoofed’ by hackers. It doesn’t take a feat of imagination to envisage the mayhem that would be caused by a cyberattack on a smart city’s entire network of traffic lights.

Equally, authorities must take steps to ensure any personal data they collect is kept securely.

In Europe, the General Data Protection Regulation (GDPR) rules give clear guidance on how this should be done and the UK has gone further by publishing a number of Publicly Available Specification (PAS) documents about how smart cities should be conceived.

We played a lead role in the drafting of PAS 185, which gives smart city authorities a blueprint for managing security risks. Like smart city technology itself, the approach to security needs to be city-specific and PAS 185 details strategies that are both appropriate and proportionate to the risks. We have also been instrumental to the creation of PAS 186 (Smart Communities); likely to be launched early 2020.

While no system can be 100 percent secure, mitigation measures that incorporate multilayer redundancy can go a long way to isolate and minimise risk.

Knowing what connects to what, for what and why is key to providing resilience and redundancy.

In many ways, the same can be said for the idea of smart cities as a whole. Whatever issue they seek to address – from extreme weather events to the need for greater energy efficiency – the smartest cities are those that can securely gather the data using technology systems to be able to proactively adapt and futureproof themselves.

However, as the technology develops, true smart cities will harness it to achieve their individual goals and cement their evolutionary advantage – the ability to adapt.