Amid accelerated innovation in fields like artificial intelligence, IoT, and data analytics, the smart cities movement has picked up momentum in recent years. With 68 per cent of the global population set to live in urban areas by 2050, according to United Nations estimates, the push to make the world’s cities more connected, efficient, and citizen-friendly comes at an opportune time.

Big data lies at the heart of smart city innovation. Drawing on data from connected devices, public agencies, private citizens, and more, cities will be able to optimise their operations and effectively manage change as more and more people call them home.

The payoff will be significant. The McKinsey Global Institute calculates that smart city technologies have the potential to boost key urban quality-of-life indicators by 10 to 30 per cent. While the benefits of smart cities will be far-reaching, three areas in particular – traffic management, public safety, and infrastructure maintenance – attest to why data-driven innovation is crucial to the future of urban life.

Intelligent traffic management

• What are Smart Cities? Everything you need to know

Talk of transportation in the smart city often centres on the distant prospect of autonomous vehicles, but cities are already harnessing data to deliver big improvements in urban mobility. This trend will only accelerate over the coming years, with revenue from traffic-focused smart city technologies more than doubling from $2 billion in 2019 to $4.4 billion in 2023.

Data collected by IoT sensors and CCTV cameras, for instance, can be utilised to help city planners address bottlenecks, make traffic flow more efficient, and reduce congestion. Citizens also benefit from open data: With real-time access to traffic information, for instance, commuters can better plan their journeys and avoid congestion. 

Traffic management platforms already exist that combine data from public agencies, connected cars, camera feeds, IoT sensors, mobility apps, and many other sources – just one example of how the intelligent use of big data can not only enable better traffic management, but also save lives.

From cameras and sensors that can monitor parking availability, to traffic lights fed data in real time to facilitate more efficient traffic flow, big data is fuelling a new wave of transportation innovation – and while such solutions are a boon to city officials and municipal planners, the end users – ordinary citizens – are the biggest beneficiaries.

Promoting public safety

• What makes smart cities, smart?

Public safety is on track to be a major growth market for smart cities, with forecasters calling for the market to reach $295.98 billion by 2023.

What does public safety technology look like in practice? It’s the use of GPS data to find missing persons. It’s the collection of data from IoT devices and sensors to feed vital information to emergency responders for more accurate dispatching. It’s the deployment of AR-equipped drones that overlay critical information for emergency responders, allowing for more effective search-and-rescue operations during major events like the California wildfires.

It’s also the use of data-driven policing – through heat maps, gunshot detection technology, smart cameras, and more. Such use cases have sparked fears of Big Brother’s encroachment, and while it will be crucial to balance civil liberties and public safety, smart city planners can’t afford to lose sight of the promise of big data for public safety. McKinsey projects that smart city public safety solutions can reduce fatalities by up to 10 per cent, crime incidences by up to 40 per cent, and emergency response times by up to 35 per cent.

Managing smart cities’ infrastructure

• How smart cities can underpin our drive to a sustainable world

Population growth and climate change will both pose significant, overlapping challenges to cities’ infrastructure over the coming decades – but big data can help city planners adapt.

Monitoring hard-to-reach areas, drones can generate rich, actionable data to guide decisions on infrastructure repair and maintenance, thereby preventing potentially deadly structural deficiencies from going unaddressed. We have all seen the catastrophic damage that can be caused by an oversight of dam maintenance — vulnerabilities that will more likely be caught with the use of smart data to monitor and check for anomalies.

Beyond damage prevention, the use of data not only keep structures physically sound, but also keeps cities’ arteries pumping. Supply chains depend on smooth roads, sound bridges and well-functioning trains — without them, economies go into freefall. Utilising data, governments can ensure these lifelines’ long-term integrity.

Data on resource availability, supply and demand, and climate will enable smarter electric grid management, as IoT devices feed operators information in real time to drive more intelligent decisions about supply management during both peak and off-peak hours.

For municipalities aspiring to be truly smart cities, having a robust data strategy in place is paramount. The data they use to streamline and optimise their operations must be rich and abundant – which is why city planners must take a holistic approach to data collection and sharing. This will entail public-private collaboration and continued investments in analytics capabilities. When cities commit to this approach, they’ll be significantly smarter – and their citizens will be much better-off.

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An insurance start-up recently settled a claim within a few seconds. Another insurance-tech company offers insurance based on selfies! Sounds futuristic, or fake? It isn’t, it reflects a better future for both people buying insurance and companies offering risk products. Like food delivery, banking and cab- hailing apps, technology – or more specifically – artificial intelligence, is set to disrupt your insurance buying and settlement experience, forever.

The good news is that this disruption is likely to be hugely advantageous for you. The better news is that it will also be a win for insurance companies. It will save them money, help them assess risk more accurately, prevent damage before it happens and process your claim very fast.

Understanding AI and Life Insurance

If all this sounds too complicated, consider this. What if someone says that Mr Gupta is like Mr Subramaniam, who, in turn, is like you? Let’s narrow things down a bit more. In the eyes of your insurance company, your neighbour – whose weekend binges are legendary in the neighbourhood – is the same as you, someone who doesn’t drink or smoke. Sounds unfair, right? This may be a bit of a stretch, but, it does reflect reality. In the absence of enough data about you or every individual whose risk they cover, insurers run analytics to aggregate people into risk groups. They then charge a similar premium from each risk group. This is advantageous to those who take more risks in life and
disadvantageous to those who end up paying an extra premium even though they live relatively safer lives.

Let’s consider more scenarios. An honest family that has suffered a tragedy wants to claim the assured amount on term life insurance – a product that these days provides a big safety umbrella for a reasonable premium. This honest family wants the claim to be processed fast to tide over a looming financial crisis. However, insurance companies can take a few days’ time, and this is not because they do not want to settle the claim. The companies take time to assess if the claim is fraudulent – the industry faces several dubious claims each year. As a result, even honest claims take time to be disbursed.

Let’s take another scenario. What if the site of an accident or specific actions post an incident are critical to how a life insurance company pays out the claim? What if there were help at the time of the accident or real-time assessment of the incident to not only process the claim faster, but also assess damage more accurately? Sounds good, right?

How artificial intelligence works?

Artificial intelligence through a variety of tools – right from machine learning to text analytics to video/image analysis is all set to address the problems mentioned above and many more. For instance, the availability of more data about you – through wearable devices such as fitness bands or sensors in your car/home or even more data through ‘smart city’ technology will help insurers come up with a more realistic assessment of you and the circumstances around you at a given point of time. This can also happen through data mining of your social data and medical history. This is great news because if you live a safer life, don’t drink or smoke, exercise regularly and don’t indulge in risky behaviour like driving without a seatbelt, the insurance company would be able to offer you the same cover at a much lower cost.

The same applies to the settlement of life insurance claims. There is the possibility of insurance companies using drones for quick assessment of an accident site to judge the circumstances for a claim. Smart devices can warn a user about a riskier situation even before the insured enters one. The ideal scenario for any family is to not reach a stage where tragic circumstances require an insurance claim. More data and connect with you through IoT (Internet of Things) devices, image recognition, video analysis also help establish identity, thereby considerably reducing the possibility of fraud in insurance claims. This means, faster processing of claims, something good for a grieving family.

What more data – specific to you – means is that no proxies are used for you to evaluate the risk you face. It also means that the insurance buying experience itself becomes smoother. Ultra-smart chatbots can now engage in conversation with you, answering unending questions specific to you, perhaps much better than an old-world insurance agent. Personal identity can also be verified much faster helping you sign up and take an insurance policy online, in a few minutes. The great thing that it will bring is the evolution of insurance products specific to a need – in the world of auto insurance, for instance, artificial intelligence will enable the concept of pay-per-mile car insurance.

The bottom-line

All this is also good news also for insurance companies, which, in turn, can be good news for you. A more accurate assessment of risk will help insurance companies charge more or avoid clients with higher risk profile – thereby saving more money to cover you. Lower fraudulent claims again leave more money for you in the insurance pool. Faster processing of insurance purchases and claims saves insurance companies money, that can translate into lower cost of premiums.

All this use of artificial intelligence, of course, will take some time to come. But, this future is not very far away or unreal. What we are looking at is a complete disruptive transformation for both the insured and the insurance company. What could be better than technology enabling this win-win situation?

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Artificial intelligence, or AI, a term that a few decades ago circled around in the realms of sci-fi and fantasy, is a reality today. The most evolved AI of our fantasy tales is often sentient machines scheming to take over the world. We are not there yet, and perhaps reality is far more benign than our imagination.

AI, as we know today, has the potential to provide solutions to many of our real-life problems. In India, which is the world’s fastest growing major economy and has the second largest population in the world, AI can be transformational.

With the publication of a discussion paper on AI by the NITI Aayog recently, the government has not just signalled its priority to this disruptive technology, but also thrown it open to the public for ideas and suggestions.

One of the problems requiring urgent attention, where AI can demonstrably make an impact, is urban infrastructure, and here we have taken the first key steps with Smart Cities Mission. Our scorching pace of urbanisation means India is no longer a nation of villages. Every minute an estimated 30 people are moving out from their village, lock, stock and barrel, to become city dwellers. According to some studies, around 40% of the Indian population will be living in cities by 2030.

The question is: Do we even have the cities to accommodate this gigantic population? Experts say we will need at least 500 new cities to house our urban citizens or risk turning the existing ones into unmanageable slums.

Already, our metropolises that were planned at a time when resources were abundant and urban living was a luxury not necessity, are bursting at the seams with their hopelessly inadequate infrastructure and lack of planning. And while we have been extremely reluctant urbanisers, the late start has given us some significant advantages, one of which is the use of technology to leapfrog stages of development.

Across the world, cities are using technologies to become smarter, in the sense they are using it to manage key functions horizontally—city services, transport, communications, water, smart grids, public safety, education and health—all through a digitally-managed central command room. The government has embarked on an ambitious plan to turn 99 of our urban clusters into smart cities with an expected investment of `2.04 lakh crore. The strategic components of these smart cities include city improvement, renewal and extension, in addition to a pan-city initiative in which smart solutions are applied covering large parts of the city. Many have already begun implementing projects involving smart command and control centre, smart roads, solar rooftops, intelligent transport systems, smart parks, etc.

While these ‘brownfield’ cities are being retrofitted, we have ‘greenfield’ cities being built up from scratch under the Industrial Corridor programme. Creating a brand new smart city requires a comprehensive, long-range plan to direct the future growth and development of the entire area. For these greenfield cities, some of which are bigger in size than the country of Singapore, we don’t just have physical master plan, but, for the first time, it is dovetailed with a digital master plan to manage, operate and control all citywide utilities through one command and control centre.

The challenges of developing brownfield cities are different from greenfield cities, but common to both is the understanding that technology, especially emerging ones like AI and Internet of Things (IoT), will be the cornerstone of realising India’s aspirations of building the ‘intelligent’ cities of tomorrow. The basic premise of AI is the development of intelligent machines that are capable of high-level cognitive processes like thinking, perceiving, learning, problem-solving and decision-making. You provide the system with lots of data and get actionable intelligence in return; for example, in the way Netflix or YouTube gives you suggestions based on your browsing patterns.

Cities of today are sitting on goldmine of useful data, churning petabytes of it daily through video cameras, sensors, traffic management systems, smart meters, vehicles and mobile phones. AI has the potential to make sense of the humongous data and use the intelligence to increase performance of cities, optimise operational costs and resources, and enable sound citizen engagement.

For a smart city operation, the basic ICT functions include collection of data, say using sensors, CCTVs, smart energy meters and even social media engines, for real-time human activity. This would be relayed through communication systems like fibre optics, 3G/LTE, internet, Bluetooth. The data would then need to be analysed using AI and other tools, and the intelligence generated used to direct decisions and actions.

How can AI be potentially used in smart cities? The answer is, in countless ways. For instance, for management of traffic that has become the bane of many cities today—AI can understand real-time traffic, calculate permutations in a flash, process data at local level of traffic junctions, and even turn traffic lights off and on intelligently.

Public safety and security is enhanced by AI through sophisticated surveillance technologies, accident pattern monitoring, linking crime databases, combating gang violence and so on. AI can help with crowd management, estimation of size, predicting behaviour, tracking objects and enabling rapid response to incidents. It can be invaluable for managing utilities and optimal use of resources such as distributed energy and water. AI can lead to smarter homes with resources-saving applications and easing domestic workloads. It can greatly ease citizen services delivery, processing of files and applications, through chatbots for responding to enquiries with smart conversations. These bots can free up operational staff at help centres to address more complicated and time-sensitive queries.

An inevitable outcome of digitisation is cyber-attack and cyber-crime, targeting sensitive and personal data, which again AI can help manage to some extent by detecting vulnerabilities and taking remedial measures automatically. AI can similarly assist in numerous other city functions to improve public accessibility, including maintenance of outdoor spaces, lighting, parking management, learning, education, skill development and so on.

Technology can be a great enabler in achieving our primary goals of a smart city—protecting citizens and planning for the future; building a sustainable, resilient infrastructure that optimises resource use and ensures essential needs of all are met; and enhancing the quality of life of citizens, enabling individuals to improve their health and productivity.

But while we do have the advantages of access to a rapidly evolving technology ecosystem, there are other challenges we need to overcome. One of these is coordination between stakeholders—residents, administrators and operators. With AI, data sharing and a well-defined activity chain will be essential for efficiency. Large migrant populations in cities may skew data, so we will need to adjust a number of variables. For example, apart from actual ingress of people, increasing business activities, infrastructure expansion easing connectivity, community exchange must also be analysed.

A more technical issue with data-reliant decision-making is the accuracy of the data itself. We need to bring in a robust standardisation system for accurate data inputs. For example, in detecting wearers of safety helmets among bike riders without proper standards for helmets, AI will count as positive even those that are not approved by law. Also, ICT infrastructure requires uninterrupted network, power and regular maintenance. Difficulties remain with relation to costs, getting people with domain expertise and end-to-end solutions for this level of work.

The Smart City model has never been implemented on this scale in any part of the world. Many systems have been adopted and implemented in silos, but all the functions of the city have never been integrated right from scratch. It is an exciting new challenge for India; we could be creating new models for future cities and setting benchmarks for urban infrastructure.

The government has steered this mission in the right direction; the budget allocation for Digital India—the government’s umbrella initiative to promote AI, machine learning, 3D printing and other technologies—was almost doubled to `3,073 crore ($477 million) in 2018. Roping in the private sector, especially Indian companies that have a solid technological expertise, to shape the overall AI strategy would be a good move.

A standardised ICT infrastructure for seamless integration—state and countrywide—is essential. Start-up companies may be given access to data so they can create business models around use cases, helping both government and start-ups. What is important this time is we make a start somewhere. In many ways, public engagement is also critical for this mission since our talent, skills, creativity and ideas are largely invested with our people.

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