Smarter cities: why data-driven cities are the only option


As urban population growth continues to outpace rural, cities across the globe continue to expand. The UN estimates that over 50% of the world’s population now lives in cities. The UK predicts some 92% of its citizens to be living in cities by 2030.

This concentration of populations in urban areas – a global phenomenon – needs careful planning and forethought so that cities avoid overcrowding and remain liveable (or ideally, see living conditions improve).

For this improvement to be realised, we need to solve questions around urbanisation and new challenges centred around safety, mobility, efficiency, and community engagement. To address these challenges, city leaders are turning to the Internet of Things (IoT) and data analytics. Cities are currently undergoing a digital transformation that will revolutionise the way they are managed.


New and exciting mobile and static infrastructure technologies are enabling safer communities, new low-cost utility services, more efficient city operations, and intelligent low-emissions transportation systems. One example of a UK smart city is Milton Keynes which showcases driverless pods that ferry citizens along fixed routes across the city.

The term "smart City" can mean different things to different people, but most share some combination of the following objectives:

Safety and security: Reducing accidents, injuries, fatalities, and lowering emergency service response times.

Sustainability: Reducing CO2 emissions and other pollutants/contaminants to reduce environmental footprint and improve air quality.

Efficiency: Improving city operations, traffic and logistics flow to expedite emergency and infrastructure vehicles while reducing costs and deliver better value to citizens.

Equality: Creating ladders of opportunities for under-served or underprivileged areas; as well as providing opportunities for innovation

Engagement: Improving community engagement and social interactions.

Further to these "functional" objectives, smart city programmes will involve a large degree of technology implementation. This could mean anything from a simple public-facing downtown development map, to a complex deployment of sensors to track traffic patterns or a big data platform to improve traffic flow.

With the advent of connected and autonomous vehicles, cities will also need to consider data from vehicle to vehicle (V2V), vehicle to infrastructure (V2I) and vehicle to everything (v2X) communications. And to further complicate matters, most smart cities have to retrofit this technology into an existing landscape; but this effort is necessary as sensor data is critical to an effective smart city strategy – and when done properly, the rewards can far outweigh the preliminary cost and effort required.

A map of sensors

Smart city programmes involve mass deployments of sensors which are necessary to gather data to justify and manage change. While sensors can be very cheap, the deployment of these sensors can often be very expensive, especially at a city-wide scale.

But rather than deploying an entirely new network of sensors, cities and local authorities can improve efficiency by leveraging existing sensor networks to avoid expensive infrastructure investments.

Telematics companies may seem unlikely partners in this endeavour, but with some of the world’s largest organically grown vehicle datasets, telematics providers can grant access to aggregated data already blanketing cities across the globe – without the expense of building a sensor network.

Using advanced analytics and data science capabilities, telematics providers apply artificial intelligence and machine learning techniques to enrich this aggregated data and deliver actionable insights to cities and local authorities. These insights can be used to infer road conditions, identify dangerous stretches of roads or junctions, and predict traffic patterns to help manage traffic flow - to name just a few areas where data can be instrumental in smart cities.

For cities and their leaders, this data provides real-time visibility into city operations including:

Road Conditions

Cities can automatically identify potholes and other road degradation indexing using vehicle data. Aggregated vertical axis accelerometer data for instance, can be analysed in near real-time to show areas in need of road maintenance. This data can be integrated directly into a city’s public works and/or road maintenance departments for automated dispatching and work orders.

Traffic Flow and Safety

City management can determine the average speed on all city roads throughout the day, identifying traffic bottlenecks or roads where speeding is a problem. Identifying the most dangerous roads is the first step to improving safety. Traffic planners can monitor the effects of new signage and traffic-light scheduling in near real-time, and optimise traffic flow during roadworks.

Electric Vehicle (EV) Infrastructure Planning

Authorities can locate optimal charging station locations based on real EV traffic data, and capitalise on revenue-generation opportunities to extend the range of cities' EV fleets.

The Future of Urban Planning

There is little doubt that the smart city revolution has begun. Many of the world’s biggest and most advanced cities are already adopting new policies that will position them for efficient and sustainable growth, based on data.

Telematics and related connected car technologies will be key enablers to this revolution, used to collect the necessary data to catalyze and manage change – ultimately preventing cities from being forced to spend on costly deployments of sensor networks.

These insights mean that today's cities can optimise urban planning and fast-track their progress towards smart city status.

Edward Kulperger ICD.D is vice president of Geotab Europe.

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