The expansion of big data and the rapid evolution of the Internet of Things (IoT) is helping to drive the growth in the number of smart cities around the world.
Governments around the world are looking at ways they can adopt and implement smart city solutions, all supported by big data applications. Smart city technology can be deployed to improve the performance of health, transportation, energy, education, water, and waste service, leading to better living standards for citizens and typically, a more sustainable city.
Big data analytics sits at the heart of smart city services. Most smart city solutions rely on connectivity and the ability to collect data to provide insights into the challenges faced by issues such as increasing traffic congestion, increasing waste and the strain on healthcare systems.
Big data offers the potential for cities to obtain valuable insights from a large amount of data collected through various sources, and the IoT allows the integration of sensors, radio-frequency identification, and Bluetooth in the real-world environment using highly networked services.
This combination of big data and the IoT is a major driving force behind the solutions that are turning cities into smart cities.
What is big data?
Before we take a closer look at how big data is being used to create smart cities, let’s first understand what big data is.
According to SAS “Big data refers to data that is so large, fast or complex that it’s difficult or impossible to process using traditional methods.”
Whilst people have been collecting and storing large amounts of data for a long time, the act of being able to analyse that data in a timely manner only really began to catch up in the early 2000s when industry analyst Doug Laney articulated the now-mainstream definition of big data as the three V’s:
Volume – Organisations collect data from a variety of sources, including transactions, smart (IoT) devices, industrial equipment, videos, images, audio, social media and more. In the past, storing all that data would have been expensive, making it unwarranted for many businesses. However, cheaper storage using data lakes and the cloud have made the storage of huge amounts of data more feasible and affordable, helping to accelerate the need for big data analytics.
Velocity – With the growth in the IoT, data streams into businesses at an unprecedented speed and must be handled in a timely manner. RFID tags, sensors and smart meters are driving the need to deal with these torrents of data in near-real-time. This is simply not feasible using traditional methods of analytics.
Variety – Data comes in all types of formats – from structured, numeric data in traditional databases to unstructured text documents, emails, videos, audios, stock ticker data and financial transactions. Being able to identify and analyse this data in real-time relies on big data analytics that can quickly process the data and, often using artificial intelligence (AI) make sense of the data and present meaningful insights in near real-time.
What are smart cities?
According to McKinsey “Smart cities put data and digital technology to work to make better decisions and improve the quality of life. More comprehensive, real-time data gives agencies the ability to watch events as they unfold, understand how demand patterns are changing, and respond with faster and lower-cost solutions.”
McKinsey highlights three layers that make up smart cities:
- Technology – this includes a critical mass of smartphones, sensors, RFID tags and smart meters that are connected by high-speed communication networks.
- Applications – in order to make sense of the data that is being collected and turn it into valuable insights for business and consumers, applications are required and this is where technology providers and app developers come in.
- Citizens and businesses – the third and final layer is the users themselves. In order for applications to succeed, they need to be widely adopted and manage to change behaviour. Apps encourage people to choose a different route, use less energy or water, or use preventative self-care to reduce the strain on healthcare systems. If people don’t “buy in” to the applications, nothing changes.
In essence, smart cities are helping to improve key quality of life indicators – the cost of living, safety, time, jobs, connectedness, environment, and health.
How can big data help to create smarter cities?
Whilst the potential to use big data to make cities smarter is huge, that potential can only be realised if the data can be converted into meaningful and actionable insights. There are, however, a growing number of examples of cities that have embraced the potential of big data and turned a city into a smart city.
Here are some examples of smart city solutions that benefit from big data:
Public Safety
One of the key driving forces behind smart cities is the desire to provide a safe and secure environment for citizens. Smart cities are using predictive big data analytics to identify areas that are prone to criminal activity and putting in place measures to tackle crime in those areas.
Historical data, along with geographical data and security camera feeds can be fed into analytical software to help predict crime hotspots and make more efficient use of police resources – sending officers where they are needed most. This is helping to create safer cities, reduce crime rates and cut down on wasted time for police.
Transportation
Another sector that is benefiting from the power of big data analytics is transportation. Big data is already being used effectively by smart cities around the world to improve the transportation industry – from public transport to freight. Some of the benefits being realised through bug data analytics in the transport sector include:
- Decreased waiting time for public transport
- Optimise freight movements and routing
- Increase safety and reduce environmental impact
In addition, smart transport solutions are also helping to tackle the growing issue of traffic congestion in urban environments. Some of these solutions include adaptive traffic signals, parking solutions and smart corridors.
Cost efficiencies
To create a smart city, governments must invest a lot to finance the remodelling or renovation of the cities and to install the infrastructure needed to make the city “smart”.
Before they commit to huge capital investments, cities are turning to big data to suggest the areas that are in most need of transformation, what sort of transformation is required and the potential cost benefits of those changes. This is allowing cities to make informed decisions based on real-time big data analytics, helping to save them money in the long term.
Using the power of big data analytics in smart cities
Writing for Medium’s Data Series, Alexandre Gonfalonieri – an AI Consultant – highlights a number of cities that are already utilising the power of big data including:
Nanjing, China
Installed sensors into 10,000 taxis, 7,000 buses and 1 million private cars. The resulting data is transferred daily to the Nanjing Information Centre, where experts are able to centralise and analyse traffic data and send updates to commuters on their smartphones. With these data insights, government officials have created new traffic routes to improve congestion, without spending money on new roads.
Italy
Trenitalia, Italy’s major rail operator, installed sensors on the trains and now gets real-time status updates on the mechanical condition of each train and maintenance predictions that allows Trenitalia to plan a course of action ahead of an unfortunate event. These technological innovations provide travellers with a reliable system and service while allowing cities to prevent major disruptions.
Los Angeles
LA is replacing 4,500 miles of streetlights with new LEDs. Not only will this result in brighter streets, but the new lights will also be an interconnected system that will inform the city of each bulb’s status. If one malfunctions, it can be identified and fixed almost immediately. In the future, we could have lights that change colours or blink to warn citizens of various conditions.
Shared data will enable cities to do even more
Whilst there are many examples of smart cities that are collecting and utilising data to improve living conditions for citizens, many of the smart cities around the world are working in silos.
Data sharing would open up new possibilities for existing smart cities, as well as allow cities hoping to deploy smart solutions to make informed decisions based on the data being collected in other cities around the world.
Every second, there are millions of sensors around the world collecting a staggering amount of data. Much of this data is captured, stored, and forgotten about. Whilst some of the data is analysed and put to use, a much bigger percentage is simply stored and never used.
Data sharing, between departments within a city and beyond that, between cities, will help to improve efficiencies, enable more in-depth analysis of the data and eventually, lead to faster development of new solutions and an increase in the number of smart cities around the world.
Summary
Big data is being harnessed and analysed to help create smarter cities all around the world. As we move through 2022 and beyond, it is expected that data sharing will play a more integral role in improving the overall efficiencies of smart cities, drawing on cross-sector and cross-city data to provide even more insights and to aid decision making at all levels.
Here at NEC New Zealand, we recently signed a long-term agreement with Environment Canterbury and the Christchurch City Council to evolve the current bus network into a smart transportation network. It is initiatives like this that put transportation at the heart of smart growth for a modern city and that help to reduce congestion.
Big data is helping to power these initiatives, collecting huge amounts of data from sensors, all made possible thanks to the power of the IoT.
Each year, more and more cities are added to the annual Smart City Index and those already established on the list continue to grow and improve. This can only be a good thing for citizens of those cities and the sharing of data can help to accelerate the move for more cities to become smart cities.
Auckland is currently New Zealand’s only entry in the 118 strong list of smart cities, placing ninth in 2021, down from fourth in 2020. The City of Sails continues to score well across the board, achieving A ratings for Structure and Technology as well as an overall rating of A. The highest rating is AAA and Singapore achieved this rating across all three aspects included in the study, the only city to achieve a AAA overall rating.
With increased data sharing, improved data analytics and advancements in IoT-powered technology, we can expect to see a much brighter future for citizens around the world.
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