Data analytics: The key to delivering smart cities


Data analytics has a crucial role to play in helping cities become zero-carbon, improve urban mobility, and better manage their infrastructure in a secure, sustainable and cost-effective manner, according to this article by Eric Woods, research director smart cities, Navigant Research.

Navigant Research is tracking smart city projects in more than 280 cities across the world. Many other cities are in the early phases of strategy development or are deploying projects under the radar. This momentum is also reflected in the expanding market for smart city solutions. The company estimates the global smart city technology market to be worth $97 billion in 2019. Over the next decade, cumulative investment is anticipated to reach almost $1.7 trillion.

This article was originally published in Smart Energy International 5-2019. Read the full digimag here or subscribe to receive a print copy here.

The growing number of Internet of Things (IoT) devices deployed across all parts of the urban environment has the potential to change our understanding of how cities work. Developments in big data analytics, machine learning, artificial intelligence (AI), and data visualisation are providing city managers and leaders with tools to help make sense of these data flows. At the same time, cities are developing new platforms for data integration and sharing that are breaking down traditional operations silos and opening access to all stakeholders and potential solutions providers. For this reason, the benefits offered by big data are an important element of many smart city strategies. For example:

• Predictive analysis of traffic and transport patterns can reduce congestion and improve the efficiency of public transport services.

• City resources for public safety, social care, and other key services can be targeted more effectively using up-to-date analysis.

• Energy efficiency programmes can be directed at the most vulnerable households and at suitable buildings for retrofit programmes.

• Open data platforms can increase citizen engagement and encourage new forms of creativity and innovation among developers and other service providers.

The importance of analytics

Data analytics has a role to play across all aspects of public service and city operations. Examples include the following: The shift to zero-carbon cities: Advanced data analytics have an essential role to play in enabling cities, utilities, and other partners to optimise energy and resource flow to meet their ambitious zero-carbon targets. Analytics are vital, for example, in the efficient management of community energy systems based on distributed renewable energy, storage technologies, and microgrids. Projects like the EU-funded Sharing Cities programme (led by London, Milan, and Lisbon) are exploring the use of energy data in a sustainable energy management system (SEMS) that optimises energy production and consumption at the community level. The SEMS also links to the broader urban data platform being developed as part of the programme.

Improved mobility: City transportation departments have been leaders in using advanced analytics. Real-time data collected from sensors and other devices is helping to optimise connections between modes of transport for faster travel times, reduce the costs of operation, and increase convenience through improved information services for users. Hangzhou, China has deployed Alibaba’s City Brain platform to predict traffic flows and detect accidents as part of its traffic management system. It claims that this platform has seen the city move from 5th to 57th on the list of China’s worst-congested cities. Communication carriers are also using telephone data to help address congestion.

Better asset management: Data analytics enable cities to better monitor and manage a wide range of city infrastructure and to use predictive maintenance to reduce risks and costs. Kansas City, Missouri is using data analytics and sensor technologies, alongside green infrastructure, to save $1 billion in infrastructure costs associated with a $4.5 billion smart sewer upgrade project.

City benchmarking: Data analytics are also being used to provide new insights into economic performance. Dublin, Ireland is one of a group of cities partnering with Mastercard under its City Possible initiative. Insights from Mastercard’s city spending analyses are being used as part of the city council’s economic monitoring reports to help the council better understand spending patterns of Dubliners and tourists and to compare Dublin’s performance to all of Ireland.

Addressing the challenges

There is immense potential for the better use of data across all city services, but city managers also need to address some major challenges. Some of these are common problems that have long beset large-scale data analytics projects, such as ensuring data quality and understanding the priority objectives for any application.

There are three challenges that are particularly associated with using big data and data analytics for city management.

Data integration: The smart city vision holds out the promise of integrating data from multiple organisations, diverse environments, and a wide variety of intelligent devices. Yet, data integration even within organisations is one of the hardest challenges in the IT world.

The adoption of open standards across the IT and communications industry has reduced (although not removed) the technical barriers, but the political and organisational ones are often the hardest to address.

The current focus on developing standards that can guide smart city developments is an important step in addressing these issues.

Data privacy: The emergence of smart cities is unleashing vast new data streams with huge potential to improve city services.

This is also putting cities at the forefront of debates over the ownership and use of data. National and international data privacy regulation, like the EU General Data Protection Regulation, has an important role to play in ensuring the acceptance of many smart city innovations. However, some cities feel they need to do more. The relationship between citizens, government, and service providers needs to evolve to address the potential challenges offered by the emergence of smart cities. This will only become more obvious as the use of big data and AI becomes ubiquitous in city management and in public and private services. Cities are realising that they need to be as active in shaping this new data environment as they are in planning and managing their physical infrastructure.

The skills gap: A lack of data skills may be the biggest barrier of all to effectively using big data for city management. Managing and analysing large datasets and developing insights for effective policymaking or operational improvement requires skills that are in short supply, particularly in the public sector. Cloud-based services, public-private partnerships, and open data strategies can all help by providing access to a broader skills base. Cities can also build deeper relationships with academia. Many universities are already active in helping cities develop sustainability and economic strategies, but they can do more to help cities effectively exploit their technology and data resources.

Preparing for the future

Smart cities are entering a critical new phase of development, where the focus is on delivering real improvements against key metrics and priority outcomes. This development requires digital innovation and data-centric perspectives to be embedded in service design and city planning processes.

The value of smart city technology investment is ultimately realised through the use of data to improve decision-making, support real-time operational control, increase service quality and efficiency, and improve engagement with citizens, businesses, and other stakeholders.

The ability to harness real-time, highly granular data across a wide range of city operations and services will change the way the urban environment is managed and experienced. To prepare for this new environment, cities need to establish a strategy for city data, build their analytics capacity, and work with partners, including energy companies, to establish a data commons that can benefit all. SEI

About the author

Eric Woods is a research director leading Navigant Research’s coverage of smart cities. In this role, he brings together his research experience across energy, mobility, buildings, and government. He has experience as an analyst and consultant on new technology trends, including in-depth research in the areas of IT infrastructure, data analytics, knowledge management, public sector IT, and cleantech innovation. He is a frequent speaker at industry conferences and is quoted regularly in major publications.

About Navigant

Navigant Consulting is a specialised, global professional services firm that helps clients take control of their future. Navigant’s professionals apply deep industry knowledge, substantive technical expertise, and an enterprising approach to help clients build, manage, and/or protect their business interests.