The challenges of smart city data management

Technology investments are improving government services but they are also creating a headache for data storage, analysis, and integration.

In a connected world, cities run smoothly. The network of sensors, cameras, and devices work together to paint a vivid picture of the urban environment informing the citizens, the government, and the private sector. We are seeing innovations in transport, energy, utilities, and crisis response designed to bring a higher standard of living, especially as IoT adoption increases.

While these investments are improving the quality of government services, they are creating a headache for data storage, analysis, and integration. There is also the question of data management.

Reassessing how data is managed is key to unlocking the value of smart cities. For effective data management, there are three core principles: data needs to be actively transmitted across different channels, it needs to be in a secure environment, and it needs to be scalable.

Data challenges of smart cities

Keeping in mind these three principles, governments are working to upgrade their decades-old infrastructure to meet the needs of new technology. This can be a costly endeavour over a short period of time, with many choosing a phased approach. However, at the centre of this modernisation is the need to quickly mine value from data to drive the next steps.

As sensors and systems are deployed, data is generated at pace, needing to be stored, analysed, and distributed to different parts of the network instantly. With traditional databases, this can be clunky, time-consuming, and require manual processes to update systems to read the same information. For smart cities, this can result in potentially dangerous mistakes and incorrect details relayed to citizens.

Data governance tools for real-time data streams can ensure the integrity of data used across an organisation. But according to the 2022 State of Data in Motion Report report, only 27% of IT decision-makers have such capabilities in place.

For smart cities, there is a need for a data streaming platform that can overcome the key challenges faced, such as:

• Integration — vast amounts of data, from legacy to custom code, across thousands of systems.
• Data correction and correlation — real-time ETL (extract transform and load) and data enrichment.
• Real-time processing — act on data when it is needed; right now.
• High availability and zero downtime — always available even in a disaster.
   

Streaming data from IoT devices at scale across the city is key to a smart city being able to monitor what’s happening in real time. This pattern can be accomplished via a smart-edge processing framework that plugs into the data hub (or hubs for further resilience). This allows for data reduction (getting just the signal from the noise) as well as data enrichment all happening at speed in real time.

This now enriched data can quickly flow to the hub for further processing and distribution to any system and other parts of the organisation that need to make timely decisions.

In turn, governments can make quick decisions, fine-tune operations, and plan strategies for positive impacts on everyday challenges. Adopting a data streaming capability within an organisation can build trust and confidence in teams to work autonomously and make decisions that are based on real-time data.

Real-time benefits for response

An area of high priority for governments is critical response situations, where timeliness is key to navigating problems to mitigate emergencies. Cities never sleep, so data is always moving and needs to be managed accordingly. To plan the shortest and quickest route for first responders to safely get to an incident, governments need to have real-time information on traffic management such as congestion levels and local road closures. Likewise, for citizens, sharing live accident information helps them plan accordingly.

Real-time data provides visibility on current operations across a city but to translate this information into actionable insights, there needs to be an easy way to access and filter multiple sources of data. Data needs to be constantly shared between different locations and computer systems and then integrated to facilitate instant decision-making. With need-to-know details at their fingertips, data streaming enables first responders to make high-pressure decisions based on real-time data.

Downtime for services can be a stressor for the day-to-day functioning of a city and, at its worst, detrimental to the safety of citizens. However, there is also the possibility of technology being exposed. When systems are down, they’re unable to detect threats, leaving access points vulnerable to security breaches. In line with the core principles of data management, smart cities should look to develop secure environments so that data is not compromised and services can continue as usual once downtime has been corrected. As such, the rise of cloud services has become more prominent due to their always-on protection against internal and external threats.

Scalability for population and tech adoption

Population numbers in major cities have continued to rise, so governments have worked to meet the increased demand for services and utilities. More people means more technology; more technology means more data.

The volume of data is not always consistent and can undulate daily, weekly, monthly, and yearly according to the activities of citizens. To combat capacity issues of traditional databases, cloud services can be adopted to shrink and grow with the movement of data.

There are several other benefits to the cloud, such as cost savings, simplicity, resilience, and security. These combined, foster a flexible environment for developers to collaborate anywhere and everywhere with the peace of mind that the underlying cloud infrastructure has loss prevention and disaster recovery measures in place. Being cloud-based also means applications and software automatically update so developers can focus on value-add rather than maintenance or resourcing.

Innovation for smart cities is only going to increase with each new technology built for integration and data-sharing to maximise the effectiveness of information produced. Governments should prepare their infrastructure with the ability to manage data throughout multiple database formats including cloud and traditional while switching to modern systems, so they have the option to use both hybrid and multi-cloud environments. This is possible with data streaming as it draws from multiple sources integrating the information to produce the full picture rather than segmented snapshots.

Data in motion for smarter cities

Seventy-six per cent of IT leaders said timely integration of real-time data from different applications is very, or extremely, important for mission-critical processes within their organisation, according to the State of Data in Motion Report. Yet nearly half reported difficulty integrating data promptly.

However, after the initial barrier is crossed, real-time data management proves itself beneficial in both performance and maintenance. Governments can worry less about the integrity of their information and look to the future to develop innovations and upgrade services.

Following the adoption of a seamless flow of real-time data, governments thrive with more effective and efficient data management. Leveraging cloud environments to manage the scalability of increasing volumes of data, governments appreciate automation and flexibility of applications while maintaining a secure environment to innovate. As governments accelerate towards modernisation, data in motion bridges the divide between imagination and reality, empowering them to harness the wealth of real-time knowledge for smarter cities.

Image credit: iStock.com/metamorworks