GN chats with Jeff Park, Seagate’s Country Manager, ANZ about the challenges and benefits of smart cities.

GN: We hear a lot about smart cities – why the fuss?

JP: A smart city integrates digital technologies into its networks, services and infrastructure and solves city problems. It connects information and communication devices and uses data to enhance city residents’ lives. The main goal of smart cities is to create efficiencies, improve sustainability, create economic development and enhance overall quality-of-life factors for the residents.

As great as it sounds, however, the holistic end-to-end networked smart cities are not here yet. First, deriving value from a smart city depends on more than a network of connected IoT devices. Cities will need to be able to implement the infrastructure, systems and capabilities like AI to manage and help decipher the avalanche of data. Adding on to that, lacking storage infrastructure to accommodate the exponential increase in data capture from sensors and digital devices is one of the main challenge the cities face. 

Despite slow development, the interest is growing. In fact, we have seen that many cities are already getting smarter, embracing the power of digital data to improve residents’ lives. The arrival of 5G, faster IoT connectivity and AI tools, have also seen assist the process of smart cities. With Covid-19 pandemic, it also given cities a push to rapidly progress in digitalisation.

While there are challenges to address in realising smart cities dream, there can be no denying that smart cities may not be so far away.

Can you talk about the benefits of smart cities in terms of health and safety, mobility, and economic development?

Smart cities are answering urban woes by collecting information from a variety of sensors to secure public safety, optimise utility efficiencies, improve traffic flow and safeguard residents from threats. It positively affects more quality-of-life dimensions, including social connectedness, civic participation, employment rates and cost of living.

Traffic congestion and roadway infrastructure are often the top struggles that growing metropolises face. A McKinsey Global Institute report recently found that metropolises using traffic sensors to improve traffic flow had the potential to reduce commutes by 15% to 20% and emergency response times by 20% to 35%. With the advent of rideshares and micro-transit options and intelligent traffic lights allow for optimised routes based on traffic patterns, these technologies can greatly reduce the number of cars on the road and overall congestion. Also, municipal camera can be used to detect an incident using video analytics or AI and send an alert to a monitoring or command center, allowing police officers to respond quickly.

Other positive outcomes include cutting the disease burden by 8% to 15%, reducing fatalities by 8% to 10% and slashing greenhouse gas emissions by 10% to 15%. Advanced IoT devices are being utilised to provide remote patient monitoring, providing real-time alerts to staff who can take action before the situation escalates to a crisis, helping to lower mortality rates. While smart meters allow for more frequent readings and home energy consumption tracking, providing families with information that can be used to make lifestyle adjustments to improve energy conservation, thereby making the cities more sustainable.   

On economic development, housing and community engagement front, the platforms are becoming available to the public providing helpful information, such as roadblocks to steer away from and disturbances to be aware of and inviting incident reporting such as vandalism.

All in all, healthcare, transportation and local economies all benefit within smart cities by  leveraging new sensors and data to improve efficiency and quality of services, making the cities more resourceful yet sustainable.

What’s the role of data in enabling smart cities to thrive?

While smart cities rely heavily on smart applications, IoT devices and technologies, the true value lies in aggregating and analysing data from disparate sources to deliver deeper insights and provide municipalities with a fuller picture of overall city operations. Data is the currency to enable smart cities.

Smart city leverages data to improve efficiency and quality of services, including city management, healthcare and transportation and become more responsive to their residents’ needs. The vast amount of data generated by the widely deployed induction and networking devices is an important foundation for AI and machine learning. Successfully obtaining and analysing these data is the key to improving smart cities. For instance, video cameras and IoT devices are increasingly smart cameras that can be incorporated onboard analytics and storage, which is critical for smart city applications such as traffic control and public safety.

Effectively storing, activating and moving the large amounts of data generated by these endpoints is vital to provide insights to the decision makers to improve livelihoods. Data storage, latency and reliability are the building blocks that allow cities to turn the data gathered from all the data sources into something actionable and of real benefit to the citizens. To realise that storage infrastructure needs to be deployed to accommodate an exponential increase in data capture from all sensors and digital devices.

What are we talking about when we refer to ‘data sprawl’ and why is this an issue?

Data sprawl is about the number of data centres and processing locations and how far data is spreading geographically. It is the increasing degree to which business data no longer resides in one location but is scattered across data centres and geographic locations.

Sprawl exists throughout various configurations – from endpoint devices through the edge and to the public and private cloud. It adds complexity to the challenges of managing data’s growth, movement and activation. How businesses cope with the increasing growth and sprawl of data will greatly impact their success moving forward.

One of the major factors leading to increased data sprawl is the expansion of data across multiple locations, from the cloud to the edge. When data sprawl, it results in silos, making it challenging to transform the data into insights, affecting the decision makers’ ability to extract total value from data and consequently grow revenue.

What are the biggest challenges posed by the exponential increase in data capture?

Smart cities are looking at mass data – data generated from traffic management, access control, public transportation and other smart applications. A smart city can generate 2.5PB of data each day, while autonomous cars generate and consume an estimated 4000 gigabytes of data every eight hours of driving. This data pool continues to grow along the way.

All this data is critical and needs to be collected, aggregated and stored for deep analysis that leads to the insights where cities can act upon to improve efficiency and the residents’ daily lives.

This creates several management challenges that stem from the complexities of storing and managing scattered data, most important of which is that storage infrastructure needs to be considered to accommodate the data.

The recent Rethink Data report found that only 32% of that enterprise data gets activated or put to use because capturing, storing and managing that deluge can be tricky. Additionally, with the unstructured data being generated at daunting speeds and distributed across many locations, it poses another challenge: data sprawl. Finally, as cities become better connected and collect more and more data, privacy and security questions arise, such as what data is being collected, how is it being used, who gets access to it and who monitors it?

What are the biggest barriers to putting data to work?

According to Seagate’s Rethink Data report, based on the IDC’s research, companies have stated five key challenges that they believe limit their ability to exploit the full potential of collected data

• Making collected data usable
• Managing the storage of collected data
• Ensuring that needed data is collected
• Ensuring the security of collected data
• Making the different silos of collected data available

How can organisations manage data efficiently?

Organisations often have a tendency to collect and dump data into large repositories. Collecting data is easy but intelligence is hard. Before we implement the steps to better manage data, we need to understand our own data. There are four main areas to look into for data management: data creation, storage, activation and movement.

Data creation considerations focus on when and where data originated. This can encompass everything from IoT devices feeding sporadic business-critical information from the edge to the constant stream of performance-monitoring data on the factory floor and anything in between.

Data storage focuses on the persistence, reliability and durability of data. The decisions here are centred around where and how data is stored. Data in motion strategies should aim for ease, speed, and cost efficiency.

Data activation involves examining how data is leveraged including when, where and how data should be stored and used. Often the data collected may be ignored and pushed aside leading to underutilisation, skewing the economics of storage toward middling or worse returns on investment. For smart city where it is all about data, it has to have the ability to capture the right data, identify it, store it where it is needed and provide it to decision makers in a usable way.

Finally, data movement. The policies here should be designed to avoid cloud vendor lock-in, and to keep specific datasets and mass data from being trapped in silos so that it can be freely accessed and moved as needed.

In short, to efficiently manage data across cloud, edge and endpoint environments, it requires a holistic visibility into data storage across on-premises and cloud architectures. It is important that every data management system can change to accommodate new data requirement by being agile and able to adapt to shifting business needs and emerging technical opportunities.

Data loss due to human error, disasters or malicious activity is a constant threat. What’s the solution?

Backup processes play an important role in ensuring data compliance, security and data governance. The 3-2-1 backup storage is a good step to start or revise a standard data backup policy. It should also be served as a baseline.

Today, standalone backups are being replaced by replication in multiple cloud locations. Organisations have also begun to move towards the cloud in their approach for disaster recovery – a trend that was accelerated by the pandemic. Unlike traditional disaster recovery, cloud disaster discovery allows organisations to achieve greater cost savings, better security and reliability in the wake of disaster.  

Regardless of the disaster recovery approach, the key elements for consideration are:

Reliability. Strong security is the foremost when looking to protect and save data. High data resiliency not only saves organisations from the risk of data loss caused by human error, equipment failure, malware, ransomware or natural disasters but also prevents interruptions to business continuity. This is especially critical for the smart city considering the data sensitivity and network breach’s potential ramifications. It enables organisations to build resilience and reduce vulnerability to data attacks while increasing productive data use.

Scalability. With more data being created than ever before and more use cases to unlock value from data, it is important that every data management system can change to accommodate new data requirements. Data management and data architecture to support it must be agile and able to adapt to shifting business needs and emerging technologies. The freedom to migrate large volume of data within a predictable cost structure and the ability to store it longer should also be considered.

Ease of access and downtime. Data backup should be secure, simple and efficient. An interoperable option with other software, hardware and services help ensure operation continuity during data loss from disasters or threats. It provides rapid data recovery and a speedy return to regular operations.  

How does Australia stack up against the rest of the world when it comes to smart cities? Looking into the crystal ball, what do you see as the future of the Australian smart city?

The three essential elements of a smart city are connectivity, data and government involvement and Australia is making big meaningful strides.

Brisbane, Sydney and Melbourne continue to be included in the top 20 list of the world’s smartest cities in the Smart City Index, an annual report conducted by the Institute for Management Development with Singapore University for Technology and Design (SUTD), has shown that the cities effort is being recognised on the world stage.

Australia has demonstrated a strong determination, but like many other cities and countries, the smart city development is still uneven and needs a lot more collaboration and coordination when it comes to how different platforms will be used and streamlined to collect, analyse, transfer and use data and information derived from that data.

While there are areas for improvement in realising smart cities, we can see that the country is entering a more actionable phase with plans and projects in place and increasing numbers of local government and private bodies now actively engaged in pilot projects.

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