Recent data suggests that by 2025, 34 cities worldwide will have a population of greater than 10 million people. With populations rising and sustainability being op of mind for many, cities are exploring ways to respond by becoming “smarter” and more flexible in order to adapt to their population’s needs.
By David Friend, the CEO and Co-founder, Wasabi Technologies
Just as businesses around the world are leveraging emerging developments in analytics, artificial intelligence (AI) and machine learning (ML) to drive better business decisions, the concept of smart cities aims to leverage intelligent technology to drive better quality of life for their citizens. Accelerated digital transformation has opened the door for cities to leverage intelligent technology that enhances citizen and government engagement, reduces environmental footprint and drives more effective, data-driven decision making for day-to-day necessities such as sanitation, transportation, and communication systems.
But these enhancements redefine the requirements for networks, storage structures and systems. The need for more dynamic computing and data storage will be a pivotal component in the “smart” city paradigm.
Selecting your storage strategy
Intelligent devices (sensors, autonomous machines, networked vehicles) implemented within smart cities generate an ever-increasing variety and volume of data that must be processed and stored. This process needs to be quick, reliable, cost-effective, and secure. Cities might not need access to all data at once, meaning there is more data being stored that still holds significance even when it’s dormant for long periods of time. With an effective storage strategy, this data can be analysed and leveraged at any time to help efficiently modernise entire regions.
System architectures that process data through a centralised enterprise data centre (on-premises or in the cloud) cannot meet the scaling and performance requirements of the smart city due to their limitations on optionality. To counter this, organisations, enterprises and managed service providers are increasingly moving their system architecture to the edge of the network (edge computing). Decentralisation enables data from devices, sensors and applications in the IoT to be analysed and processed locally before being transferred to an enterprise data centre or the cloud. This reduces latency and response time.
Traditional cloud providers typically come with rigid storage capacity, vendor lock-in, and high service fees for egress or ingress. Development teams that need easy, flexible, and cheap access to their data must be wary of these limitations. The cloud promises scale, flexibility, and seemingly infinite capacity, but these limitations put a cap on what’s possible. The reality is that budgets are tight and city development teams need a “bottomless cloud”- one in which storage prices are low enough that IT teams will not even question how much data they are storing or backing up – to cater to these new IoT environments. This gives developers the ability to store endless amounts of data without the stress of draining their budget and allows them to effectively utilise stored data to further enhance the development of their city.
Infrastructure-as-a-Service frees resources
Because smart city development revolves around optimising resource use, more organisations are turning to off-site management. They are outsourcing the management of their infrastructure, within which the data is generated, to an external service provider. What is known as Infrastructure-as-a-Service (IaaS) or Serverless Computing is one of the three basic pillars of cloud computing. The goal: cities only pay for the resources they actually use.
IaaS offers managed, on-demand cloud edge computing services for this purpose. These on-demand solutions are provided in close proximity to users, in radio towers and other remote locations. They help improve the speed and scalability of bandwidth-intensive and delay-sensitive applications by eliminating WAN latency, congestion and performance bottlenecks. After all, the longer it takes to transport data across the computer network, the longer users have to wait for their provisioning. For example, in Angers, France, the country has an open data-driven initiative that gives citizens access to their online data portal through an app. This provides the public with access to real-time data on parking availability, current air quality levels, and public transport timetables.
Providers supply users with various network-based components: software, cloud storage, virtualisation environments and network structures. They help companies and organisations automate administrative tasks and scale data management based on real-world needs. As we continue to feel and see the impacts of global warming, smart cities can utilise the data collected by technologies such as energy-efficient buildings or air-quality sensors to remain environmentally friendly. This data can be analysed to determine what technologies need to be increased in order to reduce the city’s environmental footprint.
Enabling a smart future
The world’s top cities are already beginning their transformation to keep up with the growing demand for resources to support the growing population. Before we know it, various sectors of urban life will be interconnected through intelligent technology, further optimising the use of shared resources. But nothing can be done without data and data storage. We must collect, manage, and evaluate past data to continuously improve the technologies in place. Optimising cloud-based services, such as IaaS can aid in data management. Addressing the growing demand for data storage and computing power capacity is one key factor in enabling this “smart” future.