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Charting artificial intelligence urbanism in Southeast Asia

David Fasken
David Fasken • 5 min read
Charting artificial intelligence urbanism in Southeast Asia
What's the role of a modern network in smart cities? Photo: Pexels
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We are living through an urban revolution in Southeast Asia as local governments and enterprises work together to implement secure, robust infrastructures to support an evolving smart city vision.

While Singapore stands at the forefront of smart city development, having ranked 7th globally in IMD's 2023 Smart City Index, neighbouring Southeast Asian nations are also embarking on similar journeys – each at their own pace. The Philippines, for instance, has committed to six smart city projects across three cities. And, in Indonesia, the government aims to establish 100 smart cities by 2045.

Underpinning Southeast Asia's smart city revolution is the use of cutting-edge technologies, particularly artificial intelligence (AI). Singapore has a National AI Strategy in place and is implementing seven National AI Projects across healthcare, smart estates, education, border security, logistics, finance, and government. In addition, Indonesia, Malaysia, the Philippines, Thailand, Vietnam, and others, have also developed their own unique national AI roadmaps.        

Clearly, governments in the region recognise AI as the next frontier of smart city development and are exploring how the technology can be leveraged for economic growth and innovation across sectors.

Reinventing networks for the AI era

As AI becomes increasingly integrated into smart cities, the influx of devices leveraging AI and machine learning (ML) are generating massive amounts of data, changing traffic patterns, and causing spikes in network activity. Now, more than ever, there is a need to ensure that the network infrastructure is secure and scalable enough to support data-heavy AI applications and monitor the network performance in a sustainable manner. These workloads necessitate networks that are secure, scalable, and low latency.

See also: Redefining Asean’s manufacturing landscape with deep learning

To ensure the success of AI-powered smart cities, a paradigm shift in connectivity is critical. To that end, AI and ML not only drive significant network traffic but can also be leveraged to optimise network efficiency, resiliency and operational workflows. This can be used to enhance smart city connectivity, improve urban living, enhance sustainability, and streamline city operations.

Making networks smarter: How and why

Attributes such as security, scale, low latency, measurability, and resilience form the bedrock of a robust critical network infrastructure. Recent studies underscore the significance of these attributes, with data from McKinsey suggesting that automation through scalable networks will free up 60% to 70% of employees’ time – resulting in overall operational efficiency.     

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Certainly, AI's role in making networks smarter every day is proving its potential in various applications, including database reconciliation. Organisations often maintain multiple databases with fragmented information. AI helps consolidate these disparate datasets to establish a comprehensive and accurate "source of truth." This consolidated information can be leveraged for further automation of planning and network operational tasks, such as outage management and technological support.

Moreover, AI can recognise patterns by analysing large datasets to detect trends and anomalies in networks, which further enhances the security and availability of smart city networks. By coupling AI with data-driven analytics, more efficient, adaptable, and sustainable network architectures can be planned and designed to optimise network architectures, reduce latency, improve data transfer rates, and enhance overall performance.

Predictive models for user behaviour and network demand can also facilitate network optimisation and strategic resource allocation in smart cities. For instance, service providers can proactively plan the deployment of fibre optics in areas with predicted spikes in demand due to upcoming developments and construction projects. This foresight aids in determining optimal locations for routers, switches, and data centres.

With outage management, potential areas of fault are pointed out as part of predictive intelligence. This enables swifter responses, minimising downtime, and substantially improving service reliability. By rapidly pinpointing the exact location and nature of faults, service providers can dispatch repair crews with precision to reduce the duration and impact of outages.

In a smart city, everything is connected—from traffic lights to garbage cans. But as cities and communities boldly modernise, what they truly need to realise the smart city vision is a modern network that can constantly and reliably adapt to fast-changing demand.

Supercharging smart city development with innovation and collaboration

There’s no doubt that AI can help improve connectivity in smart cities but its full potential can only be realised when combined with data-driven analytics and intelligent automation. Based on the trajectories of smart city development in Southeast Asia and the rest of the world, network capabilities to support analytics and automation is a key priority in supercharging smart city development.

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An adaptive network infrastructure that can seamlessly react to rapid changes in demand is essential to the modernisation of cities, as well as the efficiency and sustainability of associated ecosystems. Governments also play a crucial role in driving these developments through regulatory policies, guidelines, and public funding initiatives.

To that end, a whole-of-society approach combined with innovation in relentless network technology evolution is pivotal in shaping smart networks, laying the groundwork for accelerating the development of smart cities in Southeast Asia.

David Fasken is the head of Government Solutions for Asia Pacific at Ciena

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