Edge computing has the potential to enable more efficient, more insightful, and more cost-effective management of a range of public services. More and more applications – from 5G and industrial automation to connected home and streaming devices – now depend on edge computing capabilities, and appetite for the technology in this region is growing. According to GlobalData, the market for edge computing in Asia Pacific (APAC) is estimated to reach US$5.8bn by 2024, representing a compound annual growth rate of 21% over five years. Now, having seen the value it delivers in other sectors, it is a good time for government departments to consider the advantages of edge computing for themselves.
Growing adoption in different sectors
With processing carried out at, or very near to, the source of data (rather than in the cloud or in remote data centers), edge computing allows decisions to be made based on information generated by devices located in the places that matter most.
Connected transportation hubs can use private network-connected edge devices and sensors to track vehicle movements, infrastructure and weather to improve efficiencies and safety across operations. Firms in sectors such as construction can also use on-/off-body edge devices to improve worker safety. These devices can send alerts when crossing safety thresholds, while 5G network edge enables real-time analysis of data-feed from distant / mobile devices and trigger alerts.
Opening up a path to smart cities in Asia
One of the most promising use cases for edge computing in local government is in the management of smart cities. Consider the task of managing traffic flow in a city center, something of urgent importance in cities such as Bangkok and Jakarta, where road users lost an average of 67 and 33 hours a year in traffic congestion respectively in 2020, even amidst lockdown measures taken last year. This can be more serious than many realise – causing issues from frustration for drivers and their passengers, to lost productivity for businesses. Traffic congestion is also a serious problem for first responders, where even seconds can make a difference.
Only by understanding how busy the roads are at any given point in time is it possible to know whether or not to close a particular road, or to change the phasing of traffic lights to alleviate congestion. Relying on centralized processing means data could be out of date. By the time it’s addressed, the issue in question may have moved elsewhere, grown in size, or vanished altogether.
However, by putting the processing power as close to the roads as possible, and adding artificial intelligence (AI) and machine learning (ML) technology to the mix, it’s possible to give a degree of autonomy to the traffic light systems. By understanding cause and effect from previous similar instances, and by learning what’s needed to remedy a particular situation, AI/ML technologies can enable an edge device mounted on the lights to identify the issue and apply the appropriate fix in close to real-time.
Looking to the future: Expanding the use of edge computing in the public sector
Traffic management is just one way in which edge technology can be applied to managing a city. Other examples include the monitoring of HVAC systems for more cost-effective energy usage, and measuring shifting household and business behaviors for more efficient waste or water management.
It has a role to play in contingency planning, too. For example, Fuji, Japan has edge devices located in strategic locations, constantly streaming various forms of environmental data. This data enables emergency services to react almost instantly in the event of an earthquake, deploying emergency personnel where they’re most needed at any given time.
The potential of edge processing continues to grow. The sensors mounted on a city’s traffic lights could be used to manage traffic flow by employing image recognition technology, for example, as well as adapting the phasing of the lights themselves.
Why move to the edge?
Today, technology is a powerful catalyst for change in any country. This is particularly true in emerging Asia, where adoption of digital technology has been gaining pace in the past few years. Southeast Asia alone saw some 40 million new internet users in 2020, in a “permanent and massive digital adoption spurt” brought about by the coronavirus pandemic. For governments to ride this wave of change, they must bring digital services closer to their citizens, and scale the way they reach out and improve lives through technology. Singapore, for example, formed GovTech in 2016, with the aim of improving lives for citizens and promoting innovative collaboration enterprises.
All of this means governments in the region must scale their ability to collect, process and analyse data. Processing such large amounts of data is more secure and efficient done near the source, and reduces the bandwidth needed. Furthermore, as digital services become increasingly central to day-to-day life, the impact of downtime also grows. Edge computing distributes the processes across a range of devices, instead of relying on a single point of application, thus reducing the risk of system-wide shutdowns that can disrupt essential citizen services.
Edge technology also offers flexibility by enabling departments to choose what data they collect — and for what purpose — allowing them to decide where that data should be collected from and whether certain edge devices even need to be connected at all times.
Putting governments in Asia Pacific on the edge
The UN projects that 68% of the world’s population will live in urban areas by 2050. Closer to home, the number of inhabitants in medium sized cities in Southeast Asia is expected to double by 2025. While this expansion is essential to the continued growth of the economy in the region, the public sector must combine technological solutions with prudent urban planning to manage the challenges this will pose. To build cities that are smart at the core, edge computing will become key for governments in emerging Asia Pacific.
