Associate feature: It's time for government to move closer to the edge

Edge computing has the potential to enable more efficient, more insightful, and more cost-effective management of a range of public services.

With processing carried out at - or very near to - the source of data, rather than in the cloud or in remote data centres, edge computing allows decisions to be made based on live information generated by sensors and devices located in the places that matter most.

But the benefits to government of edge computing have been a long time coming.

Now, having seen the value it delivers in other sectors, it’s a good time for government departments to consider the advantages of edge computing for themselves.  

Growing adoption  

Thirty years ago, all of an organisation’s intelligence would have been held in data centres. Today, we’re at a stage where some of that workload can be moved onto edge devices. 

Mobile network providers, probably the pioneers of edge computing, use it to bring processing power close to the network edge and massively reduce latency, which is especially important in enabling the speed and availability promised by 5G.

It has been widely adopted in sectors such as manufacturing, too. From the data generated by sensors located on different machines, engineers are able to immediately identify and, by using automation, remedy any mistakes that might occur before they become issues, reducing the time spent in QA and production cycles, speeding time-to-market and, of course, saving costs. 

Typically microprocessors with limited intelligence, these sensors monitor and measure factors such as pressure, heat, or water flow. A domestic smart meter is, effectively, an edge device - it has some processing capability, it records a household usage of gas, electricity, or water, and it makes use of that information. 

At the moment, this use is limited in scope. In the future, however, it’s likely that smart meters will use the data they collect to do more than just calculate bills. They’ll also have the ability to switch energy tariffs, turn off devices when they’re not in use, and even open windows if the temperature in a building is high enough.  

Smart city management  

Following this logic, perhaps the best use case for edge computing in local government is in the management of smart cities.

As smart meters will, in time, be used to manage domestic energy use, so edge devices can be used to manage various aspects of a city.  

Consider the task of managing traffic flow in Edinburgh or Glasgow city centre. 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 centralised processing means any data will always 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 AI and machine learning 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, the combination of technologies will enable an edge device mounted on the lights to identify the issue and apply the appropriate fix - in real-time.  

Efficient and cost-effective 

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 in council-run properties for more cost-effective energy usage, and measuring shifting household and business behaviours for more efficient waste or water management.

It has a role to play in contingency planning, too. For example, the Japanese city Fuji has edge devices located in strategic locations, constantly streaming various forms of environmental data, enabling the 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. Ultimately, its benefits - and capabilities - will be seen in the places where it’s most useful. 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.  

It’s no secret that government departments don’t always have the budget or resources they need for everything they want to do.

An automated, edge-based system, however, is far smaller than the data centres which departments have relied upon in the past, and requires far fewer people to manage.

By enabling departments to choose what data they collect, and for what purpose, it also allows them to decide where that data should be collected from, and whether that edge device even needs to be connected at all times.  

The aim of any government department is to deliver better services, more efficiently, at lower cost.

The growing shift from data centres to edge computing, increasingly allows this delivery, that efficiency, and those cost savings. It’s time for government departments to move closer to the edge.

Adrian Keward is chief technologist at Red Hat. This article was sponsored by Red Hat.