Processing directly at the source of data, rather than in the cloud or remote data center, and the possibility of making decisions based on information provided in real time by sensors and devices located in strategic locations: for many public services, the edge computing offers all the potential for management

Now, after seeing the value it offers in other sectors, public authorities are also in a position to finally consider the benefits of edge computing for themselves.

The authoritative opinion is by Adrian Keward, Chief Technologist of Red Hat, according to which thirty years ago, all intelligence of an organization was kept in the data centers.

Today, however, we are at a stage in which part of that workload can be moved to edge devices.

Mobile network providers, probably the pioneers of edge computing, use it to bring processing power close to the network borders and significantly reduce latency, which is crucial to enable the speed and availability promised by 5G.

Not only that: the edge computing has been widely adopted also in sectors such as production, where, thanks to the data generated by sensors located on different machines, engineers are able to identify immediately and prevent, using automation, any errors before they become problems, all

These sensors, typically microprocessors with limited intelligence, monitor and measure factors such as pressure, heat or water flow. An intelligent home counter is, in all respects, an edge device that has a certain processing capacity (e.g. records the domestic use of gas, electricity or water), and makes use of this information. These are currently limited in scope.

In the future, smart meters are likely to use the data they collect to do more than calculate their bills. They will also have the ability to change energy tariffs, turn off devices when they are not in use, and even open windows if the temperature of a building is high enough.

Following this logic, perhaps the best case of use for the edge computing at the public level is represented by smart city management. As intelligent meters will be used over time to manage the domestic use of energy, so edge devices can be used to manage various aspects of a city.

Let’s think about managing traffic flow in the center of a big city. Only understanding how busy the roads are at a given time can you know whether to close it or not, or change the pace of traffic lights to relieve congestion.

In this situation, relying on centralised processing means that any data will always be unupdated and that, when it is addressed, the problem in question may have moved elsewhere, grown in size or disappeared altogether. On the contrary, by bringing the processing power as close as possible to the roads, and by adding AI and machine learning to this mix, you can give a certain degree of autonomy to traffic lights.

Understanding cause and effect processes from similar previous cases, and learning what is needed to remedy a particular situation, this combination of technologies will allow a device mounted on traffic lights to identify the problem and apply the appropriate correction

Edge computing, efficient and affordable

Traffic management, however, is only one of the cases where edge technology can be applied to city management. Other examples include monitoring of HVAC systems in municipal-managed properties for more efficient energy use, and measuring changes in household and business behaviour for more profitable waste or water management, but also an important role in emergency planning.

For example, the Japanese city of Fuji has deployed edge devices located in strategic locations that, constantly transmitting various forms of environmental data, allow emergency services to react almost instantaneously in the event of an earthquake and send emergency personnel where it is most necessary at any time.

The potential of the edge processing continues to grow. In the end, its benefits and capabilities will be seen in the places where it is most useful. Sensors mounted on traffic lights in a city could be used to manage traffic flow using image recognition technology, for example, as well as adapting the timing of the same traffic lights.

It is no secret that public authorities do not always have the budget or resources to do anything they want to do. An automated edge-based system is much lighter than the data centers that departments have relied on in the past, and requires much less people to manage. Allow departments to choose which data to collect and for what purpose, it also allows them to decide where that data is to be collected, and whether that edge device must always be connected.

In the end, Red Hat’s manager points out, the objective of any government agency is to provide citizens with better services, more efficiently and at lower costs, and the increasing shift from data centers to edge computing, allows more and more to pursue this goal.

In other words, it is time for the public sector to start considering the edge.

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