Edge computing brings new innovations to the Internet of Things network.

City-wide Internet of Things (IoT) networks are barely upon us but experts are already discussing the next innovations in smart city digital connectivity. Any IoT Network worth its salt is built upon a high bandwidth, low-latency network capable of handling such vast swathes of data, but currently, at least until reliable and affordable 5G becomes more commonplace, network connectivity can be lacking.

Edge computing is the answer. Traditional IoT networks collect and analyse data before sending it to a central cloud computer, where it can be processed and acted on. Edge Computing, meanwhile, allows for more on-device computing and analytics.

This process, wherein which computers are located on or close to the end-points and sensors that they manage; at the edge of the network. This means decisions can be made in real-time by the devices themselves rather than sending data on to another computer for processing.

Such an instantaneous response is a necessary requirement for high bandwidth technologies such as autonomous cars, where human-like reactions are integral to achieving high levels of safety.

Faster, Stronger

A network that includes edge computing tends to be more reliable, much faster, and places less demand on network connectivity and Internet bandwidth usage. According to a report by Markets&Markets the Edge Analytics market is expected to reach an astonishing $7.96bn by 2021. Such a fast-growing area of the IoT represents a huge boon for local authorities considering investing in smart city technology.

To truly reap the benefits of a next-generation IoT network, edge computing represents a necessary investment for any budding smart city. Not only does it regulate processing and network demands, but it also comes with fair financial savings.

On-device decision making means surplus data does not need to be transferred and stored in a cloud network, cutting data storage costs. This means that only the most vital data is processed, instead of sending multitudes of autonomous vehicle reports, or raw CCTV footage from across the city to the cloud.

Sensors that have the ability to act independently also offer privacy and security benefits. Acting without the input of a central cloud control system means that each sensor can survive a network outage or inconsistent coverage. This represents an especially enticing feature whilst reliable city-wide 5G communications remain in their relative infancy.

The rise of the machines

Edge networks form a critical component in systems that adopt machine learning techniques, such as those managing vehicles and the flow of traffic through a congested cityscape. As the machine learns and alters its behaviour based on the data it collects, quickly reacting to and implementing this new information is only possible if the data is handled on-device.

This on-device learning can aid in keeping IoT networks up-to-date, with updates pushed to computers over the network, rather than having to be physically upgraded. 

Cloud or edge?

The arrival of edge computing doesn’t necessarily signal the end for more common cloud-based IoT networks. Data stored in a central location tends to be more accessible and open, offering greater availability for shared open data agreements between the private and public sector. Sharing these data streams can lead to stronger forms of innovation and new digital design. Of course, having data available in the cloud allows for more mobile and remote interactions.

Edge computing is due to play an important role in the next stages of development in the smart city sector. As technology becomes more advanced and increasingly reliant on computers capable of human-like reactions, the ability to make such decisions on a device will become more prevalent and integral to the successful smart city environment.