Part 3 : The Cutting Edge of Smart Cities
The cutting Edge of Smart Cities
Edge computing and fog technologies continue to advance as the technology industry continues to push concepts such as Autonomous Vehicles (AVs), making them seem less of a concept and more of an actual capability that we will likely be using in the coming years.
The integration of all of this technology is also encouraging the adoption and integration of smart cities, which will continue to increase the necessity of Edge computing and infrastructure. Some assessments suggest that by 2050, 7 out of 10 people will likely live in a smart city.
As discussed in Part 1 of the series, Edge and Fog computing have been designed to process large amounts of data as close to the location of the data generation as possible, therefore minimising latency for the end-user and providing almost instantaneous decision making of complex algorithms in AVs and IoT devices.
But driverless vehicles and rapid smart IoT usage aside, what other benefits or opportunities can Edge computing offer?
Well, the answer is almost anything you can see when walking down the road; public transport, street lighting, public refuse and recycling, CCTV cameras and even messaging in the absence of a web connection are just some of the examples.
Public transport efficiency could be increased as AVs talk to one another, sharing data regarding congestions or delays between AVs, allowing them to automatically redirect themselves along a different route to avoid the delays. This information could also be shared with traffic control systems, which would enable the redirection of large amounts of traffic and the synchronisation of traffic lights along these routes to encourage general traffic to bypass congestion and therefore keep inner-city traffic flowing smoothly.
Security cameras could store data locally and transmit intermittent backups to a remote cloud server as required. Not only would this reduce the amount of data being transferred to the cloud significantly, but it would also allow for more affordable wireless IP security systems to be placed around businesses, therefore providing more coverage and in turn promoting a safer and more secure environment. An increase in cameras and access to their footage should enable law enforcement to react quicker and much more precisely.
Street lighting could become much more autonomous through the use of motion sensors, allowing them to only light up when someone is within a certain proximity. Combine this with much more efficient LEDs over the traditional sodium lights and a city can become considerably more energy-efficient too.
Smart public refuse and recycling are also aiming to significantly increase the efficiency of how waste is dealt with. The Smart Bin by BigBelly designed in Needham, ME (USA) utilises solar panels to continuously crush the waste which is deposited, thereby increasing the overall capacity of a single Smart Bin by up to 700% and reducing the necessity for waste collection by as much as 85%. This, in turn, reduces collection visits and the traffic/ congestion which it inevitably causes and also reduces the amount of emissions as the recycling vehicles are utilised less often.
Concepts such as these are likely to be integrated more and more as we move forward, looking to streamline processes such as refuse collection and increase public safety and security through the integration of more security cameras as a couple of examples.
The opportunities that a more interconnected city can create are endless, which continues to drive our technological advances and integration of Edge and Fog devices.
However, as always the integration of more connected devices will inevitably attract more malicious actors looking to exploit these systems for their own means. It is essential, therefore, that as our smart cities grow, so too does our security posture.
Securing Edge and Fog devices in the future will be imperative to ensure the success of smart cities and consequently, they should be cemented into the foundations upon which they are built.
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