Edge Computing comes into play when using web apps, doorbells and cars – each system needs to process massive amounts of real-time information which often occurs in remote areas with limited bandwidth and connectivity – this process often determines whether users enjoy an enjoyable or disappointing digital experience. Edge Computing helps make these digital interactions smooth.
Edge computing allows for local data processing rather than relying on central servers or cloud infrastructure for handling tasks, with the aim of improving responsiveness and reducing latency. Edge Computing is widely utilized across OT, IoT, autonomous vehicle and AR/VR applications – it works by sending only certain processing requirements to the cloud and having devices at the network edge take care of the rest – providing improved security as well as reduced backhaul costs.
As data is collected, it’s sent to an edge server for processing and analysis, before being sent either back into the cloud for more complex processing and storage or left at its origin. A motion sensor might send raw footage directly to a cloud-based server; however if smart cameras save only important events as save points instead this could significantly decrease bandwidth usage.
Bring processes closer to the network edge can also reduce security breaches by keeping sensitive information close at hand. Being able to monitor and control data more safely can help companies enforce privacy policies, meet regulatory compliance, meet privacy standards, as well as make devices that are less vulnerable to attack by hackers.
Example: A security camera capable of detecting unauthorised activity and alerting company security teams almost instantly would provide much greater protection than one that must send alerts via a central server.
Edge computing has seen immense growth across industries, particularly transportation. When used to support self-driving cars, edge computing technology can reduce transmission delays between sensors and cloud-based decision-making systems to enhance driving safety while optimizing traffic management systems by preemptively anticipating road conditions and responding accordingly.
Smart Cities have emerged with this architecture at their center, where local governments can monitor traffic, air quality and other environmental factors in real-time to provide residents with a higher quality of life. For instance, in an air polluted city edge-enabled sensors could quickly notify residents about health risks caused by pollution before providing directions to nearby hospitals – this approach being far more feasible than current systems that require citizens either calling an ambulance or visiting websites to find where these institutions can be found.
