Since the beginning of the year, the secondary market has risen in response to the 5G concept, but also to edge computing.
The reason why edge computing is important is that even when 5G is really commercialised, it can achieve very large bandwidth (eMBB) application scenarios, but the emergence of huge data volumes also means that a take up point needs to be found in the cloud and end of the transmission process to pre-process the data before choosing whether to go to the cloud.
1. Edge computing in transportation
The rapid development of two industries in the foreseeable future is very clear, one is the communication industry, the other is the transportation industry, because the rapid development of society brings more information and physical communication, the exchange of information by communication, physical communication by transportation. Therefore, as a combination of the most advanced communication technology and transportation technology, the field of intelligent transportation has always been a focus of society.
Over the past decade, intelligent transportation has enabled the geometric growth of urban vehicles to access real-time road information, the world-renowned China High Speed Rail to keep running at high speed, and sailors on ocean voyages to conveniently talk to their families in real time. However, many of the technologies that the industry has been waiting for, such as autonomous driving and unattended rail transport, are still not fully realised.
Along with the development of new technologies, we are gradually moving into a fully connected "smart society", and the new technology of "edge computing" in the field of Internet of Things is being used in the field of intelligent transportation. This is a promising solution to a number of challenges that have long plagued the industry.
2. Edge computing in transportation
Edge computing refers to the deployment of computing power and services at the edge of the network through the IoT network to provide communication and computing services to nearby terminals, sensors and users, solving the challenges of massive heterogeneous connections, service real-time, service intelligence, data interoperability and security and privacy protection of IoT systems in highly distributed scenarios.
In layman's terms, in the future intelligent transportation application environment, "cloud computing" is equivalent to the brain of intelligent devices, handling relatively complex processes; while "edge computing" is equivalent to the nerve endings of intelligent devices, carrying out some "subconscious" responses.
The arrival of edge computing in transport makes intelligent transport more secure. Whether it's road, rail, sea or air, safety is the most important thing in the transportation industry. For example, the most important reason why self-driving technology, in which technology companies have recently invested so much, has been delayed is that it does not ensure absolute safety on the road.
The arrival of "edge computing" will help solve these problems. As with humans, our first reaction to danger is usually not cerebral, but "subconscious". For example, if a self-driving car needs to stop in time in the face of danger, if it still needs to upload data to the 'cloud', calculate the command to stop and then send it to the car, which then reacts. It would be better to give the vehicle itself some computing power to deal with this problem.
At the same time, we can also imagine a scenario in which a sudden natural disaster, signal interference or technical failure leaves self-driving cars and trains in a certain area without a network. They would then have to rely on the computing power given to them by edge computing in traffic to react "subconsciously" in order to ensure their safety.