Edge Computing: The Peripheral Nerves of Smart Transportation

A friend of mine once told me that in the predictable future, two industries will definitely go through rapid development. One of these is the communications industry, and the other is transportation. Rapid social development brings more information and physical exchanges, which rely on communications and transportation respectively. Therefore, as a combination of the most advanced communications and transportation technologies, smart transportation has always been a social focus.


Over the past decade, smart transportation enables exponentially increasing vehicles in cities to obtain the real-time road information. Smart transportation keeps China's renowned high-speed rails running properly, and lets sailors who are navigating across the seas communicate in real-time with family members and loved ones. However, many expected technologies such as driverless cars and unmanned railway transportation have still not yet been realized.


As new technologies are growing, we have ushered in an all-connected smart society, where the newly emerging edge computing of the IoT field is applied in the smart transportation industry. This appears to be a solution to numerous problems that has hassled the industry for a long time. With edge computing, computing capabilities and services are deployed at the network edge through IoT technology, providing communications and computing services to nearby terminals, sensors, and users. This also addresses challenges of numerous and heterogeneous connections, real-time services, intelligent applications, data optimization, as well as security and privacy protection. Simply, in a smart transportation environment in the future, cloud computing equals to the brain of a smart device that deals with complex processes. Edge computing is like the peripheral nerves of a smart device that makes subconscious actions.


Edge computing makes smart transportation safer. Safety is always the top priority for the transportation industry, regardless of whether it is on the highway, railway or even sea or air. Many technical companies have invested a lot in unmanned driving technology. However, the reason why it has not been put into commercial use is that absolute safety on the road cannot be guaranteed. However, edge computing will help address this problem. We human beings usually respond to dangers through subconscious actions instead of brain responses. For instance, if a driverless car needs to stop in case of a dangerous situation, it has to upload the data to the cloud, perform a computing process, and send the stop command to the car. The car finally acts upon the corresponding actions. In contrast, to settle this problem, it is better to enable the car to have a certain level of computing capability. Along with this, if we picture a scenario in which a sudden natural disaster were to take place and a signal interference or technological fault made driverless cars in this specific region connectionless. Edge computing would be the last straw for them to keep their passengers safe by making subconscious actions and decisions.


Edge computing makes the smart transportation system more economical. The IoT-enabled smart transportation system has considerably benefited relevant industries. For example, Disney deployed IoT pre-commercial networks in the outfield, and installed over 300 detectors. This has brought Shanghai Disney's parking system several benefits. First, the vehicle detector is plug-and-play, without the need to deploy network cables, making installation simple. Second, the narrowband IoT technology covers a long distance with signals reaching the underground's second floor. The detector has a long standby time of time of 10 years. Uniform query of parking spaces within a city or even across the country can be implemented, which improves parking space utilization and help drivers find empty parking spaces quickly. In the future, edge computing can fully utilize its strength in making the transportation industry more economical. For example, a major obstacle to the realization of autonomous transport in the urban railway transportation system is the screen door. Currently, a screen doors open/closed status is based on the driver's own personal judgment. That is, all doors are closed when the last passenger gets onboard. This indicates that the entire screen door system needs not only a brain, but also peripheral nerves. If detection and control devices are installed on each screen door, the door has the edge computing capability to control its status in an independent and secure manner. This will undoubtedly make the urban railway transportation system more economical, and make autonomous transport a reality. It can be said that cloud computing enables the brain of the smart transportation system to be cleverer, and edge computing makes its peripheral nerves more sensitive. Both of the two technologies are critical to improving the operation efficiency and economical value of the transportation industry.


Edge computing also brings more value-added services to passengers and improves their experience. For example, Huawei provides Bus Online with an integrated smart Internet of Vehicles (IoVs) solution. In-vehicle smart mobile gateways are deployed on each bus to carry a unified operating platform, which uniformly schedules multimedia terminals distributed in different sites and realizes three-dimensional and differentiated precision marketing. Through this method, passengers have better experience in vehicles. The in-vehicle smart mobile gateway functions as peripheral nerves, which can cache data to ensure the vehicle's smooth operation in places with poor signals. Similarly, this kind of technology provides a good reference for offering passengers' network service in the railway transportation field. For example, if such devices are used on subways to cache information in stations with decent network signals, passengers will gain better on-line experience when they are in sections with poor signals.


It is obvious that edge computing brings many opportunities to the smart transportation system. However, its development is posed with some difficulties. Firstly, edge computing devices are always kept in environments with extreme temperatures, too low or too high or high humidity. It is of utmost significance to keep devices' long-time running a key goal in such environments. Secondly, the buffer and computing capabilities of edge computing devices are based on actual tasks which require vendors to provide customized products. Lastly, edge computing devices are applied in all links in the transportation system. Making unified production standards calls upon some major enterprises in the smart transportation field to formulate standards and norms.


To our satisfaction, six industry entities have joined together to establish the Edge Computing Consortium (ECC). The entities include Huawei Technologies Co., Ltd., Shenyang Institute of Automation of Chinese Academy of Sciences, China Academy of Information and Communications Technology (CAICT), Intel Corporation, ARM Holdings, and iSoftStone. This is promising news for settling all the problems mentioned above. In terms of transportation, the ECC will technically support the industry, and work with multiple partners to make and perfect standards based on a large number of practical cases. We believe that in the future, the ECC will make more technological breakthroughs to the edge computing field in smart transportation, formulate more standards, and improve our daily transportation experience.

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To promote in-depth industry coordination, accelerate innovation, and boost the application of edge computing, six industry entities have joined together to establish the ECC. The ECC is dedicated to advancing cooperation among industry resources from government, vendor, academic, research, and customer sectors, and pushing forward the sustainable development of the edge computing industry.
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