Contributed by Chen Guangcheng

An ordinary elevator has more than 700 sensors and over 30 sensors just for opening and closing the door. An elevator seems simple, but it is actually a complex system.

Statistics show that, by 2015, the number of elevators in the world exceeded 15 million, and the number of elevators in the world will reach 20 million by 2020. This huge number of elevators, in addition to carrying busy city folk and things every day, are also generating and transmitting a large amount of data. How can this data be transmitted, saved, and analyzed to help the O&M personnel control the elevator’s real-time status and ensure it runs safely and reliably?

Some people may say it needs to move to the cloud. Indeed, moving to the cloud is a trend that is imperative—but is this enough? The elevator is just one of the many types of industrial IoT devices that are in huge quantities and are widely distributed. If the huge volume of data collected by these devices is uploaded to the cloud for analysis and processing, a huge burden will be placed on the network, causing huge connection costs. In addition, if data analysis and control logic are moved to the cloud, real-time requirements of key services cannot be met.

Therefore, in the cloud era, all data needs to be summarized on the backend data center for calculation. However, with the advent of the era of the connectivity of everything, a new technology and market has emerged—Edge Computing.

Edge Computing Injects New Energy into Making Industries Intelligent

The essence of edge computing is to provide intelligent services at the network edge and close to data sources, and to inject new energy into the digital transformation of industries. This provides real-time data analysis and service response for industry applications.

The elevators connection solution in edge computing scenarios, for example, deploys edge computing gateways connecting to elevator controllers and many types of sensors to collect elevator running data in real time. Based on local light-weight data analysis models, the gateways implement real-time pre-analysis of data such as the elevator noise frequency and strength, helping predict and quickly detect potential faults on elevators. They also send the data to a cloud-based Big Data analysis platform for analysis, through which a customer can obtain the status of each component of the elevators. The gateways then receive the analysis results from the platform and optimize the data analysis models to implement more intelligent predictive maintenance of elevators. That is, the solution helps customers learn potential elevator faults in advance and maintain elevators in time.

Taking city water as an example, at HUAWEI CONNECT 2017 in September, Huawei and Wapwag jointly released innovative practices based on the open Edge Computing IoT (EC-IoT). These practices leverage open EC-IoT to adapt to various scenarios, such as coexisting new and old water supply devices, multiple vendors, and various interfaces and protocols. This meets the requirements for intelligent edge data processing in different water management scenarios and implements smart water supply. The smart water solution based on edge computing can monitor device and water quality in real time, predict device faults, and help water companies or operation management departments improve water supply security and quality while reducing operating costs.

Without a doubt, there are many scenarios in which the digital transformation of industries has been facilitated using edge computing, including intelligent manufacturing, electric power, city lighting, and healthcare. Edge computing can help to achieve a large number of connections, real-time responses, data optimization, intelligent analysis, and security control, and quickly obtain the dividends of digital transformation in these industries.

At Huawei, we believe intelligence is the ultimate goal of digitally transforming various industries. Intelligence is based on the intelligent analysis of data, thereby achieving intelligent decision-making and operations. Continuous and intelligent optimization of business processes is implemented through closed-loop management. Industry intelligence is progressing towards 3.0, which is the collaboration between physical data and business data that is represented by full process collaboration. In this case, intelligence needs to be distributed to the edge of the network, realizing the autonomation and collaboration of things. Edge computing will undoubtedly accelerate the advent of intelligent industry 3.0.

Huawei EC-IoT Supports Edge Computing Application Implementation and Innovation

Huawei focuses on the smart interconnection of edge computing. At the Mobile World Congress 2017 (MWC 2017), Huawei launched the EC-IoT Solution. The EC-IoT solution includes the terminal communication module, edge computing gateway (AR series), and Agile Controller. The solution provides in-depth and open edge computing, cloud-based centralized management, and a variety of industrial protocols and interfaces to create IoT solutions that adapt to industries.

Terminal communication modules support the smart interconnection of sensor networks containing a large number of IoT terminals. Edge computing gateways provide smart services in immediate areas, and the Agile Controller can be connected by industry application systems of different partners through open Application Programming Interfaces (APIs) or the Ecosystem Software Development Kit (eSDK). The solution uses the cloud management architecture to implement smart interconnection and efficient management of a large number of unattended terminals in various industries.

The EC-IoT gateway supports multiple industrial interfaces and industrial proprietary protocols. It has an industrial-level design and can adapt to complex industrial environments, and provides open container capabilities. It can also install software customized for industries, implementing distributed computing at the network edge. Data can be preprocessed locally, improving timeliness and security.

Cloud management of IoT gateways and countless IoT terminals can be implemented through the Agile Controller. With cloud management, the Agile Controller provides full lifecycle management covering IoT planning, deployment, and O&M. Additionally, through the GIS-based management component, it supports real-time monitoring of network-wide statuses, plug-and-play of masses of devices, and automatic service deployment, greatly shortening service provisioning time and slashing OPEX by over 50%.

Huawei’s EC-IoT solution facilitates open integration with partners by providing open edge computing capabilities and cloud management capabilities. The solution provides various open APIs and eSDK and allows common protocols to openly interconnect with industry application systems of different partners to establish extensive industry adaptability.

We Can Go Further Together—the Edge Computing Consortium Accelerates the Implementation of Industry Applications

It has to be said that although edge computing presents powerful capabilities, there are still challenges. Edge computing covers multiple fields such as operational technology (OT), information technology (IT), and communication technology (CT), involving multiple industry chain roles, such as network connectivity, data aggregation, chips, sensors, and industry applications. In addition, edge computing faces the challenges of technology fragmentation.

To promote in-depth industry coordination and accelerate digital innovation and industry application implementation by edge computing in various industries, the Edge Computing Consortium (ECC) was founded by Huawei Technologies Co., Ltd. together with Shenyang Institute of Automation Chinese Academy of Science, China Academy of Information and Communications Technology (CAICT), Intel, ARM and iSoftStone Technology Service Ltd.

The number of ECC members is increasing. By the end of October 2017, its members had increased from the original 62 to 136, including 20+ leading vendors. Three industry committees have been established: Smart Street Lamp, Smart In-Vehicle, and Edge Monitoring. Five working groups have also been established: Requirement and System Group, Technical Standards Group, Security Group, Experiment Platform Group, and Market Promotion and Cooperation Group. Currently, the application, review, and execution of the ECC’s first 11 test beds are complete, covering valued industries such as electric power, transportation, industrial manufacturing, and smart cities, and accelerating the commercial monetization of this industrial alliance.

The second ECC will be held at the end of November this year. Let’s look forward to the spectacle to be put on by industry players.

Register online:

https://www.ecconsortium.net/meeting/ECIS2017/english.html

The post Only When Computing Gets Close to the Network Edge Will Industries Become Intelligent appeared first on Huawei Enterprise Blog.

Source: Huawei Enterprise Blog
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