Contributed by Kang Xiang
Traffic jams must be one of the biggest annoyances of living in a city.
As a commuter, you must have experienced the feeling of being tired not at work, but on the way to work. Real-time traffic condition on a mobile map is like a barometer of our mood: green meaning joy, and red meaning sadness.
In fact, we should feel relieved. At least we can use the relatively accurate real-time traffic condition on a mobile map to plan our trips. For example, we can work a few extra hours to avoid traffic jams. Ten years ago, when real-time traffic condition analysis was not yet available, we had to rely on luck during our journeys.
Cities are becoming more and more intelligent, with real-time traffic condition analysis and intelligent route recommendations. With the development of technologies such as the mobile Internet, Internet of Things (IoT), cloud computing, Big Data, and artificial intelligence (AI), public utilities such as transportation, electricity, water, elevators, and buildings have undergone huge changes.
Cities that used to be considered as concrete jungles also seem to become smarter, and more convenient and humane.
New Chapter for Cities
As residents of the city, we can feel many changes.
Thanks to the wide-spread use of smart meters, we can now purchase electricity from the comfort of our homes. We do not have to wait in long queues to pay the electricity bills, avoiding the awkward situation of a sudden power outage. After entering a smart parking lot, we can quickly find parking spaces by following a mobile app’s instructions, without having to scour the parking lot for a space. When leaving, we pay parking fees using Apple Pay or other smart payment modes. Meat, fruits, and many other foods can be traceable through barcodes and QR codes, ensuring food safety.
These form just the tip of the iceberg in terms of the changes that Connectivity of Everything will bring to our society. In the future, cities will undergo great changes due to the widespread application of new technologies such as IoT.
According to a report by IDC, more than 50 billion terminals and devices will be connected by 2020. Massive numbers of sensors in every corner of a city make up a huge “nervous system”, and each pulse of urban production and life is transmitted to the “brain” for analysis. We can find out rules of urban operation and root causes of problems, and make improvements, making city life smarter.
For example, smart transportation solutions ensure transportation safety, ease traffic congestion, and reduce traffic accidents. According to related analysis, smart transportation solutions can reduce the rate of traffic accidents by more than 20%, death toll caused by traffic accidents by 30% to 70% each year, and traffic congestion by about 60%. In addition, short-distance transportation efficiency is improved by nearly 70%, and road network capacity is increased by 2 to 3 times.
Smart water solutions can improve security of residents’ water supply, and enables timely monitoring, fault detection, and automatic fault diagnosis of water supply equipment, improving water supply reliability and efficiency. Connection of elevators can achieve predictive maintenance, reduce operations and maintenance (O&M) costs of elevators, and improve elevator reliability and user experience. Smart building solutions enable automatic building management and control, and reduce energy consumption and greenhouse gas emissions.
Connectivity of Everything creates an ideal blueprint for our lives, but the following technical challenges must be solved:
Connection: Sensors and terminals use different standards, and there are a large number of heterogeneous bus connections. It is imperative to figure out how to enable compatibility of various connections and ensure real-time and reliable connections. Additionally, with the massive increase in the number of connected devices, network O&M and management, flexible expansion, and reliability are facing enormous challenges.
Real-time service: Real-time responses are required in many scenarios, such as connection of elevators and autonomous cars. A large number of real-time processing scenarios exist in the industrial field, which requires responses within milliseconds. If data analysis and control logic are implemented on the cloud, it is difficult to meet real-time requirements of services.
Optimization of data: A large amount of diverse and heterogeneous data exists in many scenarios. Networks will be pressed if all the data is sent to the cloud.
Smart application: Smart applications, such as predictive maintenance, are driving industries to transition to new service and business models.
Security and privacy protection: In the future, there will be hundreds of billions of IoT devices. These devices are close to the network edge, making access control and threat preventing very difficult. Hackers can easily take advantage of a large number of edge nodes to initiate attacks, or even intervene in the cloud using edge nodes. Therefore, it is critical to ensure security of devices, networks, data, and applications.
Cloud computing has long been considered the pillar of IoT. However, the preceding challenges (CROSS) cause cloud computing to underperform in a lot of scenarios. As a result, a new computing system — edge computing — becomes another pillar of IoT.
Edge Computing Empowers Smart Cities
Edge computing is a distributed open platform that converges the core capabilities of networks, computing, storage, and applications at the network edge close to things or data sources. Edge computing delivers intelligent services nearby. Its emergence is to solve the “CROSS” issues facing IoT.
In this respect, edge computing is clearly differing from cloud computing.
Cloud computing carries and connects cloud applications, beyond which is the network edge that is within the scope of edge computing. Edge computing bridges the physical and virtual worlds and provides the network edge with localized reliable, efficient, and secure computing capabilities.
Cloud computing focuses on non-real-time, long-term Big Data analytics across service sub-domains, and supports business decision-making. Edge computing emphasizes real-time and short-term data analysis, and better supports real-time intelligent decision-making and execution for local services.
Cloud computing is centrally deployed, while edge computing is geographically dispersed. Cloud computing needs to be deployed in equipment rooms where the temperature and humidity are guaranteed. Edge computing is deployed in harsh environments with extreme temperature, humidity, dust, electromagnetic, vibration, and other conditions.
However, no matter in smart cities or other IoT application scenarios, edge computing is no substitute for cloud computing. The two technologies focus on different aspects and coordinate well with each other.
Edge computing is close to execution units and can collect high-value data required by the cloud, thereby better supporting Big Data analytics of cloud applications. Through data analysis approaches such as machine learning and AI, cloud computing is used to establish digital models, generate optimized service rules, and deliver the rules to the network edge. Based on the new service rules, edge computing implements decision-making and execution for optimizing services.
So, what scenarios is edge computing applied to?
Again, let’s take a smart city for an example.
Connection of elevators: The number of global elevators has exceeded 15 million and continues to grow. The reliability of elevators, however, has increasingly become a concern, and elevators are faced with many issues such as aging, O&M difficulties, and frequent accidents. Traditional manual inspection approaches have low maintenance accuracy and require high labor costs.
Connection of elevators can address these issues. Through predictive maintenance, connection of elevators enables real-time monitoring of elevators’ operation data and on-demand maintenance in advance. This approach greatly reduces the failure rate of elevators and O&M costs, thus ensuring elevator security.
In the Industrial Cloud-based Predictive Maintenance Solution launched jointly by Huawei and GE, edge computing gateways achieve real-time fault prediction by enabling local optimization, aggregation, and real-time analysis of elevators’ operation data. The solution helps Schindler centrally connect and manage millions of elevators around the world, and slash O&M costs while driving product and service innovation.
Smart water: Water supply systems directly affect people’s water use experience and water quality. Maintenance of water supply equipment and water quality monitoring have become great challenges for water affairs companies or operation and management authorities. In smart water solution, the edge computing IoT connects power supply equipment, and monitors the real-time working status of water supply equipment and water quality, ensuring water supply safety and quality, and reducing operation costs.
Huawei launches the Smart Water Solution jointly with Wapwag. This solution uses edge computing gateways to monitor the working status of water supply equipment and water quality in real time. Based on Big Data analytics, the solution helps predict device failures, and assists water affairs companies or operation and management authorities in reducing the failure duration by 70% and manpower maintenance costs by 80%, ensuring water supply quality.
In today’s world, edge computing is playing an important role in smart cities, not only in connection of elevators and smart water, but also in the transportation, energy, electricity, building, public safety, and government sectors.
ECC Vitalizes the Edge Computing Ecosystem
Great success cannot be achieved by individuals alone. Similarly, although edge computing is critical for IoT implementation, promotion and business implementation of edge computing require close collaboration of enterprises and organizations across the industry chain, and a favorable ecosystem.
Viewed from the current situation, the edge computing development is optimistic.
Edge computing is supported by the academia. In 2015, the Institute of Electrical and Electronics Engineers (IEEE) and Association for Computing Machinery (ACM) jointly established IEEE/ACM Symposium on Edge Computing, which is an academic forum recognized by the academia, major industries, and government (National Science Foundation, United States). It carries out research and discussions on the application value and study directions of edge computing.
Edge computing is also supported by various standards organizations. In Q4 2017, the International Eletrotechinical Commission (IEC) (an authoritative standards organization) launched the Vertical Edge Intelligence (VEI) white paper, and the ISO/IEC JTC1 (an authoritative standards organization in the ICT field) set up an edge computing research team to promote edge computing standardization.
The Edge Computing Consortium (ECC) accelerates industry and business implementation of edge computing.
In November 2016, the ECC was established jointly by Huawei, Shenyang Institute of Automation, China Academy of Information and Communications Technology, Intel Corporation, ARM, and iSoftStone. The ECC’s vision is to lead development of the edge computing industry and promote digital transformation of various industries.
By the end of October 2017, the number of ECC members has increased to 136 from its original 62. The members include world-renowned enterprises, such as Mitsubishi, Bosch, Schindler, Schneider, Phoenix, Volkslift, Wind River, Infosys, McAfee, and ABB. In the last year, the ECC has established official relationships with international standards organizations such as IIC, IEC, JTC-1 SC41, IEEDP2413, CAA, and SDNFV.
To promote the implementation of edge computing in smart cities and the industry field, the ECC establishes three expert committees: smart streetlight, smart in-vehicle, and smart monitoring. The ECC, working together with industry partners, constructed more than 11 test beds involving the manufacturing, smart city, power energy, and transportation sectors.
According to IDC reports, by 2018, 50% of IoT networks will have limited bandwidth, and 40% of data will need to be processed, handled, and stored on network edges. This means that edge computing will play an important role in the future.
With the joint effort of the academia, standards organizations, and ECC, the edge computing ecosystem will be more prosperous, become a major force for IoT implementation, and a key to an intelligent world.
The Edge Computing Industry Summit 2017 will be held at the end of November 2017, and will centrally demonstrate the power of the edge computing ecosystem.
Register online:
https://www.ecconsortium.net/meeting/ECIS2017/english.html
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Source: Huawei Enterprise Blog
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