What Industries Can Edge Computing Be Applied To?
Trend

What Industries Can Edge Computing Be Applied To?

Edge computing technology is an extension of cloud computing. It can improve the analysis technology of cloud data. It is a concept of nearby computing. Its technology is gradually applied to various industries so that each industry can break through the existing restrictions and increase its productivity and efficiency.
Published: May 29, 2020
What Industries Can Edge Computing Be Applied To?

What is edge computing?

Edge computing is a concept of nearby computing (decentralized computing architecture). Computing is performed in the local area network where the resources are located closer to the cloud. As far as possible, data is not returned to the cloud, reducing the cost of data traveling to and from the cloud. The difference from the cloud is that the network center node is moved to the edge node position on the network logic for processing.

As sensor prices and computing costs continue to fall, more "things" will be connected to the Internet. As more networked devices become available, edge computing will find more and more applications in all walks of life, especially in areas where cloud computing is inefficient. We have begun to see the impact of edge computing technology in many different industry sectors.

"When we sink the power of the cloud to the device (that is, the edge), we can bring the ability to respond, analyze and act in real-time, especially in areas with limited network conditions or lack of network ... it is still in the early development stage, But we are beginning to see that these new features can be applied to solve some of the major challenges worldwide. ”-Microsoft Chief Technology Officer

Which industries are edge computing used in?

From self-driving cars to agriculture, the following separately analyzes how several industries combine edge computing technology to achieve greater benefits.

  1. Transportation Industry
    One of the most obvious potential applications of edge computing technology is transportation, more specifically driverless cars. Self-driving cars are equipped with a variety of sensors, from cameras to radars to laser systems, to help vehicles run.
    As mentioned earlier, these self-driving cars can use edge computing to process data closer to the vehicle through these sensors, thereby reducing the response time of the system during driving as much as possible. Although driverless cars are not the mainstream trend, companies are planning. Earlier this year, the Automotive Edge Computing Consortium (AECC) announced that it will start projects focused on connected car solutions. "Connected cars are rapidly expanding from luxury models and high-end brands to high-volume mid-range models. The automotive industry will soon reach a tipping point when the amount of data generated by cars will exceed existing cloud, computing, and communications infrastructure resources "-Chairman and President of AECC. Members of the alliance include DENSO Corporation, Toyota Motor Corporation, AT & T, Ericsson, Intel, and other companies.
    However, it's not just self-driving cars that generate a lot of data and need to process it in real-time. The same is true of planes, trains, and other means of transportation-whether or not they are driven by humans. For example, the aircraft manufacturer Bombardier (Bombardier) C series aircraft is equipped with a large number of sensors to quickly detect engine performance problems. During the 12-hour flight, the aircraft generated up to 844 TB of data. Edge computing supports real-time processing of data, so the company can proactively deal with engine problems.
  2. Healthcare industry
    Today, people increasingly like to wear fitness tracking devices, blood glucose monitors, smartwatches, and other wearable devices that monitor their health. However, to truly benefit from the massive data collected, the real-time analysis may be essential-many wearable devices are directly connected to the cloud, but other devices support the offline operation.
    Some wearable health monitors can analyze pulse data or sleep patterns locally without connecting to the cloud. The doctor can then assess the patient on the spot and provide immediate feedback on the patient's health. But in the healthcare field, the potential of edge computing is far from being limited to wearable devices. Think about how fast data processing can bring benefits to remote patient monitoring, inpatient care, and medical management in hospitals and clinics.
    Doctors and clinicians will be able to provide patients with faster and better care, while the health data generated by patients also have an additional layer of security. Hospital beds have an average of more than 20 networked devices, which generates a lot of data. The processing of these data will happen directly closer to the edge, rather than sending confidential data to the cloud, thus avoiding the risk of improper access to the data. As mentioned earlier, the localized data processing means that large-scale cloud or network failures will not affect business operations. Even if the cloud operation is interrupted, the sensors of these hospitals can operate independently.
  3. Manufacturing industry
    Smart manufacturing is expected to gain insights from the sensors deployed in modern factories.
    Because it can reduce lag, edge computing may enable the manufacturing process to respond and change more quickly, and it can apply insights and actions in real-time from data analysis. This may include shutting down the machine before it overheats. A factory can use two robots to accomplish the same task. The two robots are equipped with sensors and connected to an edge device. Edge devices can predict whether one of the robots will fail by running a machine learning model.
    If the edge device determines that the robot is likely to malfunction, it will trigger actions to prevent or slow down the robot's operation. This will enable the plant to assess potential failures in real-time. If robots can process the data themselves, they may also become more self-sufficient and responsive. Edge computing should support more insights from big data faster, and support the application of more machine learning technologies to business operations. The ultimate goal is to tap the huge value of the massive amounts of data generated in real-time, prevent potential safety hazards, and reduce machine outages on the factory floor.
  4. Agriculture and smart farm industry
    Edge computing is very suitable for agriculture, because farms are often in remote locations and harsh environments, and there may be problems with bandwidth and network connectivity.
    Now, smart farms that want to improve network connectivity need to invest in expensive fiber optics, microwave connections, or have a satellite that operates 24/7; and edge computing is a suitable, cost-effective alternative. Smart farms can use edge computing to monitor temperature and equipment performance, and automatically slow down or shut down various equipment (such as overheated pumps).
  5. Energy and grid control industry
    Edge computing may be particularly effective in the entire energy industry, especially in the safety monitoring of oil and gas facilities.
    For example, pressure and humidity sensors should be closely monitored and cannot make mistakes in connectivity, especially considering that most of these sensors are located in remote areas. If an abnormal situation occurs-such as an overheated tubing-but it is not noticed in time, then a catastrophic explosion may occur. Another benefit of edge computing is the ability to detect equipment failures in real-time. Through grid control, sensors can monitor the energy generated by everything from electric vehicles to wind power plants, helping to make corresponding decisions to reduce costs and improve energy production efficiency.
  6. Application in other industries
    Other industries that can take advantage of edge computing technologies include finance and retail. Both industries use large customer and back-end data sets to provide everything from stock-picking information to in-store clothing placement, which can benefit from reducing dependence on cloud computing.
    Retail can use edge computing applications to enhance the customer experience. Today, many retailers are working to improve the in-store experience, and optimizing the way data is collected and analyzed is meaningful to them-especially considering that many retailers are already experimenting with connected smart displays.
    Also, many people use point-of-sale data generated by in-store tablet computers, which will be transferred to the cloud or data center. With edge computing, data can be analyzed locally, reducing the risk of sensitive data leakage.

To conclude: From wearable devices to cars to robots, IoT devices are showing an increasingly strong development momentum.

As we move towards a more interconnected ecosystem, data generation will continue to increase rapidly, especially after 5G technology has taken off and further accelerated network connectivity. Although a central cloud or data center has traditionally been the first choice for data management, processing, and storage, these two solutions have limitations. Edge computing can serve as an alternative solution, but because the technology is still in its infancy, it is difficult to predict its future development.

Equipment capabilities challenges-including the ability to develop software and hardware that can handle off-load computing tasks in the cloud-may emerge. It is also a challenge to teach the machine to switch between computing tasks that can be performed at the edge and those that need to be performed in the cloud.

Even so, as edge computing becomes more adopted, companies will have more opportunities to test and deploy this technology in various areas. Some use cases may prove the value of edge computing better than others, but overall, the potential impact of edge computing technology on our entire interconnected ecosystem will be unpredictable potential, and we look forward to the future development of edge computing.

Published by May 29, 2020 Source :kknews

Further reading

You might also be interested in ...

Headline
Trend
Grinding Robots and Human Machine Collaboration
The integration of robotics into grinding processes can greatly transform traditional manufacturing into dynamic environments where human workers and robots collaborate seamlessly. While robotics offers precision, consistency, and efficiency, skilled operators are essential for the efficient operation of advanced grinding machines. Training programs are important to provide hands-on education, certification, and expertise in setup, operation, and troubleshooting for optimal performance.
Headline
Trend
Keyless Digital Electronic Door Locks: The Evolution of Security
We've all had the experience of returning home with our hands full, juggling packages while fumbling for keys. However, there are innovative solutions that prevent this predicament by eliminating the need for traditional keys. Keyless digital electronic door locks utilize a variety of technologies to provide secure, flexible access control without the traditional key. Advanced technologies that use various forms of authentication, such as codes, biometrics, and smartphones, not only streamline your entry process but also enhance the security of your home.
Headline
Trend
Refining the Essence: Three Fundamental Pillars of Smart Industrial Manufacturing
The conventional manufacturing sector stands at a crossroads necessitating a shift towards intelligent transformation. By incorporating advanced production technologies, a new era of industrial development is inaugurated.
Headline
Trend
The Role of Artificial Intelligence in Autonomous Vehicles
Utilizing machine learning and neural networks, artificial intelligence (AI) plays a crucial role in enabling the autonomous operation of self-driving cars. These vehicles leverage a combination of sensors, cameras, radar, and AI to navigate between destinations without the need for human intervention. For a car to be considered fully autonomous, it should demonstrate the capability to independently navigate predetermined routes without human input, even on roads that have not been specifically modified for autonomous vehicle use.
Headline
Trend
Worldwide Bicycle and Electric Bicycle Market Overview
The global increase in environmental consciousness has resulted in a shift for bicycles from primarily sporting and recreational roles to becoming popular modes of commuting. Notably, the rising adoption of electric bicycles is driven by factors such as an aging population, contributing to a significant upsurge in the global production of electric bicycles in recent years.
Headline
Trend
Opportunities and Trends in the Application of 5G in Smart Grids
In recent years, developed nations have initiated comprehensive power grid upgrade initiatives. In line with its commitment to energy conservation and carbon reduction policies, Taiwan has advanced the implementation of Automated Metering Infrastructure (AMI) as part of its national energy-saving strategy. The plan encompasses the integration of 4G/5G and other communication industries. The noteworthy progress in the development and integration of smart grid applications with 5G communication technology represents a significant industrial advancement deserving of attention.
Headline
Trend
Confronting the Era of Digital Advancement, Facial Recognition Technology Has Enhanced
Recently, there has been widespread discussion about Artificial Intelligence, Machine Learning, Deep Learning, and Big Data. These technologies find application in various domains such as the financial industry, logistics, business analysis, unmanned vehicles, computer vision, natural language processing, and more, permeating every facet of daily life.
Headline
Trend
The Arrival of 5G Technology Marks a Shift in Business Transformation, Redefining Innovations in the Manufacturing Sector
5G is recognized as a key enabler of Industry 4.0. With its high network speed and low power consumption, 5G facilitates the connectivity of every sensor in the upcoming unmanned factory to the cloud. This connectivity allows for the extraction of data for analysis, ultimately fueling advancements in artificial intelligence.
Headline
Trend
How Can Humans Collaborate with Robots in a Work Environment?
The integration of collaborative robots into production has become a pivotal element in the manufacturing chain, enhancing overall production efficiency. These compact collaborative industrial robots are designed to operate in confined spaces, addressing challenges posed by limited working spaces.
Headline
Trend
Can 3D Printing Be Applied in the Die and Mold Industry?
As the utilization of 3D printing expands across the broader spectrum of industrial manufacturing, the significance of this technology extends beyond its role as a rapid prototyping tool. This article provides an overview of the applications of 3D printing in the fabrication of molds and dies for processes such as injection molding and die casting.
Headline
Trend
Tooling 4.0: Bridging Industry 4.0 with Mold Manufacturing for the Future
Are you familiar with the latest terminology related to Tooling 4.0? In this article, we'll offer an overview and examples that can help manufacturers understand and align with this evolving concept. Tooling 4.0 revolves around leveraging technology to transform 'inefficient' products into 'intelligent' ones.
Headline
Trend
Industry 4.0 Propels the Global Industrial Market Towards Automation
In the present day, conventional industries are blending Internet of Things technology to drive the evolution of Industry 4.0 and the advancement of smart manufacturing.
Agree