Intel's new report, "The Edge Outlook“; identifies the” edge computing» as an important factor that companies must take advantage of to successfully evolve and understand data both now and in the future. The world in which they operate is changing, at an accelerated pace due to the Covid-19 pandemic, the climate crisis and the increase in social and political tensions.
You are being asked to step forward to help society meet these new challenges as our dependence on technology increases. The digital transformation and a general demand for computing power has been driven. Intel is moving into distributed intelligence, a technological inflection point that will allow companies to keep up with this pace of change. They want to bring computing closer to data sources at the edge - that is, all the data endpoints that exist outside of the data center, from smartphones and PCs to IoT devices and sensors. They claim that it is the only way to manage the volume of data that is being generated now.
Edge computing will also play a critical role in enabling companies to leverage the benefits of 5G and AI to turn ambitious ideas into reality. Some examples of its use are boosting operational efficiency to create new products and open up new revenue streams.
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Advantage is the key to generating innovative opportunities
We have entered a new era of computing in which distributed intelligence is present. IDC predicts that by 2025, every connected person in the world will have at least one digital data interaction every 18 seconds, likely from one of the billions of IoT devices, which are expected to generate more than 90 ZB of data by 2025. This opens up a series of growth opportunities, such as automation and hyper-personalization.
Seizing these opportunities requires that data be harnessed for value. Sending all the usage data that is generated every second along with data back to the cloud for processing would not be practical. There would be problems due to latency and the large volume of data involved, and this is where the term comes in Intel edge computing.
CIOs know that data strategy must be a top priority, and recent research from HPE Aruba shows that they are recognizing that real-time data analytics closer to the edge drive greater efficiency and insights. With this better efficiency it is possible to improve commercial results. 72% of IT leaders are already using Edge technologies to deliver new results.
A recent IDG survey found that identifying clear use cases, security, lack of internal skills, and cost concerns are among the top considerations when adopting this technology. This suggests that CIOs are beginning to understand the value of the advantage of working toward a future where data is no longer stored where it has no value. But companies that adopt cutting-edge technologies can move, process and extract value from this data in real time, which is the key to innovation. With numerous examples of edge implementations already generating real business value across multiple industries.
Intel Edge Computing Uses for Industry Optimization
El edge computing of Intel is already being carried out in digital services working in synergy with critical technologies such as Artificial Intelligence and 5G. Among Intel customers alone, there are more than 24 edge computing deployments that create real business value and help companies grow and innovate with their distributed intelligence.
Retail sales sector to improve inventory management
The retail sector is the one that most demands cutting-edge technology to help them overcome current challenges such as accelerating their digital transformation. Intel edge computing will offer competitive advantages to retailers such as greater efficiency and better customer experiences. It will be instrumental in helping retailers thrive in the future of commerce shaped by unprecedented levels of engagement, customization, and convenience. There will be two opportunities for retail companies that will be the insights generated by edge computing.
The first is being able to be correcting massive amounts of inventory distortion, and making supply chains and product development more efficient. Machine vision is being used to address this challenge by enabling predictive inventory and supply chain control, ensuring critical materials are in the hands of those who need them most.
The other great benefit is providing real-time consumer behavior analytics to deliver greater convenience and more engaging and personalized experiences. Today's digital signage and interactive kiosks are connected, smart and responsive, with smart sensors and cameras that make it possible for kiosks to recognize products, respond to non-contact gestures, and even address loss prevention. Vision capabilities for AI-powered analytics also allow retailers to know when an advertising message is effective. One example is the luxury boutique Wonderstore, which uses visual sensors and real-time analytics to personalize store experiences based on fashion choices, sentiment, and customer dwell time. Wonderstore's storefront conversion rate has improved by 17% and it has been able to streamline staff management and create experiences that extend the customer journey beyond the physical store. Another case is the autonomous tents that allow comfort and security without contact.
Data flowing from supermarket shelves, conveying important information about inventory, traffic flow, purchase frequency, and dwell time, can be combined with sensors, computer vision, and robotics to provide automated checkouts and shopping experiences as soon as you leave the point of sale. Artificial intelligence and video analytics powered by Edge technology can also identify potential criminal behaviors in real time, such as theft and changing labels, whether in a stand-alone store or otherwise to save stores money and enable an environment safer purchase.
Industrial sector to drive transformative results
Technologies edge computing Intel are driving a new industrial revolution that unites digital and physical technologies to create more flexible, responsive and interconnected companies that make better decisions faster. Its potential to transform industrial processes is due in large part to the amount of raw data generated by the machines in the sector.
One such use case is condition-based monitoring and predictive maintenance. Hyper-converged edge data centers perform analysis and filter data locally for faster assessment of asset health. This opens up the possibility of maintenance contracts based on the actual condition of the machine. Work is also being done to eliminate human error and manufacturing limitations.
With the help of machine learning, Intel's edge computing technology collects, aggregates, and filters data from multiple machines, processes, and systems to tailor the manufacturing process in real time and provide precision monitoring and control. Artificial intelligence-based robotic process automation systems are being used to perform repetitive and potentially dangerous tasks with greater speed and precision than humans, and machine vision is being used to validate functions and check for defects, helping to provide the highest possible performance.
These implementations of edge computing helped Audi increase the number of weld inspections 100 times with a latency of 18 ms and reduce labor costs by 30 to 50 percent at its Neckarsulm plant in Germany, one of Germany's two main plants. company assembly. These innovations reduce employee risks and enable new knowledge and skills to be implemented. Edge computing is improving the employee experience by powering wearable and wearable augmented reality devices that accelerate job safety training, provide complex assembly instructions, and display equipment status such as temperature and vibration to aid maintenance
Revolutionizing patient outcomes in healthcare
The potential of Intel's Edge Computing technology to change the world and improve the quality of life will be demonstrated in the healthcare sector. Healthcare has undergone a digital transformation brought on by the COVID-19 pandemic by exposing the lack of efficiency, accuracy, and speed, and by challenging healthcare providers to find a new way to view and treat their patients. Telematic care helped solve this problem by keeping patients connected to their healthcare managers and it is here to stay.
Edge computing will enable the healthcare industry to unlock even more benefits from telematics care with more secure and remote remote environments for patients and providers. It will provide greater and more reliable access for rural, underserved communities and patients with limited mobility. It will deliver better quality of care and clinical efficiency by enabling frequent patient monitoring and data collection, integration with electronic medical records, and AI-powered patient data analysis. Image-based diagnostics are already used to speed up the detection of health problems such as speeding up CT images 188 times without adding accelerators.
This technology enables robots to function more autonomously supporting healthcare workers, improving patient care, and providing operational efficiencies and risk reduction. A prototype autonomous robot from Akara, it uses motion sensors and ultraviolet light to disinfect contaminated surfaces and creates safer environments for employees by reducing downtime. It is already helping to provide more accessible healthcare with better patient outcomes, but as artificial intelligence and robotic technology become more sophisticated and the use of wearable and other connected medical devices grows, the ability to use Real-time data will substantially improve the quality of life.
Boosting the Telecom Network and Operational Efficiency with Edge Computing
As the telecommunications industry prepares for 5G, it is important to consider the critical role that edge computing will play in helping them deliver services. The volume and complexity of 5G services will increase, and bringing computing closer to data is the only way to achieve the ultra-low latency required by 5G use cases. The commercialization of 5G, the rise of Artificial Intelligence and the growth of edge computing will create a multiplier effect that makes each one more impactful than it would be on its own.
Machine learning can help telecom operators increase network and operational efficiencies to meet rising service level expectations while reducing costs. With AI-based engines and analytics, communications operators will have the ability to intelligently manage 5G networks to achieve key network KPIs, network automation, energy savings, and operational flexibility to serve a wide variety of 5G use cases.
Rakunten Mobile developed the world's first container-based, fully cloud-native network, dramatically reducing its reliance on dedicated hardware and legacy infrastructure. They are also using edge computing data centers to provide fast response times for rich media content and applications, enabling a mobile network to support immersive and multisensory experiences for customers.
The future with Intel edge computing
5G and cutting-edge technologies are inextricably linked. The rise of 5G is critical to the future of edge computing because the promise of a world of new 5G-enabled use cases that makes investing in a next-generation network a smart financial decision.
Its ultra-reliable low-latency capabilities make the shortest connection between device and edge even more efficient. With this, companies will be able to obtain massive amounts of data. But this future is impossible without collaboration. Artificial intelligence expert Inma Martínez urges CIOs to remember that implementing edge computing and extracting its benefits is only possible when you have strong alliances and partnerships with all members of your ecosystem. It's the key to maximizing the benefits of connected devices. Each object has the ability to obtain information that can be extracted and used in real time.
This is expected to open up opportunities in sectors such as healthcare. An example of this are the w that will be able to track the patient's vital signs throughout the day and transmit data for easy and continuous assessment and to inform treatment. This will help patients with chronic conditions, such as cardiovascular disease, diabetes, and asthma, better monitor their health and even help prevent emergencies. Fully automated image-based diagnosis without human error will also be made possible.
With this unprecedented amount of information, Intel edge computing can change the way we communicate, move, work, shop, and live. Across all industries, companies will be able to better predict events, track performance, better understand customers, and create innovative products and services. All areas of life and business can be transformed.
CIOs will need to embrace collaboration and harness ecosystems that allow them to capitalize on all their opportunities. Siled approaches will fail. Fragmented strategies will hamper their ability to extract value from the edge and leave them behind as their industry and society evolve around them.
