Edge convergence brings diverse workloads across artificial intelligence (AI), media, and network together onto a common infrastructure delivering optimizations, efficiency, and lower cost of ownership. From prevalidated reference architectures to deployment-ready offerings, Intel and its vast ecosystem of partners make it easy to deliver converged innovations at the edge.
Do More with Your Data and Do It Faster
Digital transformation among enterprises and entities of all types and sizes has enabled revolutionary data-driven solutions to become common practice. Putting this data to work, and getting the greatest value from it, means moving it and processing it at faster and faster rates and doing so close to or at the point where the data is generated—at the edge.
New technologies that are propelling this shift in computing paradigms—including AI—are enabling us to analyze and act upon data from Internet of Things (IoT) in near-real time. In addition, the advent of 5G is extending network transformation and cloudification from the network core to the edge.
With the explosion of the amount of data at the edge, it is critical that we not only focus on key workloads but also optimize those technologies that enable convergence of these workloads. For businesses to derive actionable insights that can positively drive business value and outcomes, solution developers and partners need scalability, choice, and use-case-specific capabilities for deploying at the edge.
Converged edge solutions address this need by bringing diverse workloads—such as AI, network, and media—together onto a common infrastructure to deliver IT, OT, and CT insights to lead to innovations and better business outcomes at the edge.
From roadway cameras sensing when an accident has happened to tailoring medical treatments for patients through data analytics, the possibilities for what edge computing can do are expanding every day. Sectors of industry including retail and smart cities need to deploy converged edge solutions faster and with reduced complexity. Intel's Converged Edge Insights software is helping businesses and solution developers get there faster with a package of tools and resources that can speed up your development time.
Benefits of Converged Edge Solutions
Converging edge workloads offers a host of benefits and possibilities. Converged edge solutions bring IT, OT, and CT workloads together to simplify device and workload management and enable new cloud-native capabilities. With the power of 5G networking, edge convergence is set to drive a new phase of digital transformation and enable businesses to enjoy:
Develop solutions utilizing AI inferencing and 5G network capabilities at the edge, optimized on a common infrastructure, to help maximize your use of resources and bring down your TCO.
Faster Time to Market
With prevalidated software and reference architectures, Intel can abstract the complexity of developing for converged edge, allowing you to start rapid prototyping sooner and reducing your time to market.
Seamless Edge-to-Cloud Workflow
Intel is making it simpler for developers to benefit from edge-to-cloud workflow integration enabled by the Intel® Distribution of OpenVINO™ toolkit as well as the cloud-like agility offered by OpenNESS for developing and deploying applications and network functions. This is allowing cloud developers to extend their applications seamlessly to the edge.
Intel's Converged Edge Insights
With robust software packages and tools, Intel is accelerating the development of edge computing solutions and lowering the barriers to creating reliable, scalable applications. Intel's Converged Edge Insights, available on the Intel® Edge Software Hub, gives you quick access to preintegrated software packages and reference implementations designed to accelerate the development of converged edge applications with AI and networking capabilities, including 5G.
Intel's Converged Edge Insights is powered by the Intel® Distribution of OpenVINO™ toolkit and OpenNESS, an edge computing software toolkit. OpenVINO™ provides a tool suite for high-performance deep learning targeted at fast, real-world results deployed into production across Intel® architecture for a simplified and streamlined inferencing development workflow. OpenNESS enables highly optimized and performant edge platforms to onboard and manage applications and network functions with cloud-like agility across any type of network.
Intel® Distribution of OpenVINO™ toolkit
With a write once, deploy anywhere approach, the OpenVINO™ toolkit enables deep learning inference from edge to cloud. It accelerates AI workloads and supports heterogeneous execution across Intel® architecture.
Open Network Edge Services Software (OpenNESS)
OpenNESS is an edge computing software toolkit bringing various optimizations for networking at the edge in the form of modular building blocks built on a microservices-based, cloud-native architecture resulting in performant edge platforms. OpenNESS provides a software foundation at the edge to onboard and manage applications and network functions by abstracting network complexity and accelerates developer innovation.
Traffic Management Reference Implementation
There is also a reference implementation provided that leverages the Converged Edge Insights package. There is an urgent need to address the immense data pressures brought on urban transportation infrastructures by emerging technologies such as connected vehicles, 5G, and IoT. As cities and municipalities look to improve quality of life through new technologies, modernizing transportation systems and road infrastructure becomes a vital part of enhancing citizen experiences and addressing traffic congestion, environmental issues, and technical challenges.
The Wireless Network-Ready Intelligent Traffic Management reference implementation is enabling a new generation of smart city solutions. Its proven design consolidates visual intelligence from a distributed network of cameras over a 5G radio access network (RAN). It can detect and identify motorists, vehicles, bicyclists, and other subjects on a city street. Using their location and trajectories, it can optimize traffic flow and detect problems such as collisions.
More Reference Implementations to Come
We are currently working to develop additional reference implementations that will help business, governments, and other organizations bring innovation to the edge. Check back often to stay ahead of the curve.
Intel® Hardware Portfolio for the Edge
Converged edge solutions require a variety of compute, memory, and storage solutions to support and consolidate diverse workloads across a variety of environments, form factors, and use cases. Whether it’s deep learning–driven predictive analytics or smart cameras operating on a 5G network, the Intel® Edge Software Hub’s catalog of recommended devices and development kits offers a selection of devices that are prevalidated and designed for a variety of environments, form factors, and workloads.
A Proven Blueprint for Converged Edge
Intel can help you design for converged use cases with Converged Edge Reference Architecture (CERA). This blueprint provides a validated reference architecture to merge network workloads with inference, analytics, media, or any IoT applications onto a common infrastructure, providing a faster development path for solutions.
Converged Edge Use Cases
From industrial machines to medicine and smart city applications, converging edge workloads can make enterprises of all types smarter and more efficient. Example use cases include:
Public safety solutions can help make cities safer and more convenient by analyzing real-time data from a distributed network of sensors and video cameras. By converging these workloads at the edge and integrating 5G networking and deep learning algorithms, cities can use data video analytics to automatically detect events, such as automobile collisions, and respond to them faster. This data can also lead to traffic flow and management insights that increase the efficiency of roadways and city services.
Developing machine vision solutions capable of automating quality control and assurance can greatly increase manufacturing efficiency and the quality of end products. It can also reveal new efficiencies and enable new revenue streams. Edge convergence can take the disparate elements of a manufacturing process—cameras, industrial controllers, networking—and bring them onto a common infrastructure.
Precision medicine is the tailoring of interventions to specific individuals based on the unique characteristics in their DNA. Edge convergence with Intel® technology can help speed results for predictive models used in genomics studies.
Converged Edge Solutions from Our Partners
QNAP Smart Retail
Intel’s partner QNAP has developed an AI-driven branch networking solution for retail stores that enables smart checkout and personalized shopping experiences.
Foxconn Smart Access Control
Foxconn Technology Group is developing high-performance multiaccess edge computing (MEC) solutions that offer new approaches for industrial edge computing and private wireless applications.
We are excited to partner with Intel in our journey to provide superior customer value through innovation in the 5G edge network. Our collaboration with Intel for OpenNESS as well as other Intel® technologies such as OpenVINO™ and FlexRAN has empowered Wipro with a cloud-native edge platform that can provide high scalability and availability, as well as support several application workloads on a common, optimized infrastructure."