Edge computing capabilities create a wide range of innovative use cases for organizations across all industries and particularly in areas such as manufacturing, warehousing and logistics, to drive modernization and support the shift to Industry 4.0.
Edge is a catalyst in creating innovative new use cases incorporating artificial intelligence (AI), augmented and virtual reality (AR/VR), autonomous drones and industrial internet of things (IoT) sensors, as well as enhancements for traditional apps such as enterprise resource planning and data analytics.
In Europe, the largest share of enterprise edge spending in 2021 is being driven by use cases around IoT, AI, robotics, drones, and AR/VR, according to research by IDC.1 It expects spending on edge computing in Europe to reach $24 billion (U.S.) this year.
This article explores four of the most innovative use cases for edge computing and shows how a platform-based deployment model gives organizations maximum flexibility to adapt these technologies and capabilities to meet the needs of their own applications and environments.
Edge Computing: Winning with Platform Approaches
This paper explains how edge computing securres the digitalization of companies, which key challenges companies are facing when introducing edge computing, and how to successfully use edge computing.
Download NowArtificial Intelligence
AI is able to cope with a wide array of complex situations by finding optimal decisions and adapting to changes quickly, incorporating pattern recognition or simulating the outcome of multiple decision alternatives, among other capabilities. Manufacturing is one of the industries in which many organizations in Europe are effectively using AI to reduce costs, improve safety and increase productivity.
Typical AI use cases are automated steering of transport robots to avoid obstacles; visual quality control in production or intelligent resource planning systems; and expert support for complex maintenance processes. In maintenance use cases, AI is integrated with AR glasses to visually aid maintenance personnel through work steps. At the same time, AI checks whether all work steps have been carried out properly.
Campus Positioning
Localization of objects is key to many advances in productivity, safety, efficiency and cost savings for factories, warehouses and other environments. Seamless indoor-outdoor positioning is a prerequisite for holistic autonomous intralogistics, and low-latency edge positioning is necessary for many industrial use cases, such as autonomous drones for warehouse inventories or video from 5G-enabled drones that monitor potential security issues.
With an integrated end-to-end platform such as EdgAIR from T-Systems, organizations can leverage various localization technologies in combination with mobile network positioning for coordination and synchronization of different positioning techniques. Standard APIs can be used for positioning data for apps using an open interface. Customer benefits include improved performance and reliability, as well as reduced operational and safety risks, particularly with the use of positioning services in transport and logistics in manufacturing and industrial sectors.
AR/VR
IoT sensors are precipitating a huge increase in the volume of actual, historical and contextual data. Applications infused with AR/VR capabilities provide organizations with analytics and insights that enable flexibility and fast decision-making and make interactions between humans and machines more seamless and productive. EdgAIR enables organizations to map AR to device-specific functions and connect to 5G networks to facilitate real-time processing of large amounts of data with low latency.
With EdgAIR, a standardized connection between IoT devices and agents and an AR-capable device like smart glasses allows visualization of computed results with low latency. A holographic AR cockpit with real-time data of all production machines reduces complexity for workers and enables on-site decision-making and planning. Fast configuration of data visualization for all the different AR device dashboards enables efficient orchestration and management of massive amounts of data with a standardized assisted reality asset for quick integration. AR allows organizations to speed up productivity, enable hands-free operation, and leverage real-time data analytics and transformation of data between IoT and AR devices.
Automated Guided Vehicles
Automated guided vehicles have vast potential to lower overhead and cost, particularly in warehouses and Industry 4.0 factories. However, there are technical challenges that can be addressed only by an edge computing platform. Such challenges include frequently changing logistics processes and lack of reliable real-time indoor and outdoor connectivity. A platform-based edge solution like EdgAIR solves these problems in a number of ways, including a time-sensitive network, very low latency, 5G integration and edge analytics.
EdgAIR enables autonomous navigation, safety and obstacle avoidance, indoor mapping and path planning. In addition, the solution can be adapted to different sensor and robot setups. Customer benefits include flexible and optimized linking of production processes and facilities; seamless use of autonomous vehicles for indoor material transport; improved performance and reliability; reduced operational risks; and lower costs.
Taking the Next Step
While some of these use cases sound futuristic, in reality, they are all available now and being used by customers of EdgAIR across the globe. EdgAIR provides customers with a holistic, end-to-end platform and ecosystem that enables them to maximize the value of edge computing and the cloud-edge continuum.
Benefits of EdgAIR include a vendor-agnostic ecosystem for all aspects of edge computing, with connectivity to all applicable network infrastructures, including Deutsche Telekom’s 5G campus network; edge analytics; high performance and ultra-low latency; and seamless integration with public clouds.
EdgAIR provides additional benefits powered by 3rd Gen Intel® Xeon® Scalable processors, which are optimized for cloud, AI, enterprise, performance, network, security and IoT workloads with a wide range of frequency, feature and power levels. With built-in AI inference acceleration and network-optimized SKUs, 3rd Gen Intel Xeon Scalable processors provide an agile and robust edge foundation for trusted performance that scales.
To learn more about how Intel-powered EdgAIR solutions can enhance use cases and facilitate innovation at your organization, please visit T-Systems.
1 “IDC Forecasts Double-Digit Growth for Enterprise Edge Spending in Europe, Driven by Demand to Reduce Time to Value and Enhance Customer Experience,” IDC, July 14, 2021
