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      Preparing for the Business Future of Edge Computing

      Written by :
      Team Uvation
      | 7 minute read
      |September 16, 2023 |
      Category : Edge Computing
      Preparing for the Business Future of Edge Computing

      Enterprise digital infrastructure is shifting to the edge—and a new era of computing that will have a
      massive impact across industries is emerging as a result. Now, “edge computing has become a top
      priority for C-suite executives and is critical to the success of strategic business objectives,” as IDC
      describes in their 2022 report. These leaders are looking to deploy solutions that include emerging
      technologies like Internet of Things (IoT), AI, and 5G networks alongside edge technologies as well.


      But even with a conceptual understanding of edge computing, it’s difficult to envision how it will shape
      the future and drive real value for manufacturers, retailers, hospitals, and other organizations. In this
      article, we explore the buying intentions of business leaders; we help you consider strategies and
      emerging use cases for technology and workloads at the edge in your own organization as well.


      Edge Computing in the Context of Modern Business


      Edge computing is the processing of data at or near the source of data collection—instead of in
      centralized data centers far away. This addresses the limitations of centralized data centers, which are
      struggling to keep up with the demands of today's data-driven technologies at multiple “edge” locations.


      Modern edge networks are next-generation wireless networks at these locations, which offer ultra-low
      latency and high bandwidth when connecting nearby devices. Edge computing supports optimized on-
      site processing and performance for devices and processes beyond what’s possible using centralized
      data centers alone. Elements of edge infrastructure may include:


      •  Internet of Things (IoT), which works with edge computing to solve the problem of processing
        massive amounts of data. Devices at the edge can communicate with IoT sensors and devices,
        thus eliminating distance constraints. This enables real-time analysis for things like predictive
        maintenance or traffic management.


      •  Fog nodes, which are intermediary devices that sit between edge devices and the cloud. They
        can be fixed edge devices or mobile edge devices, offering local compute and storage resources
        as well as bandwidth management.


      •  Cloudlets, which are edge computing platforms that provide compute, storage, and connectivity
        for edge devices and local users. They are often deployed in edge locations such as stores,
        branch offices, or event venues where user may need to access enterprise applications or data.


      •  Edge AI, which refers to AI algorithms that are executed on edge devices, as opposed to in the
        cloud. Edge AI offers several advantages over cloud-based AI, including faster response times,
        increased privacy and security, and reduced costs.


      As we will find, these setups support emerging applications like virtual reality (VR), augmented reality
      (AR), autonomous vehicles, and industrial IoT (IIoT), which put a lot of demand on IT infrastructure.


      Future Edge Infrastructure Has Applications Across Industries


      As a modern digital infrastructure and networking solution, edge computing is not just a collection of
      solutions but an evolving field with widespread business applications. Edge computing can be used to
      improve performance, optimize resources, and reduce latency in any industry. Consider these seven
      benefits and how they might apply in your own operations:


      1. 1. Reduced latency: Data doesn't have to travel as far to be processed and analyzed, resulting in
        faster response times. This is crucial for edge applications that require real-time data processing
        such as autonomous driving or industrial control.


      1. 2. Improved performance and efficiency: Edge solutions can perform tasks in real time, which
        improves performance and efficiency. edge computing can also be used for predictive
        equipment maintenance or to perform other tasks that require immediate action or response.


      1. 3. Optimized resources: edge devices can process data closer to the source, eliminating the need
        for expensive and complex networking infrastructure. edge computing can also help reduce
        bandwidth requirements by processing data before it's sent to the cloud.


      1. 4. Enhanced customer experiences: By processing data at the edge, businesses can improve
        customer experiences by delivering content and services faster and more securely. Edge
        computing can also be used


      1. 5. Increased security: Since edge devices are closer to the data source, they can be used to detect
        and prevent attacks. In addition, edge-based security solutions can be more efficient and less
        costly to implement and operate than traditional security methods.


      1. 6. Reduced costs: Edge computing solutions are often less expensive than traditional ones because
        they do not require as much infrastructure and can be deployed quickly. Edge computing is also
        scalable, meaning it is easier to add new edge devices without disrupting existing infrastructure.


      1. 7. Greater agility and responsiveness: Edge setups can process data faster and more efficiently,
        which enables businesses to be more agile as they scale their edge infrastructure. edge setups
        are also easier to deploy and manage than traditional, centralized enterprise solutions.


      Four Industries with Transformative Edge Models



      Basic edge computing models have been in place for some time. But advanced edge computing models
      are beginning to transform industries, with unyielding potential for more robust and sophisticated
      applications. Consider these four industries and use cases where edge computing is already making a
      substantial impact.




      Retailers are already using edge computing to provide a better shopping experience by reducing the
      amount of time it takes for in-store digital applications to perform. Edge computing can also improve
      customer experiences by providing them with real-time information about products or services.


      “To deliver on customer expectations for speed and flexibility, retailers need to bring the applications
      and the underlying processing and storage closer to where the data is being created," as MIT
      Technology Review describes. "To do this at scale requires edge computing… rather than risking issues
      with data transfer speed and bandwidth by uploading all that data directly to the cloud.”




      Healthcare provider spending on edge computing will reach $10.3 billion in 2025, with a five-year CAGR
      of 17%, Computerworld reports based on 2021 IDC findings. Edge solutions allow hospitals to be more
      responsive in their interactions, which leads to better treatment options and better patient care.


      Already, hospitals are using edge computing to speed up the time it takes to get test results back to
      physicians. Edge computing also provides doctors with real-time information about a patient’s health,
      giving them more opportunities to improve patient outcomes.




      Manufacturers use edge computing to improve the efficiency of their operations. For example,
      manufacturers can use edge computing to automate key factory and supply chain processes, support
      advanced robotics, and improve how machines communicate with one another—quickly onsite, rather
      than via a centralized network. “[Edge computing] will revolutionize manufacturing as adoption spreads
      across the globe,” as Forbes describes.




      Edge computing will support better consumer experiences on rail, buses, commercial airplanes, and
      other forms of transportation. Edge computing also can support smart infrastructure in cities and
      transportation hubs for greater transport efficiency, reduced delays and accidents, and predictive
      capabilities that prevent unit degradation and downtime.


      In the automotive industry, edge computing “will generate a tremendous amount of real-time data from
      self-driving vehicles, driver-monitoring systems, and surveillance cameras for artificial intelligence
      algorithms to harness,” as Forbes describes.


      Getting Started with Innovation at the Edge


      As recently as 2018, “around 10% of enterprise-generated data [was] created and processed outside a
      traditional centralized data center or cloud,” Garter reports. Edge computing is poised for massive
      growth in the coming years as businesses rush to deploy emerging edge technologies, such as fog nodes,
      cloudlets, advanced IoT, and edge AI. “By 2025, Gartner predicts this figure will reach 75%.”


      No matter your industry, edge computing will be essential in some capacity. C-suite executives who
      understand both the challenges and benefits will get the greatest value from this inevitable future. By
      planning today, you can reduce risks and take advantage of countless new opportunities at the edge.


      Partner with Uvation for Your Edge Computing Transformation


      The edge computing experts at Uvation can help you as you transform your business model to support
      more robust edge computing capabilities. Contact us directly to discuss your options today.


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