Center for Edge Computing and 5G
The edge exists wherever data is acted on to create immediate, essential value. It’s where trailblazers in every industry are leveraging edge computing and 5G to transform business models, operations, and user experiences.
Edge deployments can be complex with many silos. Learn how to consolidate and simplify deployments using Dell Technologies Edge solutions.
The benefits of smart manufacturing come not from making individual machines smarter, but from gaining continuous insights into, and control over every process, from the start of the supply chain to the end customer.
Telecommunications is evolving with the introduction of new technologies, such as 5G. And with it, the intelligent factory and the possibilities for tomorrow. Watch now.
The opportunity at the edge is clear. Learn how Dell Technologies is helping organizations seize it.
Dell’s five step plan and recommendations for undertaking successful artificial intelligence implementations.
Learn how the edge cloud enables the use of infrastructure in edge locations via an “as-a-service model.”
Learn how intelligent edge systems make instantaneous and autonomous decisions independent of the datacenter and private or public clouds.
Learn about the role of Dell Technologies’ solutions for designing and deploying digital twins for manufacturing and industry.
5G and edge technologies are expected to provide the bandwidth, low latency, and reliability that address the needs of connected cars.
According to the FWHA, there is a need for early-stage research to support emerging advances in artificial intelligence to help solve complex issues in highway transportation.
Increased speed and reduced latency are the top reasons that make the combination of 5G and edge computing a big hit today.
Integrating smart cities efforts across geographic boundaries helps democratize expertise and skillsets needed to get the most impactful results.
5G can help realize the ideal of a modular factory where machinery can be quickly reconfigured to optimize production.
Breaking down the barriers of smart cities development could be achieved through the use of open-source standards and frameworks.
Companies are trying to address supply chain challenges by leveraging cutting-edge technologies including robotics, edge computing, and artificial intelligence.
5G networks act as an enabler, driving efficiency through automation and use of technologies reliant on high-quality connectivity such as edge computing and IoT.
Edge computing is paving the way to more effective automation and monitoring of industrial assets, systems, processes, and environments are increasingly important across manufacturing industries, including transportation, electronics, mining, and textiles.
Citizens and governments will be connected in ways that we’ve never seen before. IoT will deliver huge opportunities and benefits to smart cities, but this level of interconnectivity will also bring its own set of challenges.
The numbers don’t lie. Businesses need data and the edge. Here’s how to get it right.
While waiting for broader availability of 5G devices, there are significant numbers of companies operating private networks based on technologies such as TETRA, P25, Digital Mobile Radio, GSM-R, and Wi-Fi.
Lower latency services such as IoT, 5G, and video streaming are behind much of the edge data center market’s growth.
With the proliferation of high-definition cameras, computer vision, and AI applications, retail stores can now get real-time insights while customers shop.
A new research collaboration will focus on Superlearners, a foundational machine learning technology that enables autonomy for all building applications.
While $1.1 trillion annually is being invested in digital factory initiatives worldwide, most companies, 64%, are still at an early stage of their digital transformation.
The data pipelines and plumbing underneath efforts to support artificial intelligence and machine learning capabilities at the edge are critical.
A new Cornell University study has tried to embed memories into a self-driving vehicle to better learn routes and overcome weather challenges.
Edge is going through a revolution or evolution, enabled by more connectivity, even in really low-end devices, that makes much more data available.
Digital cities seeing the most remarkable success use technology to achieve clear, measurable goals. They also prioritize citizen and business engagement from the start.
An urgent call to action that optimizes patient experiences and how edge computing can help.
Deploying AI applications at the edge with 5G has the potential to generate new revenue sources in manufacturing, putting the industry at the forefront of innovation.
Researchers have retrofitted an AI tool originally developed during COVID that used edge elements and deep-learning object detection to calculate pedestrian and traffic densities so that it now assists urban planners and government officials on crisis management response and urban congestion.
With SONiC, organizations can extend their data center fabric out to edge locations, using a single unified network operating system and the same familiar data center networking tools that they are accustomed to.
Managing data gravity through proper planning prevents poor performance.
Organizations can derive extraordinary value by collecting new data smartly and efficiently, at the right place at the right price, and analyzing that data to extract business gold.
Vehicles today are edge computers on wheels, running on software that is constantly being refreshed.
The leading smart cities use emerging technologies and innovation to make their cities more livable and offer new services and economic opportunities.
Smart manufacturing based on edge solutions delivers real-time insights that can improve operations and provide global visibility into progress towards desired business outcomes.
Organizations are using 5G and edge technologies to improve employee productivity, augment existing products and services by making them more connected and intelligent, and automate business processes.
By 2026, the number of sensors deployed in smart buildings will exceed one billion. As a result, more AI deployment will follow to provide insights into the building data they collect.
The edge is where about half of new retail applications and infrastructure will be deployed and where much of all new data will be processed.
5G and software-defined networking together promise to make the real-time digital factory a working reality.
Underwater IoT sensors can provide data-driven insights to plan ahead and notice subtle characteristics in our environment that—in the past—we may have missed.
5G and edge initiatives are typically part of broader enterprise-wide digital transformation efforts.
The smart lighting project is one of the most extensive smart technology infrastructures in the country relying on edge technology and focusing on the use of greener energy, carbon footprint reduction, and more.
Edge computing and 5G-based application development have become the leading use cases for containers and Kubernetes.
Edge computing and 5G unleash the potential to improve the lives of factory workers, solve growing labor shortages, and contribute to a more sustainable planet.
Leaders who actively bring citizens into the smart city conversation and consider the long-term impacts of solutions like AI have a better chance of success.
Manufacturers can use edge data for the full product lifecycle to gain accurate and timely insights into how their products are used by customers.
Governments like Shanghai and the others in the top five smart cities spots want to use data to democratize services and engagement.
Edge computing, often enabled by 5G, represents the next force shaping enterprise computing in the year ahead.
An increased focus on automation and environmental data is driving demand for smart sensors as companies and cities focus on environmental impacts in operations.
A continued surge in 5G and edge computing over the coming year is predicted by multiple studies and analyst reports.
The city also plans future smart cities initiatives such as creating a cross-sector board of governance and greater sharing of data resources.
5G supports real-time data at points of origin, which can be used to uncover supply chain problems across inventory at speed, predicting future disruptions.
The automated lights can lessen the impact of C02 emissions resulting from idling traffic at intersections. And because they use edge computer control located right on the junction control box, they offer scalability.
Analysts at some leading consulting firms are already planning out the ways 5G will make a difference, and a key area is government – with functions as wide-ranging as port inspections to frontline troop deployments.
The autonomous driving trial conducted at BMW’s testing facilities in Munich has far reaching implications for fleet management tools.
Unlike other industries where the opportunity only seems promising, factories are primed to be completely transformed by 5G and edge now.
Digital twins offer companies the opportunity to test out new 5G environments and conduct maintenance on existing rollouts without significant disruption.
Smart systems powered by 5G and edge technologies have the potential to improve safety on the roads and in industrial facilities. Jillian Kaplan of Dell Technologies has a strong personal interest in developing such technology for good.
In the long term, infrastructure edge demand will be driven by edge-native use cases that can only function when edge computing capabilities are available.
IoT technology will have a stronger foundation thanks to the infrastructure bill’s focus on bridging the divide between areas with internet access and those who struggle to find quality internet.
Edge devices, with their small footprints and low power, are often too constrained to support AI. What’s needed are new approaches to address these issues.
Investment in IoT is set to overtake cloud computing, next-generation security, big data analytics, and other digital transformation technologies in the near future.
As enterprises evolve to 5G edge-intensive architectures to deliver and process information, security basics get elevated in importance.
Most enterprises do not know what to do with IoT technology. And if they do, there is concern over who will be leading these initiatives.
With edge computing, workloads, storage, and networking infrastructures are moved closer to the sensors, actuators, and other IoT devices that generate and use that data.
Edge computing requires elements that can fit into the limited space available, withstand harsh conditions, and run sophisticated analysis routines.
Edge computing and 5G in the enterprise will transformation what we know as data centers. They are likely to evolve to be smaller and more geographically dispersed.
A controlled 5G trial took place in central London using a compact radio designed to use less energy without sacrificing connectivity or performance.
Edge deployment supports real-time decision-making and enables digital transformation, which is a vital part of next generation business.
Manufacturing, healthcare, transportation, environmental monitoring, and gaming are poised for growth using 5G and edge.
The new solutions and updates consolidate and streamline data management and operations as deployments scale, overcome latency constraints, and secure the operating environment at the edge.
Within the next two years, more than half of new enterprise infrastructure deployed will be at the edge rather than corporate data centers.
The highly interconnected smart city that is evolving is built on having real-time data openly available and capable of being shared across agencies.
The IoT-based forest management system offers ultra-early fire detection based on AI, as well as tree health and growth monitoring.
The changes edge computing brings can be profound, and businesses will want to be in the best possible position to change as well.
Employee home devices, which are often connected to corporate networks, were a source of IoT vulnerabilities during the pandemic.
By integrating the 5G and IoT network, it will be feasible for the manufacturers to operate with comprehensive flexibility and move ahead to a dynamic ecosystem of suppliers and consumers.
5G and edge computing used together are already delivering business capabilities in use cases across a broad range of industries.
The key to deployment of managed edge services is the rollout of 5G services, which enable faster, more consistent services.
A discussion on how the edge is all about generating new value from data and accessing more of that data by getting closer to where it’s created.
The two leading areas of edge investment are in infrastructure operations and digital services. 5G networks underpin these promising developments.
The demand for private mobile networks based on LTE or 5G technologies is driven by the exploding edge computing requirements of modern businesses.
A discussion about the need for telcos to modernize their infrastructure and the role edge can play in bringing innovative applications and services to market.
The 5G-enabled factory will have the capacity to maintain connections for far more sensors than either wired or previous wireless facilities.
Now that companies have embraced edge, updated disaster recovery plans are needed to offer assurance that a company can survive a disruption.
For manufacturers, an advanced factory platform can unify information technology (IT) and operational technology (OT) to minimize costly disruptions.
Bill Pfeifer, Edge Message Director at Dell Technologies, provides an overview of edge technology, its use cases, and its benefits.
Computing architectures need to mix and match data, workloads, and their environments along the center-to-edge spectrum.
In many situations, using cloud computing and edge computing at the same time can lead to the best overall outcome from a performance perspective.
Intelligent edge computing is the application of edge computing architectures to workloads involving data analysis, machine learning, or AI.
5G networks deliver the versatility and flexibility to support millions of IoT devices and sensors in a way that 4G or LTE couldn’t.
Moving to an edge architecture requires managing costs, orchestration, and security challenges.
Earlier entrants are getting a head start on reaping the benefits of edge computing and they are providing roadmaps and lessons that will benefit everyone across the board.
The most significant implication of using mobile edge computing seems to be a continued focus on efficient data processing and gaining timely insights.
IoT infrastructure is one possible way to build an edge computing environment.
As things return to normal, IoT strategies could give physical stores a boost, allowing retailers to enhance the experience for their customers.
CIOs are realizing that the edge is the key to unleashing innovative opportunities.
Edge computing changes are enabling decision-making where data is generated, and are powering applications that are reliable, private, and faster than ever.
Learn why the edge-to-cloud compute continuum is a foundational component of digital transformation into a data-driven enterprise.
The rise of open source at the edge is happening by necessity, as no two edge networks and device clusters are alike, requiring high degrees of customization.
Industrial IoT paves the way for industrial companies to shift from selling products to delivering services and solutions.
IoT, machine learning, artificial intelligence, 5G, augmented reality, and virtual reality all benefit from increased edge compute power.
The convergence of computing environments, from edge to the central server, is forming the foundation of the emerging real-time enterprise.
The edge is ripe for cross-pollination where lessons learned and solutions developed in one industry may be used for another application in a different industry.
If edge computing capabilities can be woven into the very fabric of our cities, this might come to revolutionize the way we interact with them.
Organizations face significant challenges deploying IoT infrastructures and discovering insights from the vast amounts of device-generated data.
An enterprise-class infrastructure can enhance the effectiveness of digital twin initiatives and enable innovative applications.
Many industries are looking to 5G to help move data at lightning speeds from edge devices and networks to more centralized decision-making systems.
Welcome to the digital future, where every organization needs to be a digital organization powered by data, running in a multi-cloud world. The digital future demands a data-first perspective.
One of a smart city control center’s most useful features is its ability to serve as an Early Warning System (EWS) and quickly act on its own EWS recommendations.
Providers realize the competitive advantage of offering 5G for edge applications and will be bidding on available spectrum to put a suitable infrastructure in place.
Artificial intelligence and machine learning, once mainly seen on the supercomputers of the world, are now prime candidates for deployment at the edge.
The most significant cybersecurity focus for 2021 for 5G and edge will be blending human expertise with newer solutions such as AI-driven security.
Industry Use Cases
Every industry is undergoing digital transformation. Edge plays a critical role in how organizations leverage new data sources to drive specific and differentiated business outcomes.
Learn how communications service providers can quickly and easily build their virtual network infrastructure for 5G using Dell Technologies Bare Metal Orchestrator.
Learn about the three key steps for Telcos to realize the 5G opportunity.
Learn about the benefits of 5G for your business.
5G and edge go hand-in-hand because of 5G’s lower latency and the higher bandwidth. Together they will enable a new class of applications across industries.
RAN is critical to network performance. But RAN innovation is limited due to closed proprietary technologies. Open RAN gives you the flexibility to avoid vendor lock-in and accelerate innovation.
Modernize with confidence. Dell Technologies edge solutions for manufacturing enable innovative applications.
As a critical-enabler of high value technologies like AR/VR and 5G, edge computing is seeing substantial investment across the enterprise landscape.
A new Ford service will let businesses monitor their connected fleets while helping to manage driver behavior, performance, and compliance goals.
Learn how smart factories, powered by data-driven insights and automation at the edge, are revolutionizing manufacturing.
Simplify the manufacturing edge to generate insights where you need them.
Meeting the evolving needs of society demands continuous innovation. Learn how cutting edge solutions emerging from data analytics are advancing manufacturing and giving rise to Industry 4.0.
A discussion about how the edge is where data is acted on near the point of creation to drive immediate essential value.
An overview of how the edge can be used to generate insights and provide intrinsic security for your projects.
Edge lets companies act on data near its point of creation to generate immediate, essential value. When combined with 5G, edge computing will drive a digital revolution.
Edge compute is growing significantly. What percent of infrastructure is deployed at the edge?
ROI for edge computing needs a deep drill-down and exacting metrics to determine how and where edge deployments deliver value.
Every situation is unique. What is clear, however, is that a balance between cloud and edge computing will likely drive tomorrow’s IoT architecture.
As massive amounts of data are created, the cloud will extend to the edge. It won’t be cloud versus edge; it will be cloud with edge.
Disruptions of supply chains are hopefully temporary. Yet, they point to data and analytics gaps hindering the ability to connect products with consumers.
Heath Muchmore and Manny Yusuf, Chief Architect and Cloud Architect, respectively, within the Federal Office of the CTO for Dell Technologies, continue their discussion addressing how to overcome the challenges of bringing Edge computing to Federal Mission environments.
Heath Muchmore and Manny Yusuf, Chief Architect and Cloud Architect, respectively, within the Federal Office of the CTO for Dell Technologies, continue their discussion addressing how to overcome the challenges of bringing Edge computing to Federal Mission environments.
Your data is there, hiding at the edge.
What is Edge Computing?
Edge computing and 5G are two of the emerging technologies that will fuel the future by transforming the physical world into digital. Adoption is expanding, and organizations harnessing these technologies will pave the way for some of the most innovative industries. Digital transformation depends on a data-first approach, with rapid ingestion of data and raw compute power driving the analytics necessary to turn vast quantities of data into actionable insights.
IDC predicts that the collective sum of the world’s data is on track to grow from 33 zettabytes in 2018 to 175ZB by 2025, for a compounded annual growth of 61 percent. According to Gartner, while today only about 10 percent of enterprise-generated data is created and processed outside a traditional data center cloud, by 2022 that’s expected to increase to 75 percent; and the location of the data being generated is the edge.2
IDC defines the datasphere as having three main locations. First is the core, which includes traditional and cloud data centers, second is the edge, which includes things like cell towers and branch offices, and third is endpoints, which include PCs, smartphones, networked cars, wearables and edge and IoT devices. Determining how to aggregate, analyze and process the data these devices generate and collect is one of the key challenges for today’s organizations as they integrate edge solutions. For use cases that require immediate insights, the data is most valuable the instant it’s ingested, and the longer analysis takes, the less value a business can glean from it or rely on it.
Edge technology is undergoing rapid and expansive changes to accommodate these shifting needs, as more and more organizations are adopting what is now know as edge computing. For most organizations, it will be invaluable to their future growth.
At its core, edge computing is the practice of deploying distributed devices that are capable of performing data processing, computation, and decision making across a network. Businesses place these computational devices as close to the “edge” – the location within the network where data is generated by IoT devices – as possible, to minimize the space and time between ingestion and the analysis of data.
These edge and IoT devices come in a variety of forms, depending on the application and the computational power necessary. They can be offshore wind turbines, industrial controllers, a smart light bulb, security cameras, gas turbines, autonomous vehicles, cameras phones, point-of-sale systems, and much more. Sometimes, they’re as inconspicuous as a single industrial sensor on an oil rig or in a factory. They can also be small “data centers” of servers located in strategic areas around a business’ network or embedded within distributed facilities (such as warehouses or distribution centers) rather than centralized either on-premises at company headquarters or in a cloud computing data center.
Regardless of the size, edge devices often take on the responsibility of processing real-time streaming data themselves, rather than relying on a centralized cloud computing service. They perform analytics, make decisions, and even run artificial intelligence or machine learning models on the data, without additional support. An autonomous car is an excellent example of the types of considerations required for a good edge architecture – many focus on video-based object detection and recognition, but consider the simple use case of smart air bag, and the requirements this may impose for analysis and response. The many variables of passenger height/weight/position in car (especially proximity to the dash), and the sensors which need to work in concert to ensure accuracy and determine whether or not to deploy on impact (and based on severity of impact, location of impact, etc.). There is no time to take the data from an impact to a car to a data center or a cloud, and back again, in time to instruct the air bag to deploy – this analysis and response must happen at the edge – in milliseconds.
An autonomous vehicle relies heavily on sensors that monitor the vehicle’s current state and observe its surroundings. These sensors are connected, through the vehicle’s operating system, to essential mechanical functions like steering and braking. In order to respond rapidly to hazards, shifting lanes, other vehicles, pedestrians, cyclists, and stop signs, the vehicle needs to ingest data from sensors, analyze that against the current speed and other state data, make a decision of its next move, and apply that decision in a fraction of a second.
The increasing power of edge devices and infrastructure is one of the primary reasons autonomous vehicles exist today. If the vehicle needed to send sensor data back to a cloud computing data center for analysis, it may have crashed by the time a decision was transferred back. By placing computational power in the vehicle itself, and thus the fleet’s physical edge, an entirely new industry is born.
This is where the value of 5G networks becomes apparent. The telecom edge, also known as Multi-access Edge Computing (MEC), allows for distributed computing that enables low-latency and high-bandwidth uses cases that otherwise wouldn’t be feasible on centralized cloud architecture3. Autonomous vehicles are one of the ideal use cases for MEC. Beyond transportation use cases, industries in every sector are adopting edge computing and 5G.
Consumers see edge computing in action in so many ways today. A few of the most recognizable are in voice-recognition hardware, smart thermostats, internet-connected TVs, and even the smartphone in their pockets. At the same time, industrial organizations are pushing edge infrastructure and edge analytics to empower their digital innovation and create smart factories using truly intelligent machines and automated processes. By applying computational power, artificial intelligence, machine learning, and advanced analytics at the machine’s edge, businesses can tap into yet-undiscovered value from machine data.
Benefits of edge computing
- Dramatically reduced latency. Without the edge, data transfer between an IoT device and a cloud computing infrastructure adds latency and reduces value; and isn’t fast enough for applications that require instant action, such as autonomous vehicles, customer experiences or industrial applications in a closed-loop system where insights from machine data directly affect the following actions.
- Value gained instantly from data. Edge computing helps to prioritize data as it reduces the signal to noise ratio. Often data is most valuable at precisely the second it is created, and then its value diminishes over time. Through reduced latency – the time gap between the acquisition and analysis of data – organizations can respond to, or learn from, the data and save lives, perform robotic surgeries, create experiences, deliver outcomes and drive disruptive innovation. Edge Computing can reduce the cycle to just a few milliseconds.
- Streamlined analysis process. Traditional IoT & Cloud infrastructures transfer all data from dozens, hundreds, or thousands of devices to and from a centralized computing environment. But, if edge devices are capable of making critical decisions locally, they can choose when and how to push that data to the cloud – if it’s necessary at all.
- Bandwidth reduction. Because high volumes of bandwidth incur a heavy cost for businesses, any cut can make a meaningful impact on the bottom line. Edge computing presents an agile opportunity to keep data close to home whenever possible.
- No single point of failure. A centralized cloud computing environment, despite all its benefits, creates a single point of failure for making mission-critical decisions on IoT machine data. Edge computing spreads out the risk – an edge platform can still operate – ingesting data and making key decisions even if the central cloud experiences downtime.
- On-device encryption and security. By reducing the need for data in transfer (and through embedded or on-device data encryption itself), edge computing can provide security benefits to industrial applications requiring the tightest security measures. By minimizing reliance on a single cloud environment to store all company data, there is also less vulnerability.
- Operations maintained where data connectivity is difficult. Remote or challenging locations, such as offshore oil rigs or deep mining sites, often struggle to maintain strong network connectivity. Edge computing can allow these rough operations to function self-sufficiently using onboard decision-making capabilities.
- Onboard data streaming made easy. Instant analysis of streaming data plays an important role in the future of smart manufacturing and challenges around IT/OT convergence across industries. Edge computing can open the door to complex analysis on high-velocity streaming data.
Will edge computing overtake cloud computing?
The importance of a data-first strategy is to understand the importance of a multi-cloud environment. Every organization needs to be a digital organization – powered by data, running in a multi-cloud world. That means understanding the dynamics and significance of the edge, the core and the cloud.
Cloud computing immediately presents an opportunity for businesses to reduce up-front IT costs, scale as needed, and manage infrastructure more efficiently. Cloud computing providers have consistently improved both the performance of their product and its ease-of-use, which has resulted in enormous innovation and economic growth. Today, it’s possible for even the smallest of businesses to leverage the power of a supercomputer-strength data center.
Edge computing presents a paradigm shift away from computing architectures of the past, but there is no indication it will displace cloud computing environments. In fact, businesses are gaining the most value out of bridging their cloud and edge environments together and utilizing each to their strengths.
Cloud computing will continue to dominate in applications that require massive computational power or managing large quantities of data, such as deep learning training. That said, edge computing is more than powerful enough for even complex AI applications. An autonomous vehicle’s training may happen in the cloud, but its instantaneous decision-making and execution happens at the edge.
How is edge computing being used today?
By managing and analyzing the enormous volumes of data at the edge, the point of origin, and only transferring the most important results, edge computing has already delivered on the power of analytics, low latency, cost reductions and high flexibility capabilities to a variety of industries:
- Defense: Soldiers work in some of the most rugged environments imaginable, and require the ability to make split-second, informed and data-driven decisions, in real-time, using technologies that fit in a backpack or in the back seat of a Humvee. Edge computing, with approved military systems that include compute, storage, and networking capabilities, can assess critical situations, analyze communication spectrums being used on the battlefield, and enable real-time decisions that can save lives, divert critical maneuvers and protect nations.
- Energy: Across all energy use cases including utilities, natural resources, and oil and gas, edge computing is playing a critical role. From real-time workplace safety conditions in rugged environments like on oil rigs and in mines, to improving maintenance by remotely monitoring and tracking equipment conditions, to using smart meters to prevent theft and using smart grid technologies to reduce over consumption, the edge is delivering results. Edge devices eliminate latency and allow the most urgent decisions – such as shutting down operations due to a safety breach – to happen automatically, while also leveraging the raw power of the cloud to make wider analysis of efficiency and possible optimizations.
- Transportation: Aside from the enormous strides being made in autonomous vehicles, the transportation industry is embedding trains with edge platforms to help analyze the billions of data points per second that are already being collected by dozens of onboard sensors. Edge computing is being used to monitor the health of locomotive equipment in real time, and the industry is working toward autonomous operations applications, as well. For improved operational efficiencies, passenger recognition systems are being used to speed boarding for rail and air travel alike. We’re seeing edge computing use cases across land, sea and air.
- Healthcare:The healthcare industry is adopting edge solutions in so many ways. From hospitals, to ambulances, to pharmaceutical companies, and more, the industry has grown tremendously. From general biometric wearable medical devices, such as a wristwatch that would monitor motion and heart rate data to a similar wristwatch now monitoring seizure activity, blood sugar levels and the data that builds predictive algorithms in pacemakers, to using onboard computing power. Today these edge devices can detect episodes and notify caregivers or emergency services without the latency of cloud computing and without the risk of being momentarily disconnected from the network.
- Smart manufacturing: Smart manufacturing facilities can improve safety, efficiency, and quality all while reducing costs through automated processes driven by decisions made on edge computing devices. Edge, IoT, driving insights from machine-to-machine data, can detect when a machine is about to fail and automatically apply contingency plans, such as diverting product to alternative lines or notifying stakeholders.
- Retail: Infrared sensors create physical heatmaps of where retail customers gather in the store and how they move about, which gives retailers up-to-the-minute insights on performance. They can optimize store layouts, ensure associates are in the right places, and deploy promotions with guaranteed results. Edge use cases for retail include advanced loss prevention strategies, enhanced customer experience and improved inventory management.
- Smart cities: The future holds limitless possibilities, but to make them a reality, cities must become digital organizations, ecosystems of interconnectivity powered by data, running in a multi-cloud world. The city of the future uses Edge computer vision to protect citizens, sensors to improve traffic flow and smart grids to reduce the impact on the environment. As municipalities upgrade their aging gas or water infrastructures, they can install edge devices capable of monitoring for faults or anomalies. An intelligent water meter, for example, could detect a water main leak and reduce or shut off supply to minimize the impact before services can respond.
- Environmental monitoring: Warning the public about dangers from fires, volcanoes and earthquakes is difficult because of the speed at which it happens, and how remote the locations where they are most common. Seismic, vibration, air pressure, and temperature sensors, when placed in rugged conditions at the edge, can not only detect anomalies internally, but also know when it’s time to inform public safety organizations.
The amount of data being generated across the globe will continue to grow. Organizations must innovate to find ways of managing that data. Edge computing will play a key role in overseeing and prioritizing data while decreasing costs, lowering necessary bandwidth requirements and reducing latency for delivering insights that can save lives, drive businesses forward and transform the world in which we live.