A convergence of technology is leading to a digital transformation that has been in the works for several years. With 5G maturing and 5G standalone on the horizon, IoT accelerated adoption, maturity in the cloud, and now the rising demand for edge computing – it can be confusing to know whether these emerging technologies are competing or if they come together to maximize the opportunity.
An IoT solution begins by connecting sensors within IoT devices to the internet. Those devices collect and transmit data that is analyzed and displayed through a user interface. The internal infrastructure of an IoT solution runs communications beginning with the endpoint through an IoT platform to the cloud and back. That’s a very boiled-down explanation of the IoT technology stack, but the important thing to note is that it’s interconnected. The cloud is a major component of the tech stack because that’s where the data collected and transmitted through the IoT devices and platform are computed and processed.
Now with the introduction of edge computing, the distance that data needs to travel to be processed and computed is getting shorter – and it’s largely dependent on the use case and where an enterprise chooses to have the edge sit.
With edge computing comes greater bandwidth, lower latency, higher speed, and more accessibility when connectivity is limited or bandwidth is restricted.
Edge computing isn’t going to overtake the cloud and in fact, many edge computing builds are going to integrate into the cloud. Infrastructure is built to satisfy both technologies and some use cases might choose to divert some data to the cloud and other more mission-critical or sensitive data along the edge.
Data requirements are going to continue to incline – with 5G, IoT, as well as edge and cloud computing. Hyperscalers offer agility in computing and data management for many reasons, particularly in the ability to scale up as needed. With 5G and IoT, large amounts of data are likely to be processed.
One key area where data generation will be high is artificial intelligence, which is readily supported through IoT. IoT lays the groundwork for massive data aggregation that can help enhance and accelerate the adoption of artificial intelligence (AI). IoT combined with artificial intelligence (AIoT) and machine learning can power end-to-end operational business solutions by accelerating data processing and programmed evaluation.
Many industry segments have an opportunity to benefit from AI, including:
Enterprise and corporate: AI meets the workplace in the form of augmented reality (AR), virtual reality (VR), or extended reality (XR). AI can help achieve collaboration and efficiency no matter where employees are located, whether it’s a decentralized work office or global offices. Robotic process automation (RPA), as well, is an AI application that can help streamline operations by automating administrative tasks such as billing, order processing, and other routine data entry.
Fleet: Artificial vision is paired with in-vehicle video monitoring that screens drivers for unsafe behavior, such as distracted driving, cellphone use, or drowsiness. The driver is alerted in real-time to help support safety on the road.
Supply chain and logistics: AI can help tackle forecasting through data-driven decisions and can drive greater visibility across the entire supply chain through more precise analytics.
Manufacturing: This industry is facing workforce shortages, labor skills gaps, safety, efficiency, equipment maintenance, cost mitigation, and more. With the adoption of Industrial IoT (IIoT) and AI, manufacturing firms can integrate technologies such as digital twins, robotics, and automated guided vehicles.
Healthcare: Robotics, digital twins, and high-performance analytics can be adopted within hospitals to increase efficiency, optimize physical infrastructure, and support greater patient outcomes.
Edge computing can support artificial intelligence in those applications where the device-level response needs to be incredibly quick, like in healthcare and manufacturing robotics, for instance. With the rollout of 5G standalone, the speed with which data packets are communicated will be very fast and edge computing can help even further reduce latency in computing.
A common thread in 5G and edge solution is it requires relationships with Mobile Network Operators (MNOs) and hyperscalers for the connectivity and the computing components. Particularly with edge infrastructure, it’s not been entirely defined who is the main provider of edge solutions – telcos or hyperscalers. The edge sits in many different places, as well, and even when deploying edge solutions, cloud integration is important. IoT providers can be a simplified bridge to 5G, cloud, and edge deployments by having expert, strategic partnerships with both MNOs and hyperscalers.
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