Going forward, 5G edge will serve as a scalable, flexible connectivity and computing platform on which organizations can deploy an array of powerful digital technologies. These tools can help you glean valuable insights from mountains of customer and operational data; achieve cost efficiencies through automation; and create a nimble IT infrastructure that can adapt quickly when new opportunities arise.
Consider how the following 5G edge and digital possibilities could impact your bottom line:
Capture cost savings in manufacturing and logistics with computer vision. The combination of software and hardware is making it possible to automatically extract, analyze, and understand useful information from a single digital image, a sequence of images, or an entire video. In the arena of disruptive digital technologies, computer vision can be a game changer. It supports real-time analysis and decision-making, and allowing organizations—particularly those with thin margins—to control and automate some functions across the value chain, regardless of industry.4 For example, cameras are rapidly becoming ubiquitous and connected. Supply chain operators are placing them, in tandem with AI, throughout warehouses and freight yards to count stock. Other organizations are exploring computer vision use cases on factory floors and in offices to validate safety protocols and help maintain procedural compliance.5
Innovate and automate with IoT, AI, analytics, and computer vision. With 5G edge addressing long-standing constraints on data processing power, we expect new data-driven applications will lead to new business models and innovations within the next two years. In retail, this gold rush is already underway. A number of online and traditional retailers are exploring an alternative “grab and go” business model that leverages advanced networking, a variety of sophisticated sensors, and real-time analytics to deliver an “autonomous shopping experience.” In other words, there are few, if any, employees on site because almost everything is automated. As a customer enters the store, IoT sensors and computer vision track the individual’s movements and product selections, and analyze this information—along with the customer’s purchase history—to suggest additional products and offer coupons. When the customer finishes shopping, the system senses the items selected, tallies their cost, and charges the amount owed to a payment account in the app. Not only do retailers increase efficiency by managing inventory in real time, they can also reduce payroll costs.6
Increase productivity with autonomous robots and vehicles. For now, ignore the steady drip of sensational headlines about autonomous cars. The more intriguing stories—and the ones that directly relate to your future competitiveness—describe how autonomous robots and heavy machinery are loading ships in Chinese and Dutch ports.7 Or how 5G edge is turbocharging robotic deployments in Canada and the United States to create fully automated grocery warehouses and fulfillment centers.8 These technologies can drive value by reducing direct and indirect operating costs and increasing revenue potential. They can lower labor costs and increase productivity by working around the clock. Likewise, “cobots” work alongside human workers, augmenting their performance. Their movements are programmable, which enables them to perform specific tasks such as sorting packages. In material transportation environments, cobots can zip past each other, people, or moving objects in a warehouse or on a factory floor thanks to advanced collision avoidance capabilities.9
Optimize operations with digital twins. Digital twin technology makes it possible to build a digital replica of a single process or an entire operation. This data-hungry tool can help optimize supply chains, distribution and fulfillment operations, and even hospitals. As an example of how this works, let’s say a global consumer products manufacturer creates virtual models of dozens of its factories. At each location, IoT sensors embedded in factory machines feed performance data into AI and machine learning applications for analysis. The analyzed operational information is fed into digital twin simulations, which then identify opportunities for workers to perform predictive maintenance, optimize output, and limit waste from substandard products. Taken together, these opportunities can have a major positive impact on efficiency and cost.