Edge Ecosystem Podcast: Lumen Technologies and the retail industry use case for edge
Edge Industry Review has a new episode of the Edge Ecosystem Podcast available. On this episode, our guest is Scott Brindamour, head of product innovation at Lumen Technologies, who discusses the edge computing ecosystem and the use cases that Lumen Technologies is deploying.
Lumen is primarily thought of as a provider of network connectivity services, but has long offered CDN services and has branched out into edge computing as a natural complement to connectivity. That combination of network connectivity and edge computing is evident even in announcements about expanding the core network’s capacity.
Brindamour explains that his role at Lumen is to focus on derisking emerging technologies and understanding how they can be used at the edge. His team then focuses on productizing those technologies, noting that those companies investing heavily in technology are the ones that experiment with emerging tech sooner and have larger IT departments.
Currently, retail stores are one of the biggest use cases for edge computing, according to Brindamour. Large box stores like Home Depot and Walmart are leveraging edge computing to optimize their real estate, network connectivity, and to provide better customer service.
The show wraps with a discussion of some of the underlying services that Lumen offers, ranging from network connectivity to bare metal as a service, as well as what’s ahead for Lumen’s edge strategy.
Show notes
(2:06) The companies that tend to invest heavily in technology and have big IT departments are the ones that tend to embrace emerging technologies and experiment with them. Some smaller companies are also advanced in their technology use, focusing on using technology as a tool to improve customer experience, supply chain, inventory management, and reduce costs.
(3:03) Lumen is finding that edge computing is commonly used for sensor-driven applications such as computer vision, which can be used for tracking people in stores to optimize traffic flow, understand the number of customers, and improve the customer experience. Edge computing can also be used for behavioral analytics to gather data on customer behavior and purchase patterns. Another use case is frictionless checkout, which enables customers to quickly enter the store, scan their items, and leave without having to wait in line or interact with personnel. This type of checkout is supported by technology such as apps, sensors, beacons, and cameras. Edge computing can also be used to prevent theft and improve accuracy in self-checkout aisles by using cameras to monitor scanning and prevent manipulation.
(7:20) Lumen is considering how to bundle edge computing solutions to retailers, especially those with many locations because they are the ones that have difficulties with the management of inventory and the IT requirements of processing video in-store. The idea is that Lumen would offer a network-connected GPU as a service in a small number of locations near the customer. This would reduce costs, reduce waste and allow the retailer to focus on the real-time use cases that they require, without having to manage a large IT infrastructure.
(14:05) Investing in new technology without a large upfront cost is important. The technology changes every 6-9 months, so having the ability to turn it on quickly is necessary. This can be achieved through a network device or using a third-party provider as long as it meets the latency requirements.
(16:17) Brindamour discusses in broad terms some of the areas of research and development for Lumen in the coming year. He also offered some thoughts on what are some of the key areas of the edge ecosystem that still need development, and how Lumen could play a role in interconnecting private wireless networks at the network edge with applications and content that is residing in the cloud.
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Article Topics
BMaaS | CDN | computer vision | edge computing | EdgeIR Video Interviews | GPU | Home Depot | Lumen Technologies | networking | retail | Walmart
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