Combined with cloud, edge will enable businesses to reimagine experiences. The potential applications of edge have expanded far beyond just manufacturing and IoT. Edge can be incorporated to drive rapid decision-making and improve user experiences by increasing relevance at each touchpoint. Now, edge is helping create new insights and experiences, enabled by the larger cloud backbone.
Some benefits of edge computing include:
Rapid response: Data transmission takes time. In some use cases—like self-driving cars or telesurgery—there isn’t time available to wait for data to make a round trip to the cloud and back. Edge makes sense for these cases where there are requirements for real-time or extremely rapid results.
High data volume: While the cloud can handle very high data volumes, there is a significant cost of transmission and physical limitations of network capacity to take into account. In these cases, it might make more sense to process the data at the edge.
Privacy: Users may prefer (or be required) to keep control of sensitive data locally without sending it to the cloud.
Remote areas: Some use cases are “remote” in the sense of connectivity, whether actually remote (like an offshore oil drilling platform) or practically remote (involving mobile or transportation-related scenarios using edge).
Cost sensitivity: Processing data in different parts of the cloud continuum involves different cost profiles, which can be optimized to minimize total cost across the system as a whole.
Autonomous operations: Where connectivity to the cloud is not possible—or likely to be intermittent or unreliable—users may need end-to-end processing within the local environment to keep operations up and running.
The prime advantage of edge computing is clear: User experience improves because relevance increases with edge. Additionally, edge unlocks valuable data to shape new opportunities and innovation for the future. More sensors generate more data, and there is more processing at the location where the data is created—which is faster, more reliable and safer. Integrated with knowledge from the cloud, the system yields better predictions and more relevant information, repeating in a cycle of continuous improvement.
Other characteristics of edge use cases include:
Intelligent machines and real-time productivity: Edge lets users process data with velocity, enabling robots and sensors to make split-second decisions and complete tasks in smarter, faster and safer ways. This is revolutionizing everything from smart signage to assembly-line quality assurance.
Optimized close to consumption: Digital production and consumption is optimized for the best experience and lowest cost, making edge work for content delivery, for example, or on an offshore oil well.
Experience with extended reality: These use cases can incorporate digital twins and optimize rich experiences in healthcare, the workforce and entertainment, from smart health to mixed-reality gaming.
Privacy and security by default: By processing sensitive data on the edge, these use cases improve reliability and protect privacy. Examples include wearable health devices and the processing of regulated data.
Always-on and untethered: Edge allows for decision-making and processing independent of connectivity for mission-critical and remote applications, like POS or autonomous operations.
Edge computing examples
Let’s dive into a couple of examples of edge use cases that are already happening today and will only improve with a greater 5G rollout and other innovations.
Retail: A flexible, customer-centered experience that is at the heart of a Store of Tomorrow concept, a new integrated vision for the near future of retailing. Edge technology will be a core retail capability in the near future and is a key enabler component for the human-centered experiences at the heart of this model. One of the applications of edge is frictionless store checkout. Long lines are the bane of shops: 86% of consumers have left a store because of them, resulting in an estimated $37.7 billion in missed sales annually in the United States.
An edge network in the store processes data collected by on-site cameras using AI that is trained to recognize inventory items, allowing customers to walk out of the store past a kiosk that accurately charges their accounts without waiting in line. Retailers can provide a superior customer experience, prevent theft and better manage their inventories and supply chains.
