Use cases for AI on the edge
AI inference could be placed on a device, on-premise, or in the cloud, but the edge shines for numerous scenarios where speed and privacy matter. “Edge AI allows for instant decision-making where it matters most — close to the data source,” says Venkatesh. “This opens up use cases that weren’t possible before.”
Many user-facing situations could benefit from edge-based AI. Payton emphasizes facial recognition technology, real-time traffic updates for semi-autonomous vehicles, and data-driven enhancements on connected devices and smartphones as possible areas. “In retail, AI can deliver personalized experiences in real-time through smart devices,” she says. “In healthcare, edge-based AI in wearables can alert medical professionals immediately when it detects anomalies, potentially saving lives.”
And a clear win for AI and edge computing is within smart cities, says Bizagi’s Vázquez. There are numerous ways AI models at the edge could help beyond simply controlling traffic lights, he says, such as citizen safety, autonomous transportation, smart grids, and self-healing infrastructures. To his point, experiments with AI are already being carried out in cities such as Bahrain, Glasgow, and Las Vegas to enhance urban planning, ease traffic flow, and aid public safety.
