The A Team demonstrated an innovative aerial drone surveillance system that leverages Multi-access Edge Computing (MEC) to execute AI algorithms for real-time pedestrian and wildlife tracking. By utilizing ETSI MEC APIs, the solution enables intelligent data analysis directly at the network edge, allowing the drone to adapt its behavior to varying signal quality and power conditions without relying on heavy onboard hardware. This architecture significantly reduces the drone’s weight and cost while extending its autonomy, showcasing how standardized edge environments can support flexible, low-latency applications for 5G vertical markets. The project highlights the practical benefits of deploying localized AI assets to optimize surveillance operations and enhance overall system efficiency.
Keywords: Multi-access Edge Computing, autonomous drone flights, real-time video analysis, ETSI MEC APIs, surveillance applications