Edge AI servers bring data processing and analysis closer to the source. Deployed at the edge of networks or in proximity to data-generating devices, these servers enable real-time AI inference, low latency, and enhanced decision-making capabilities. Edge AI servers excel at processing data locally, minimizing delays caused by data transmission to centralized servers or the cloud. Equipped with processing capabilities such as CPUs, network IO, storage and AI accelerators, Lanner edge AI servers perform AI inference and real-time analytics at the edge and find applications in various domains, including network security, automation, computer vision and autonomous driving. By processing data at the edge, they empower these industries with real-time intelligence, enhanced decision-making capabilities, and reduced bandwidth usage.
Lanner Edge AI Server works a high-performance network security platform specifically designed for an AI-powered next-generation firewall. The integration of Intel Deep Learning Boost and Intel Traffic Analysis Development Kit enables faster decision-making, facilitating quick identification of malicious patterns, real-time threat detection, and classification.Use Case
Lanner Edge AI Server can enable computer vision for automated warehouse management tasks, including object detection and recognition. The server analyzes video feeds from cameras to identify and locate items, monitor stock levels, and detect anomalies or discrepancies. This enables more efficient inventory management, reduces manual errors, and improves overall accuracy.Use Case
Lanner Edge AI Server enables an Automated Fire Detection System for critical infrastructure. By integrating computer vision and AI algorithms, the system can analyze data from thermal cameras and smoke detectors to identify potential fire threats. It can then trigger temporary power transmission shutdowns to mitigate the risk of wildfire ignition from transmission cables.Use Case
Lanner Edge AI Server plays a crucial role in enabling autonomous driving. By providing computing power and AI acceleration for processing data from sensors, cameras, LiDAR, radar, and GPS, it enables real-time analysis of complex driving scenarios. This analysis helps in interpreting the environment, detecting objects, making informed decisions to changing road conditions.Use Case