Smart Behavior Detection in Manufacturing Assembly with Lanner Edge AI - Lanner Electronics | Network Appliance | uCPE SD-WAN| MEC Server | Intelligent Edge Appliance

In today’s competitive manufacturing landscape, ensuring consistent assembly quality and maintaining workplace safety are top priorities. Manual processes or hybrid human-machine workflows often introduce variability and risk that traditional monitoring systems fail to catch in real time.

Solution

To solve this, Lanner’s Edge AI-platforms provide low latency AI inference right at factory zones, including cabinet assembly, packaging, and manual workstations. These platforms can integrate AI vision models and industrial-grade video cameras, providing continuous, real-time monitoring of behavior patterns to detect anomalies, prevent errors, and reduce safety risks.

At the heart of the solution are three scalable platforms designed for different performance needs:

• The EAI-I133, built on NVIDIA Jetson Orin, is ideal for entry-level behavior detection with single video stream analysis.
• The EAI-I731, equipped with NVIDIA L4 GPU, supports mid-range deployments, managing up to five concurrent video streams with fast AI inference.
• The EAI-I730, powered by an RTX 6000 Ada GPU, delivers up to 1457 TOPS and handles intensive multi-stream analysis and model training workloads.

All Edge AI platforms feed into a centralized Factory Management Platform, enabling supervisors to oversee operations from a unified dashboard. The Edge AI computer integrates with alarms, sensors, emergency stop buttons, and HMI interfaces to trigger real-time alerts and enable instant human intervention when unsafe or irregular behavior is detected.

Deployment Scenarios

In one example, the system was installed on an assembly line where screen modules were frequently misaligned due to inconsistent manual handling. By monitoring hand movements and object positions in real time, the system flagged deviations from standard operating procedures, significantly reducing rework and improving throughput. In another case, the behavior detection AI triggered a safety alarm when a worker moved too close to a robotic arm, preventing a potential injury.

The result was a measurable improvement in production consistency, reduced downtime from human errors, and enhanced workplace safety—all achieved with minimal disruption and scalable AI deployment.

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