Written by AQ | Dec 9, 2025 9:18:34 AM
- Immediate detection of on-site anomalies and situation assessment
- Action proposal by LLM and robot automatic response
- Continuous knowledge accumulation through Human in the Loop
For Various Industries Industry-Specific Use Cases
01. Manufacturing (Line Anomaly Detection / Equipment Maintenance)
- Use Cases
- Real-time detection of manufacturing line operational anomalies or foreign object contamination from camera footage.
- Based on vibration and temperature changes in specific equipment, the LLM assesses the failure risk and proposes predictive maintenance actions.
- Detects misalignment or stoppage of a robot arm and automatically makes fine adjustments to the arm position or issues recovery instructions via ROS.
- Effects
- Minimizes production line downtime and contributes to improved productivity.
- Reduces high repair costs caused by sudden failures through predictive maintenance.
- Accelerates initial response when quality issues occur, reducing the risk of defective products being shipped.
02.Construction and Infrastructure (Safety Management / Remote Inspection)
- Use Cases
- Detects hazardous behavior of workers on construction sites (e.g., not wearing safety harnesses) via camera footage and sends immediate alerts to managers and on-site robots.
- Detects changes such as cracks or rust from drone footage of infrastructure (bridges, wind turbines).
- Proposes and executes detailed photography or simple repair actions remotely to inspection robots in response to detected anomalies.
- Effects
- Significantly reduces the risk of industrial accidents and enhances site safety.
- Improves the efficiency of wide-ranging infrastructure inspection work and standardizes inspection quality.
- Reduces access to hazardous areas, cutting inspection costs and human risks.
03.Warehousing and Logistics (Inventory Anomaly Detection / Sorting Optimization)
- Use Cases
- Detects package collapse or anomalies in inventory quantity/arrangement in specific warehouse areas using surveillance cameras.
- The LLM analyzes sorting robot operational errors or a sudden increase in cargo volume to be processed, and proposes corresponding actions (speed adjustment, route change).
- Activates AGVs (Automated Guided Vehicles) to automatically re-arrange or tidy up cargo in response to detected anomalies.
- Effects
- Improves inventory management accuracy and operational efficiency within the warehouse.
- Eliminates sorting bottlenecks during peak seasons, improving logistics throughput.
- Reduces the human resources and time required to handle troubles such as package collapse.