人工智能方案目錄

WildFaces’ predictive maintenance system is based on multi-sensory artificial intelligence, combining video, sound, and smell analytics. Unlike deep learning approaches that rely on massive datasets and GPU computing, this solution uses patented “Intuitive AI” technology, which requires only a very small amount of data from equipment in normal condition (e.g., fewer than 30 images) to train models.

The system detects anomalies by analyzing equipment appearance (e.g., rust, cracks, or looseness), sound patterns (e.g., abnormal vibrations or unusual noises), and smell indicators (e.g., burning odors or chemical leaks) to predict potential failures. This enables automated and cost-effective maintenance processes, reducing the need for time-consuming and error-prone manual inspections.

WildAI provides early warning of potential equipment failures, helping prevent incidents and damage to infrastructure. For example, it can detect overheating pumps, identify corroded pipes that may leak, and automatically stop an escalator if a small object (e.g., a screw or coin) is about to fall into its mechanism.

The technology can be deployed on fixed cameras, drones, robots, and IoT devices, enabling scalable predictive maintenance across a wide range of facilities while improving operational efficiency and reducing maintenance costs.

-Railway Maintenance: Analyzing meter readings in the driver's cab, monitoring engine overheating (using thermal imaging), detecting abnormal engine start/stop sounds.

-Equipment Visual Inspection: Automatically detecting loose screws, metal scratches, cracks, deformation, or rust on equipment.

-Leak Monitoring: Detecting oil or water leaks from equipment, or unusual steam/smoke.

-Odor Warning: Detecting abnormal smells like "burning odor" or "toxic chemical smell" within a facility for early warning.

-And more...