Switchgear monitoring for anomalies using AI predictive models and markers
This technology relates to a switchgear system that uses an AI platform's anomaly prediction model to forecast signs of failure or fire, records them on a marker, and allows for data utilization via smartphone capture.
Conventional switchgear systems struggle to predict and share anomalies early, leading to delayed responses to failures and fires.
To address this, this technology analyzes abnormal current patterns using a big data-based predictive model, records the findings on a marker, and enables immediate information utilization through smartphone capture.
Key Features:
- Predicts signs of failure and fire by identifying abnormal current patterns based on anomaly prediction models tailored to input data and power information types on an AI platform
- Records predicted information onto a marker mounted on the exterior of the switchgear
- An AI monitoring system configured to utilize recorded information by capturing the marker with a smartphone
- Includes a smartphone mount for capturing the marker, with the mount featuring a base pad equipped with an attachment component
