| I&T Solution |
Intelligent Fault Detection and Optimization System
(REF: S-2072) |
| Trial Project |
|
| Solution Feature |
- Using the software platform, sensor and control data are analyzed by AI models to predict potential faults early.
- The hardware-agnostic platform supports multiple protocols and easily integrates with existing BMS or IoT systems.
- Built-in rule and workflow engines automate alerts, reports, and work orders to support facility management decisions.
- Models are fine-tuned with normal and known abnormal data, improving over time through user feedback on detected anomalies.
- Reduces equipment failure rates and downtime, enhances HVAC efficiency, and ensures a safer healthcare environment.
|
| Trial Application and Expected Outcome |
- Connect existing sensors and control systems at pilot sites to collect real-time and historical data.
- Train models with normal operation data and fine-tune using verified anomaly samples.
- Monitor predictions during pilot operations and refine models based on operator feedback.
- Evaluate alert accuracy, response time, and improvements in predictive maintenance efficiency.
- Standardise validated models and workflows for scalable deployment across other facilities.
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| Info on I&T Solution Provider |
| Solution Provider | : | Cereb Intelligence Limited | | Address | : | 3/F, Building 2W, Hong Kong Science Park, Pak Shek Kok, New Territories, Hong Kong | | Contact Person | : | Trevor Ho |
| Position | : | CEO | | Tel | : | 69766934 | | Email | : |
trevor.ho@cereb.ai | | Webpage | : | https://www.cereb.ai |
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