| I&T Solution |
Develop an AI-based Control System to Forecast Sewage Flow Rate, Optimize Pump Control and Reduce Energy Consumption
(REF: S-1912) |
| Trial Project |
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| Solution Feature |
- Predict time-series inlet flow rate based on historical data
- Construct a network based on the layout with pump control and energy consumption parameters
- Formulate an optimization problem where the objective function
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| Trial Application and Expected Outcome |
- Deploy AI system in sewage facilities to validate flow prediction accuracy against real-time data. Outcome: Enhanced forecast reliability and reduced overflow risks.
- Test optimized pump control under live conditions, tracking energy use and pump cycles. Outcome: Lower energy costs and minimized pump wear.
- Integrate with existing protocols to ensure interoperability. Outcome: Seamless data exchange and adaptive control.
- Run trials across diverse flow scenarios for 14 days. Outcome: Proven system resilience and performance gaps.
- Analyze daily reports on energy savings and operations. Outcome: Iterative algorithm refinement for efficiency.
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| Additional Solution Information |
W-0563.pdf
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| Info on I&T Solution Provider |
| Solution Provider | : | Green AI Technology Limited | | Address | : | Room 556, 5/F, Building 19W, 19 Science Park West Avenue, Pak Shek Kok, N.T., H.K. | | Contact Person | : | Lam Ho Lok |
| Position | : | CEO | | Tel | : | 6213 5937 | | Email | : |
colalam@greenaitech.com | | Webpage | : | https://www.greenaitech.com/ |
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