The AIPQAP (AI Power Quality Analytic Platform) by iBonus Limited is a cloud-based, zero-capex solution for intelligent electrical health monitoring. It uses AI to learn facility-specific patterns, establish dynamic baselines, detect deviations, correlate parameters (THD, PF, voltage, etc.), predict failures early, and provide health scores (0-100) with root-cause diagnostics—targeting hospitals, data centers, manufacturing, and aging Hong Kong facilities for predictive maintenance, energy savings, and reduced downtime.

The AIPQAP (AI Power Quality Analytic Platform), also referred to as AIPQAP or AIPQPAP in the provided presentation, is a cloud-based, zero-capex AI-driven solution from iBonus Limited (Hong Kong) for intelligent electrical health monitoring.

Key highlights:

• Addresses limitations of traditional systems: static thresholds, false alarms, no predictions, isolated parameter monitoring (e.g., THD, power factor, voltage).
• Core innovation: Learns your facility’s unique “electrical personality” in phases — Learning (establishes context-aware baselines from load, time, conditions), Monitoring (detects deviations and early deterioration trends weeks ahead), Intelligence (correlates parameters, diagnoses root causes, predicts failures with timelines/confidence).
• Technologies: Multivariable regression for adaptive predictions; trend-based detection (sliding windows, rate-of-change, correlation to failure modes).
• Dashboard example: Shows real-time health indices (0–100 overall + per-parameter risks), device status overview (e.g., transformers, breakers) with color-coded alerts and diagnostics.
• Benefits: Predictive maintenance, energy savings (e.g., 3–8% in data centers/industrial), reduced downtime (20–40% fewer stoppages), extended equipment life, ESG compliance, avoided costs/fires.
• Competitive edge: Continuous, predictive AI vs. reactive threshold-based monitors, energy-only systems, or periodic manual tests.
• Target markets:
  • Healthcare (e.g., Tuen Mun Hospital implementation via EMSD)
  • Data centers (uptime, UPS/battery predictions)
  • Manufacturing/industrial
  • Commercial real estate (aging infrastructure, HVAC optimization)
• Hong Kong focus on aging facilities: Detects degradation from outdated wiring, harmonics, overloads (modern loads like EVs/ACs/LEDs/servers), leading to overheating, insulation breakdown, arcing, fires, outages.

It provides “electrical peace of mind” by forecasting issues (“something will likely go wrong, here’s what/why/how to fix”) rather than just alerting to current problems.

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