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Funded by the Environment and Conservation Fund and organised by the Hong Kong Green Building Council (HKGBC), this micro-credential topical course series is designed to provide participants with more in-depth continuing education than traditional CPD webinars. It enables practitioners to construct weekend or after-hours study programmes that meet their development needs. Courses will be rolled out at a frequency of about 1-2 courses per month, throughout a period of two years from 1 September 2025 to 31 August 2027. Participants taking 20 or more courses can apply for a skill enhancement certificate from HKGBC, certifying their significant efforts in studying green building.

Micro-Credential Topical Course – AI Applications in Smart Green Buildings

Nowadays, many buildings already collect operational datasets, but they often sit in separate systems, are hard to trust and have little bearing on day-to-day operational decisions. 

This intensive 2-hour technical talk equips green building professionals with a practical five-step framework to optimise smart green buildings by converting operational data into measurable building-performance improvements.

The five-step framework is as follows:

Step 1 - Start with the Building Outcome: 

Overcoming stalled pilot projects by translating strategic goals into operational questions; selecting actionable Key Performance Indicators (KPIs) that operators can influence, including energy, water, Indoor Air Quality (IAQ), reliability, and carbon resilience, while distinguishing reporting metrics from operational control metrics.

Step 2 - Connect and Contextualise Building Data:

Integrating data from Building Management Systems (BMS), utility meters, Computerised Maintenance Management Systems (CMMS), and Internet of Things (IoT) technologies through protocols such as BACnet, Modbus, MQTT and APIs; addressing time-series data management, semantic tagging, data quality and cybersecurity.

Step 3 - Turn Insight into Operational Action:

Moving beyond alarms and dashboards by converting insights into prioritised actions through fault-to-work-order workflows, defined approval processes, accountability mechanisms, and frontline execution.

Step 4 - Apply AI: 

Understanding the differences between rule-based approaches and machine learning techniques, including supervised learning, unsupervised learning, forecasting, and Fault Detection and Diagnostics (FDD); applying AI to forecasting, HVAC and chiller optimisation, anomaly detection, predictive maintenance, IAQ analytics, and operational documentation.

Step 5 - Verify and Scale: 

Establishing performance baselines, accounting for weather and occupancy variations, validating savings persistence, and scaling successful initiatives from individual projects to portfolio-wide deployment and governance.

After the course, participants will gain a practical method for identifying a credible, measurable building-improvement use case.

Speaker: Mr Tobby FU Sin-tou, Senior Director of AI Solutions, NTT Com Asia Limited 

Language: English

Target Audience: Building Owners, Property/Facility Managers, E&M Engineers, and Sustainability Consultants

Learning Mode: Hybrid (registrants can choose either Physical/Online)

Capacity: 50 (Physical); 1,000 (Online)

Register Now