What You’ll Learn: Building Intelligence
Design buildings that don’t just respond—but *anticipate*. Learn to fuse IoT, AI, and domain knowledge to create self-optimizing environments that balance energy, comfort, health, and operational resilience.
AI-Optimized HVAC
Replace rule-based schedules with ML models that predict thermal load and optimize setpoints in real time.
Occupant Behavior Modeling
Infer presence, activity, and preference from Wi-Fi, CO₂, and motion—without compromising privacy.
Predictive Maintenance (MEP)
Forecast chiller failure, VAV box drift, and pump cavitation using vibration + operational telemetry.
Building Digital Twins
Simulate retrofit impacts, fault scenarios, and emergency responses before deploying on-site.
Who Should Enroll?
For professionals shaping the next generation of high-performance, human-centered buildings.
- Architects & computational design leads
- Building services (MEP) & sustainability engineers
- Facility & property managers (commercial, healthcare, campus)
- Smart city & urban infrastructure planners
- Building automation & IoT system integrators
- ESG & real estate portfolio analysts
Smart Building Projects
AI HVAC Optimizer (Office Tower)
Reduce energy by 22% while maintaining PMV within ±0.2—using occupancy forecasts + weather lookahead.
Predictive Chiller Failure Model
Detect early-stage refrigerant leaks & compressor wear 7 days in advance using BACnet trend logs.
🏢 Retrofit-Ready
Smart Retrofit Plan (Hospital Wing)
Design a phased IoT + edge-AI rollout for a 20-year-old facility—prioritizing critical zones and ROI.
6-Week Smart Building Syllabus
~42 hours • Real BACnet/Modbus datasets • Grafana + Node-RED labs • Digital twin simulation • 1:1 mentor
Weeks 1–2: Foundations & Sensor Integration
- Smart building stack: sensors → edge → cloud → dashboard
- Protocols deep-dive: BACnet/IP, Modbus, MQTT, COAP
- Privacy-preserving occupancy sensing: Wi-Fi probing, CO₂ correlation, anonymized BLE
- Lab: Ingest & visualize live BMS data streams in Grafana
Weeks 3–4: AI for Energy & Comfort Optimization
- Thermal load forecasting: LSTM + weather + calendar features
- Model Predictive Control (MPC) for HVAC: cost vs. comfort trade-offs
- Personal comfort modeling: integrating surveys, skin temperature, activity
- Lab: Tune an AI setpoint optimizer for a mock office zone
Weeks 5–6: Predictive Maintenance & Digital Twins
- Failure mode libraries: chillers, AHUs, pumps, VAV boxes
- Feature engineering: derivative trends, cross-variable correlations
- Building digital twin layers: geometry, physics, control logic, AI agents
- Capstone: Present your smart retrofit roadmap + ROI analysis
NSTC‑Accredited Certificate
Validated credential for LEED/WELL AP maintenance, ASHRAE certification pathways, and smart building RFP compliance.
Frequently Asked Questions
Familiarity with building systems (HVAC, lighting, sensors) is helpful—but not required. We provide primers on BACnet, Modbus, and BMS architectures. You’ll use intuitive dashboards (e.g., Grafana + Node-RED) to simulate and optimize systems—no PLC programming needed.
Yes. Over 50% of projects focus on cost-effective retrofit strategies: adding IoT gateways, AI edge controllers, and cloud analytics to legacy BMS. You’ll learn deployment pathways for commercial, institutional, and multi-family residential buildings—regardless of age.
