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Which systems are the focus of NIST’s AI-Optimized Building Controls project?

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  1. Which systems are the focus of NIST’s AI-Optimized Building Controls project?
    • Commercial-building heating, ventilation and air-conditioning systems
    • Passenger aircraft navigation systems
    • Restaurant payment systems
    • Municipal drinking-water billing systems
  2. What is the purpose of pre-cooling in a building demand-response strategy?
    • Guarantee lower energy use in every building
    • Use thermal mass to shift some cooling demand away from a peak period while considering comfort
    • Disable occupant comfort limits during peak hours
    • Replace the building automation system
  3. What comparison does NIST’s IBASIM research plan use when testing control algorithms?
    • Assume every new algorithm improves performance
    • Evaluate only how many parameters the model has
    • Compare their performance with baseline controllers under different scenarios
    • Remove comfort constraints to maximize the reported savings
  4. How does fault diagnosis fit NIST’s intelligent-building-agent research?
    • It guarantees equipment can never fail
    • It replaces all maintenance staff and inspection
    • It proves that every energy increase is a fault
    • Agents investigate equipment status to identify and diagnose possible problems
  5. Mengapakah jisim haba bangunan kadangkala digambarkan sebagai 'seperti bateri'?
    • Ia boleh menyimpan haba atau kesejukan, membiarkan penggunaan tenaga dialihkan mengikut masa
    • Ia menyimpan elektrik di dinding
    • Ia diperbuat daripada litium
    • Ia menyalakan lampu secara langsung
  6. What is NIST’s Virtual Cybernetic Building Testbed (VCBT) used for?
    • Issuing HVAC operating permits
    • Evaluating building-control hardware and software with a simulated building
    • Writing construction contracts
    • Replacing all onsite sensor data with forecasts
  7. Why should a building controller include occupant comfort constraints?
    • Comfort is irrelevant to HVAC control
    • AI can infer consent automatically
    • Energy savings should not come at the cost of unacceptable indoor conditions
    • A temperature sensor guarantees comfort
  8. How should an AI building controller be evaluated before deployment?
    • By training accuracy alone
    • By one day of energy data
    • By removing manual overrides
    • In simulation or a testbed first, then monitored in the target building with safety limits