Term 252

Smart Building Digital Twin (Lite): HVAC Energy & Comfort Optimization for KFUPM Building 54

Project Type: Self-Initiated

Project Description

This project develops a read-only, zone-level digital twin for an existing university building to quantify and reduce HVAC overcooling while maintaining indoor quality. The system deploys non identifying sensors (temperature, humidity, and CO2 environmental with PIR-based occupancy) and performs standalone logging without dependence on campus IT/BAS networks. Collected data are time synchronized (≤ ±10 minutes) and used to compute thermal comfort (PMV), IAQ understood through indoor–outdoor CO2 differential, and energy performance indicators including zone cooling-load index, EUI, and peak kW. The digital twin is implemented as an interactive Unreal Engine dashboard that visualizes both zone and building summaries with end-to-end data latency ≤ 5 minutes and refresh ≤ 10 minutes. To support quantitative validation, the project defines a baseline window and comparison rules (aligned with occupancy schedule and weather treatment) and evaluates ≥ 4 rule-based operational scenarios that provide decision indicators derived from measured variables. Performance is assessed against fixed targets: temperature within 22–26°C and PMV within −0.5 to +0.5 for ≥ 90% of occupied hours, indoor CO2 quality Cin − Cout ≤ 400 ppm for ≥ 90% of occupied hours, and energy outcomes including ≥ 5% HVAC energy and peak reduction, with prediction accuracy MAPE ≤ 12% against metered data. The pilot discussion focuses on the HVAC type present in the selected zone (e.g., CAV), ensuring the concepts and evaluation reflect the actual building system. The final deliverable is a reproducible workflow that translates multi-domain measurements into a balanced recommendation where no single discipline dominates the justification.