BIM-based digital twin platform integrating real-time occupancy data from building spaces.

A real university building required device data to be connected to a BIM-based digital twin so that occupancy profiles could be represented by building space and time band rather than treated as generic asset telemetry.
The integration layer connects local tracking sensors with a BIM based digital twin, processing occupancy data and updating the building information model in real time. Edge processing keeps data private, reduces latency, and enables operation without cloud connectivity.
Space-level occupancy profiles
Time-band occupancy analysis
BIM-based digital twin integration
Real-time building data synchronization
ML-based local tracking

IoT data acquisition

API integration

Data synchronization

Cloud connectivity

Dashboard support







Technologies:
IoT devices, Cloud services, REST API, MQTT, Data processing, Digital-twin integration, Backend services, Custom CM4 carrier board, Machine Learning (Edge AI), Wireguard, Golang
Methodology:
API-first architecture, System integration, Continuous validation
Team:
3 engineers
Duration:
12 months