Smart Buildings & Indoor Environmental Quality
Integrated occupancy, ventilation, and air-quality sensing across VinUniversity, Vinhomes residences, and Vincom Retail spaces.
Pilot Status: Planned | Formal Launch: January 2027 | Timeline: VinUniversity (2026) → Vinhomes Phase 1 (2027)
The Challenge
Indoor environmental quality directly impacts occupant health, comfort, and productivity. Yet most sensor networks drift silently—CO₂ sensors age, calibrations fail, and occupants never know whether they're breathing truly fresh air or a sensor's false positive. Pilot 01 deploys self-aware sensing infrastructure that quantifies this uncertainty in real time.
Sensor & Inference Stack
Neuromorphic Edge-AI Inference
Environmental modules compute uncertainty metrics locally on-chip using low-power memristive hardware. This eliminates raw, un-vetted sensor streams being transmitted to cloud networks, enabling:
- ▸Zero-latency confidence scoring — confidence bounds computed before data leaves the node
- ▸Privacy by design — raw environmental streams never transmitted, only validated measurements and uncertainty estimates
- ▸Autonomous failure detection — sensor drift, bio-fouling, or thermal stress flagged on-node without cloud dependency
CMOS-Integrated Electrochemical Gas Sensing
Solid-state, fully integrated gas sensors (CO₂, TVOCs, particulate matter) engineered to execute automated on-chip baseline calibration. This directly addresses sensor drift:
- ▸Integrated AFE tuning — calibration baseline updated dynamically as the sensor ages
- ▸Cross-channel validation — multi-modal gas sensors detect electrochemical inconsistencies
- ▸Occupancy-adaptive baseline — CO₂ drift differentiated from occupancy changes via pattern recognition
Adaptive Electrochemical Drift Compensation
Watch how on-chip RLS (Recursive Least Squares) filters detect and compensate for sensor drift in real-time. Adjust drift intensity and sensor type using the controls below. The algorithm continuously learns the baseline corruption pattern and corrects it before the signal leaves the node.
Phase 1 & 2 Deployment
Controlled environment with known baseline. Academic buildings, dormitories, and common spaces instrumented with 40–60 sensor nodes. Quarterly validation cycles with ASHRAE comparators.
Scale to residential occupancy patterns with seasonal variation. Initial deployment: 200+ units across one Vinhomes complex. Occupant feedback and long-term drift characterization.
This pilot draws on V-SENSE's three core engineering frontiers: