A digital twin is a continuously updated virtual model of a physical asset — a building, a machine, a city block, or a supply chain. Sensor data from the physical asset feeds the model in real time, and the model can be queried, simulated, and analyzed independently of the physical asset.
For buildings, a digital twin typically represents: room-level environmental conditions (temperature, humidity, CO₂, noise, occupancy), mechanical system states (HVAC, elevators, pumps, generators), energy consumption by floor, zone, and circuit, access events and security system state, and structural data (vibration, load, water leak sensors).
The twin enables facility managers to optimize operations (reduce energy waste, schedule maintenance before failures), support regulatory compliance (environmental standards, fire codes), and provide verified data to tenants, insurers, and certifying bodies.
A digital twin is only useful if its data is trustworthy. Unverified twins have several critical failure modes:
A failed CO₂ sensor reports stale data. The twin shows acceptable air quality. The HVAC system does not respond. Occupants experience poor air quality for weeks before anyone notices.
In regulated environments (food cold chain, pharmaceutical storage), unverified twins can be manipulated to show compliant temperatures during audits while actual conditions are non-compliant.
A water damage claim requires proving that the flood sensor was functional and reporting correctly before the incident. Without ZKP verification, the insurer disputes the sensor data — litigation follows.
As buildings automate more decisions (AI-controlled HVAC, autonomous access management), falsified sensor data creates safety risks — fake fire sensor readings could suppress real alarms.
FidesInnova solves these problems by applying ZKP verification to every data point entering the digital twin. The twin does not just reflect the building — it reflects the building with cryptographic proof that the reflection is accurate.
Building sensors run FidesInnova firmware with the ZKP SDK. Before transmitting, each sensor generates a Groth16 proof (≈694ms) certifying firmware integrity and reading authenticity. Proofs are transmitted alongside readings via MQTTS.
The building's FidesInnova Node receives all sensor data, verifies incoming proofs, and runs Service Contracts for the twin. Only readings with valid proofs are fed into the twin model. Invalid proofs trigger immediate alerts (potential sensor compromise or failure).
The digital twin consumes data exclusively from the FidesInnova Node's verified data store. Any third-party BMS (Building Management System) integration receives only proof-verified readings — raw, unverified data from non-FidesInnova sources is marked as "unverified" in the twin UI.
Every verified reading is anchored on the FidesInnova blockchain. This creates an immutable, timestamped history that regulators, insurers, and certifying bodies can independently verify via the ZKP Explorer — no access to your building systems required.
A comprehensive building digital twin requires sensors across multiple systems. Recommended sensor architecture:
Temperature, relative humidity, CO₂ (ppm), TVOC (air quality), PM2.5, illuminance (lux), noise (dBA). Sample every 5 minutes minimum; every 60 seconds for occupied critical zones.
Smart energy monitors on main panels and sub-panels. kWh, kW demand, power factor, voltage and current per phase. Real-time monitoring for demand response participation.
Passive infrared (PIR) motion sensors per room/zone. Optional: CO₂-based occupancy estimation (privacy-preserving — no cameras). Door contact sensors for entry/exit counting.
HVAC system status (on/off, fault codes, filter differential pressure), pump vibration and temperature, elevator door cycle counts, generator run hours and fuel level.
Leak detection sensors at water-risk locations (under sinks, near HVAC drain pans, pipe joints). Structural vibration sensors for seismic monitoring or vibration from nearby construction.
Door open/close with credential events (anonymized badge IDs). These are highly privacy-sensitive — use ZKP range proofs (access event occurred / did not occur) rather than sharing raw badge data.
Verified occupancy and environmental data enables precise HVAC optimization. A Service Contract that adjusts heating/cooling based on proven occupancy:
When participating in utility demand response programs, the verified energy reduction proof is automatically generated and submitted — the utility's settlement system can verify your load curtailment without a site inspection.
Vibration, temperature, and electrical current signatures from mechanical equipment reveal impending failures days or weeks in advance. A FidesInnova Service Contract running an anomaly detection model on these verified readings generates ZKP-proven maintenance alerts:
Each alert carries a ZKP proof of the sensor reading that triggered it. Maintenance contractors cannot dispute the triggering condition — it is cryptographically proven.
For regulated buildings (pharmaceutical labs, food processing, financial data centers), the FidesInnova blockchain provides a continuously growing, independently verifiable compliance record. Regulatory inspectors receive a blockchain explorer link — they verify temperature, humidity, and air quality records without accessing building systems or requiring a site visit.
Generate compliance reports directly from the Node dashboard: specify the time period and sensor types, and the system produces a PDF with embedded proof IDs that regulators can spot-check against the blockchain.
LEED, WELL, and BREEAM certifications require verified performance data. FidesInnova's ZKP-backed sensor records directly support:
Verified energy consumption data supports LEED EA credits for energy performance measurement and verification.
Continuous ZKP-verified PM2.5, CO₂, and TVOC records directly support WELL Air concept requirements.
Verified temperature and humidity records demonstrate continuous compliance with WELL thermal comfort standards across all occupied spaces.
Verified indoor environment quality data across lighting, air quality, thermal comfort, and acoustics supports BREEAM HEA credits.