IoT and LiDAR: making the twin live, not just accurate
A twin captured once a month is accurate for one day a month. Live sensor data is what keeps the other twenty nine days honest.
The first two posts in this series were about capture, getting a photoreal, accurate model of a building. That model, on its own, describes one moment. Buildings do not stay still, and a compliance record that only reflects the day of the last scan has an expiry date built into it whether anyone admits that or not.
What live data actually adds
Sensor data, temperature, occupancy, environmental readings, connected asset status, gets overlaid onto the exact physical location it relates to inside the twin, typically as a heatmap or a status indicator on the relevant surface or asset. Instead of a dashboard of numbers disconnected from the building, a Building Manager or technician sees a reading in the actual context of where it is coming from, next to the asset it is describing.
LiDAR tracking adds a spatial awareness layer on top, useful anywhere knowing where people or assets are within a space, in real time, matters, from occupancy driven space planning in an FM context to situational awareness on a secure site.
Why this is genuinely different from a BMS dashboard
Most buildings already have a building management system reporting sensor data somewhere. The gap is rarely the sensors, it is the disconnect between that data and an accurate spatial model of the building it is describing. Overlaying live data on a current, photoreal twin closes that gap directly, rather than asking a technician to mentally translate a dashboard reading into a physical location.
An honest caveat: this depends entirely on a building already having, or being willing to install, the relevant sensors. We integrate with existing IoT infrastructure where it exists. We are a spatial intelligence platform, not a sensor hardware manufacturer, and we are upfront about that distinction with every client.
Live data and capture fidelity both feed into another capability worth its own explanation, comparing two points in time to show exactly what changed. Read the next post.
See live data on a real twin
If your estate already has sensor infrastructure in place, we can show you what an integration with your existing IoT data would look like inside a twin.
See the product