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Q‑EDGE BUILDINGS

Edge AI for Intelligent Buildings

Edge AI and edge-cloud architectures that analyse energy and operational data close to the source to support building optimization.

Abstract wireframe building with glowing edge nodes on each floor sending pulses to a cloud layer
Illustrative visual
IndustryEnergy & Smart Buildings
StatusR&D · In development
Core technologyEdge AI · Edge-cloud orchestration
ContextLE2C ecosystem

Edge AI for Intelligent Buildings.

Q-EDGE BUILDINGS develops Edge AI and edge-cloud architectures for intelligent buildings. Data is analysed close to where it is generated, enabling energy forecasting, anomaly detection and operational optimization with lower latency and less data movement.

Building data is high-volume and time-sensitive, and sending everything to the cloud is slow and costly.

The challenge

  • Buildings generate continuous streams of energy and operational data.
  • Cloud-only processing adds latency, bandwidth cost and privacy exposure.
  • Optimization requires reliable forecasting at room, floor and building level.

Our approach

  • Edge inference on devices and gateways close to the sensors.
  • Edge-cloud orchestration for training, updates and aggregation.
  • Forecasting and anomaly detection to support energy optimization.

Built on our core technology pillars.

Edge AIEdge-cloud orchestrationTime-series forecastingIoT dataEnergy analytics

How we approach each technology

Where Q-EDGE BUILDINGS applies.

Energy forecasting

Anticipating consumption to plan and optimise usage.

Anomaly detection

Spotting faults and waste in real time, close to the source.

Operational optimization

Supporting facility teams with actionable insights.

Where we are today.

01 · currentR&D
02Prototype
03Pilot
04Product
EcosystemConnected to the LE2C – Lombardy Energy Cleantech Cluster ecosystem
KPIsEnergy and latency KPIs are design targets until validated in the field

What we are designing for.

Inference at the edge

Decisions made close to the sensors.

Energy optimization

Better forecasting to reduce waste.

Less data movement

Only relevant information sent to the cloud.

Design targets — not achieved results. Metrics will be published only after validation.

What comes next.

  1. Edge reference stackHardware/software stack for edge inference.
  2. Field testValidation on a real building environment.
  3. PilotPilot with energy and real-estate partners.

Let’s explore Q-EDGE BUILDINGS together.

Let’s turn advanced research into deployable intelligence. Tell us about your challenge — a partnership, a pilot or a request for our company presentation.

Partnerships & pilotsinfo@qubitale.com
HeadquartersVia B. Quaranta 45, 20139 Milano, Italy
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