AI-supported transformation of the urban infrastructure
summary
Holistic control stacks combine model predictive control with ML forecasts for zones, HVAC and microgrids, running as modular software modules that coordinate price signals, PV and storage; a building deployment runs since 2018 and pilot results across eight sites in five countries report 4–30% energy savings depending on controllable assets. Water demand and uncertainty models run in Spain, Czech Republic and Portugal; rail braking energy reuse shows large theoretical savings in a case study but remains unpiloted; growth chambers produce fast crop data for yield and pest models.
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chapters (10)
- 0:00Start
- 1:38LARES - Laboratory for Renewable Energy Systems
- 12:39Meteorological forecasts correction
- 15:00Smart railway transport system
- 16:04Urban traffic travel times
- 17:12Smart city lighting
- 18:32Water demand predictions
- 19:07Prediction system breakdown
- 20:07Water use disaggregation
- 21:15Smart water distribution system
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