Smart Building Sensitive to Daily Sentiment
Acronym
SUSTAIN
Description of the granted funding
Buildings are evolving into smart organisms through their unmatched concentration of distributed sensing, actuation and intelligence. Indeed, the regulatory decree 2010/31/EU (European Parliament) requires building automation control systems in tertiary buildings by 2025. Still, despite massively deployed sensors of all kind, instead of actual awareness, nowadays at most unconscious processing (C0) is reached.
SUST(AI)N derives theoretical & experimental underpinnings to combine novel distributed intelligence, unpre-cedented sensing accuracy, and reconfigurable hardware in a smart building context into a conscious organism that achieves self-awareness through probabilistic reasoning across its connected sustainable devices. SUST(AI)N constitutes the first concentrated effort to explore novel advances in distributed intelligence, reconfigurable hardware, and environmental sensing to establish awareness for smart buildings that reaches global availability of information (C11; through data aggregation across connected reconfigurable hardware), and self-monitoring (C21; via distributed probabilistic intelligence and the sensing of group sentiment). We simplify intelligent building hardware and systems by exploiting electromagnetic signals jointly for backscatter communication, energy harvesting, physical-layer computation offloading, and non-intrusive sensing. Reconfigurable intelligent surfaces are used to support each of these functions.
SUST(AI)N achieves awareness along three high-risk, complementary paths:
1: Reconfigurable intelligent circuits: fit to awareness need by post-installation hardware adaptation
2: Distributed, self-organizing global intelligence: awareness through probabilistic reasoning
3: Unprecedented self-awareness through ubiquitous radio sensing: group-sentiment recognition
It achieves sustainability via demand-tailored adaptive hardware, energy and data-efficient AI,non-intrusive RF-sensing, energy harvesting, multi-party encryption.
Show moreStarting year
2022
End year
2026
Granted funding
YILDIZ TECHNICAL UNIVERSITY (TR)
339 563.75 €
Participant
UNIVERSITA DEGLI STUDI DI TRENTO (IT)
453 382.25 €
Participant
INSTITUT MINES-TELECOM (FR)
591 060 €
Participant
UNIVERSITAT POLITECNICA DE CATALUNYA (ES)
499 480 €
Participant
Amount granted
2 550 196 €
Funder
European Union
Funding instrument
HORIZON EIC Grants
Framework programme
Horizon Europe (HORIZON)
Call
Programme part
The European Innovation Council (EIC) (11739Topic
Awareness Inside (HORIZON-EIC-2021-PATHFINDERCHALLENGES-01-01Call ID
HORIZON-EIC-2021-PATHFINDERCHALLENGES-01 Other information
Funding decision number
101071179
Identified topics
artificial intelligence, machine learning