Descrizione del progetto
Condurre al margine l’elaborazione visiva di ispirazione biologica
Il traffico dei dati di Internet si sta espandendo in maniera esponenziale. La sempre più capillare introduzione di reti 5G e la connettività dei dispositivi al margine della rete, dai prodotti di consumo alle automobili fino ai robot di fabbrica, stanno trainando la grande domanda per un edge computing a bassa potenza e ad alte prestazioni. Nel prossimo futuro, molti dei dispositivi collegati al margine si baseranno sul rilevamento ambientale, osservando e adeguandosi ai cambiamenti, sia che si tratti di un’auto a guida autonoma che di un robot di fabbrica che si sposta in un magazzino affollato. Il progetto MISEL, finanziato dall’UE, svilupperà un sistema di sensori neuromorfici a bassa potenza dotato di elaborazione neuromorfica integrata per l’imitazione del sistema visivo umano a partire dal livello cellulare fino alle regioni cerebrali e all’elaborazione di sistemi interconnessi. Il successo del progetto ispirerà e permetterà l’innovazione al margine.
Obiettivo
"MISEL aims at bringing artificial intelligence to the edge computing (decisions made on-device) through a low-power bio-inspired vision system with multi-spectral sensing and in sensor spatio-temporal neuromorphic processing based on complex events. The science-to-technology breakthrough is the heterogeneous integration of a neuromorphic computing scheme featuring three different abstraction levels (cellular, cerebellar and cortex processors) with high-density memory arrays and adaptive photodetector technology for fast operation and energy efficiency. The context-aware, low power and distributed computation paradigm supported by MISEL is promising alternative to the current approach relying on massive-data transfers and large computational resources, e.g. workstations or cloud servers. This answers to the challenges and related scope presented in the Work Programme towards ""more complex, brain mimicking low power systems"" ""exploiting a wider range of biological principles from the hardware level up"" by introducing the human eye like adaptivity with cellular processor and the data fusion, learning, reasoning, and “conscious” decisions performed by the cortex.
The stand-alone system fabricated in MISEL will be tested on timely and challenging applications such as distinguishing birds from drones through their spatio-temporal flying signature, and scene anomaly detection from a mobile platform. From the technology development and industrialization point of view, MISEL includes the whole value chain: materials research for back-end of line (BEOL) processing-compatible densely-packed ferroelectric non-volatile memories (FeRAMs) and intensity adaptive photodetectors, novel neuromorphic computing algorithms and circuit implementations, and system level benchmarking. This is all in line with the challenge and scope of ""outperforming conventional SoA with relevant metric"" and benchmarking ""challenging end-to-end scenarios of use"" for industrial adaptation.
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Campo scientifico
- natural sciencescomputer and information sciencesartificial intelligence
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringsensorsoptical sensors
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringroboticsautonomous robotsdrones
Programma(i)
Invito a presentare proposte
Vedi altri progetti per questo bandoBando secondario
H2020-FETPROACT-2020-01
Meccanismo di finanziamento
RIA - Research and Innovation actionCoordinatore
02150 Espoo
Finlandia