Descripción del proyecto
Llevar el procesamiento visual bioinspirado hasta la periferia
El tráfico de datos en internet ha crecido exponencialmente. El despliegue cada vez más expansivo de las redes 5G y la conectividad de los dispositivos en la periferia de la red, desde productos de consumo y vehículos hasta robots industriales, están impulsando una demanda importante de una computación en la periferia de alto rendimiento y bajo consumo de energía. En un futuro próximo, la mayoría de los dispositivos conectados en la periferia dependerán de la detección de su entorno, observarán y se ajustarán a los cambios, ya sea un vehículo autónomo o un robot industrial desplazándose a través de un almacén abarrotado. El proyecto MISEL, financiado con fondos europeos, desarrollará un sistema de detección neuromórfica de bajo consumo de energía con procesamiento neuromórfico integrado para reproducir el sistema visual humano desde el nivel celular hasta las regiones cerebrales y el procesamiento de sistemas interconectados. Su éxito inspirará y permitirá la consecución de innovaciones en la periferia.
Objetivo
"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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Ámbito científico
- 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
Palabras clave
Programa(s)
Convocatoria de propuestas
Consulte otros proyectos de esta convocatoriaConvocatoria de subcontratación
H2020-FETPROACT-2020-01
Régimen de financiación
RIA - Research and Innovation actionCoordinador
02150 Espoo
Finlandia