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Stochastic Spiking Wireless Multimodal Sensory Systems

Source: EU Funding & Tenders Portal

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SWIMS vision is to propose a bio-inspired paradigm change for the design and hardware of future smart wireless multimodal sensory systems that will operate with stochastic spikes, offering a breakthrough with unrivalled energy efficiency at system level, for event detections and communication. The scientific breakthroughs proposed here are sine qua non advancements for a sustainable deployment of

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The project "Stochastic Spiking Wireless Multimodal Sensory Systems" is an infrastructure initiative in the Chemical (Industrial), Broadband, Metal, Advanced Electronics, Manufacturing (Industrial), Telecommunications, Government sector, located in N/A, Germany. Taiyo aggregates data from EU Funding & Tenders Portal, including information on sponsoring government bodies, EPCs, and contractors.

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Description

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SWIMS vision is to propose a bio-inspired paradigm change for the design and hardware of future smart wireless multimodal sensory systems that will operate with stochastic spikes, offering a breakthrough with unrivalled energy efficiency at system level, for event detections and communication. The scientific breakthroughs proposed here are sine qua non advancements for a sustainable deployment of billions of future Internet of Things nodes to support smart economy and society development, with large energy savings and limited impact on environment. The synergistic interaction of four complementary skilled PIs enables the realization of a radically-novel end-to-end stochastic analog spiking neuromorphic concept for SWIMS nodes, offering solutions to challenges of sensor spiking signal generation, processing and communication with disruptive innovations at all levels, inspired by the biological model of a small insect. SWIMS involves many beyond state-of-the-art scientific advancements from technology to system level to enable a neuromorphic architecture with i) as input neuron layer, new heterostructure spiking sensor arrays based on transition metal oxides/2D semiconductor, covering infrared, ultraviolet, acoustic and electromagnetic detections, ii) hidden layers in tiny spiking neural networks based on novel CMOS Fe-FET concepts capable of efficiently dealing with inherent stochastic noise when processing spiking signals on-chip, iii) a spiking emitter as output layer for event-driven wireless transmission using optimized spike modulation and encoding, and iv) a modelling framework embedding stochastic effects in task-based electronic system design and biologically inspired recurrent neural networks. The synergistic interaction will enable unique design and experimental validations of first of their kind event-driven demonstrators with optimized all spiking multi-modal sensor nodes and energy consumption more than 100x lower than existing state of the art.

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