Project description
Edge computing inspired by neuroscience is ultra energy-efficient and secure
The global network of internet-connected devices is expanding exponentially. Endpoint devices at the "edge" of the IoT network are increasingly requested to perform advanced sensing and processing, in particular AI inference, to extract valuable information from their environments and eliminate the need to transfer vast amounts of raw data to cloud servers. This is important in many consumer applications to improve user satisfaction, as well as in safety-critical applications such as self-driving cars. Enhanced sensing and processing at the "edge" reduces latencies and data degradation while enhancing security and efficiency over the entire IoT network. The EU-funded NimbleAI project will create an integral neuromorphic sensing–processing architecture to efficiently run accurate and diverse computer vision algorithms in resource- and area-constrained chips destined for endpoint devices.
Objective
Today only very light AI processing tasks are executed in ubiquitous IoT endpoint devices, where sensor data are generated and access to energy is usually constrained. However, this approach is not scalable and results in high penalties in terms of security, privacy, cost, energy consumption, and latency as data need to travel from endpoint devices to remote processing systems such as data centres. Inefficiencies are especially evident in energy consumption.
To keep up pace with the exponentially growing amount of data (e.g. video) and allow more advanced, accurate, safe and timely interactions with the surrounding environment, next-generation endpoint devices will need to run AI algorithms (e.g. computer vision) and other compute intense tasks with very low latency (i.e. units of ms or less) and energy envelops (i.e. tens of mW or less).
NimbleAI will harness the latest advances in microelectronics and integrated circuit technology to create an integral neuromorphic sensing-processing solution to efficiently run accurate and diverse computer vision algorithms in resource- and area-constrained chips destined to endpoint devices. Biology will be a major source of inspiration in NimbleAI, especially with a focus to reproduce adaptivity and experience-induced plasticity that allow biological structures to continuously become more efficient in processing dynamic visual stimuli.
NimbleAI is expected to allow significant improvements compared to state-of-the-art (e.g. commercially available neuromorphic chips), and at least 100x improvement in energy efficiency and 50x shorter latency compared to state-of-the-practice (e.g. CPU/GPU/NPU/TPUs processing frame-based video). NimbleAI will also take a holistic approach for ensuring safety and security at different architecture levels, including silicon level.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
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CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
This project's classification has been validated by the project's team.
- natural sciences computer and information sciences internet internet of things
- natural sciences computer and information sciences artificial intelligence computer vision
- engineering and technology electrical engineering, electronic engineering, information engineering electronic engineering sensors
- natural sciences physical sciences electromagnetism and electronics microelectronics
Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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HORIZON.2.4 - Digital, Industry and Space
MAIN PROGRAMME
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HORIZON.2.4.2 - Key Digital Technologies
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Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
HORIZON-RIA - HORIZON Research and Innovation Actions
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) HORIZON-CL4-2021-DIGITAL-EMERGING-01
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Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
20500 MONDRAGON
Spain
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Participants (17)
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08034 BARCELONA
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06560 Valbonne
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2311 EZ Leiden
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602 00 BRNO
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1016DP AMSTERDAM
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28006 MADRID
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46022 VALENCIA
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00197 Roma Rm
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20133 Milano
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75015 PARIS 15
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3001 Leuven
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24118 Kiel
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8020 Graz
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20560 Onati
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1010 WIEN
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1040 Wien
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5656 AE Eindhoven
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Partners (3)
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M13 9PL Manchester
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E1 4NS London
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Participation ended
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5612 AE Eindhoven
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