Project description
Sensor encoding and interactions
Ultra-low power sensors incorporating artificial intelligence require an analog-to-digital converter (ADC) before the signal processing block implemented with a neural network (NN). ADCs have been employed based on a voltage-controlled oscillator (VCO) to implement integrated sensors. This requires the development of a new multiply–accumulate cell (MAC) for the first layer of the NN that operates with signals from the VCO as well as a suitable VCO interface with existing sensors. However, methods aiming to apply a sensor interaction using a VCO and implement a phase/frequency-encoded MAC unit for the NN have been attempted separately. The EU-funded TEVI project aims to combine the two for the benefit of research and industry applications. To that end, it will remove the ADC before the NN by directly connecting the sensor to it and encoding the sensor signals with a VCO.
Objective
The research of this EID focuses on ultra-low power sensors incorporating artificial intelligence. The current solution for such systems requires an analog-to-digital converter (ADC) prior to the signal processing block, usually implemented with a neural network (NN). The innovation consists of removing the ADC prior to the NN by directly coupling the sensor to it and encoding the sensor signals with a voltage-controlled-oscillator (VCO). VCO-based ADCs have been used to implement integrated sensors. Achieving this goal requires to develop a new multiply-accumulate cell (MAC) for the first layer of the NN that operates with signals from the VCO, and a suitable VCO interfaces with existing sensors. In most applications, the raw data form the sensor is required as well. Here, signals coming from the VCO can also be converted to a sampled sequence by enabling a digital decoder, which is not needed when detecting a pattern in the NN. As a benefit, power consumption can meet the requirements of battery-operated products. Power improvement comes from both the ADC removal and the power efficiency of the NN implementation. Approaches to implement a sensor interface using a VCO and to implement a phase/frequency-encoded MAC unit (P-MAC) for a NN have been attempted separately but, there is no combination of both ideas. The research in this EID tries to bridge this gap. This architecture can be useful for both research and industrial applications, such as neural probe chips, wearable electronics or battery powered IoT devices. This EID proposal requires intersectoral involvement of both academia and the industry, to develop a doctoral program and train researchers that will be in high demand by having the specific skills developed in this research. We have selected waterproof smart microphones as an application to benefit from this research, which may directly lead to a product development of interest to microelectronic industries in the EU producing MEMS microphones.
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.
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.
- natural sciences computer and information sciences internet internet of things
- engineering and technology electrical engineering, electronic engineering, information engineering electronic engineering sensors
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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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H2020-EU.1.3. - EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions
MAIN PROGRAMME
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H2020-EU.1.3.1. - Fostering new skills by means of excellent initial training of researchers
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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.
MSCA-ITN - Marie Skłodowska-Curie Innovative Training Networks (ITN)
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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) H2020-MSCA-ITN-2020
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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.
28903 Getafe (Madrid)
Spain
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.