Skip to main content

Very Efficient Deep Learning in IOT

Objective

The ever increasing performance of computer systems in general and IoT systems, in particular, delivers the capability to solve increasingly challenging problems, pushing automation to improve the quality of our life. This triggers the need for a next-generation IoT architecture, satisfying the demand for key sectors like transportation (e.g. self-driving cars), industry (e.g. robotization or predictive maintenance), and our homes (e.g. assisted living). Such applications require building systems of enormous complexity, so that traditional approaches start to fail. The amount of data collected and processed is huge, the computational power required is very high, and the algorithms are too complex allowing for the computation of solutions within the tight time constraints. In addition, security, privacy, or robustness for such systems becomes a critical challenge.
An enabler that aims at delivering the required keystone is VEDLIoT, a Very Efficient Deep Learning IoT platform. Instead of traditional algorithms, artificial intelligence (AI) and deep learning (DL) are used to handle the large complexity. Due to the distributed approach, VEDLIoT allows dividing the application into smaller and more efficient components and work together in large collaborative systems in the Internet of Things (IoT), enabling AI-based algorithms that are distributed over IoT devices from edge to cloud.
In terms of hardware, VEDLIoT offers a platform, the Cognitive IoT platform, leveraging European technology, which can be easily configured to be placed at any level of the compute continuum starting from the sensor nodes and then edge to cloud. Driven by use cases in the key sectors of automotive, industrial, and smart homes, the platform is supported by cross-cutting aspects satisfying security and robustness. Overall, VEDLIoT offers a framework for the Next Generation Internet based on IoT devices required for collaboratively solving complex DL applications across a distributed system.

Field of science

  • /engineering and technology/civil engineering/architecture engineering/home automation
  • /natural sciences/computer and information sciences/internet
  • /natural sciences/computer and information sciences/artificial intelligence/machine learning/deep learning

Call for proposal

H2020-ICT-2020-1
See other projects for this call

Funding Scheme

RIA - Research and Innovation action

Coordinator

UNIVERSITAET BIELEFELD
Address
Universitaetsstrasse 25
33615 Bielefeld
Germany
Activity type
Higher or Secondary Education Establishments
EU contribution
€ 1 899 000

Participants (11)

EMBEDL AB
Sweden
EU contribution
€ 725 750
Address
Massans Gata 10
402 24 Gothenburg
Activity type
Private for-profit entities (excluding Higher or Secondary Education Establishments)
CHALMERS TEKNISKA HOEGSKOLA AB
Sweden
EU contribution
€ 568 125
Address
-
41296 Goeteborg
Activity type
Higher or Secondary Education Establishments
SIEMENS AKTIENGESELLSCHAFT
Germany
EU contribution
€ 691 832,50
Address
Werner-von-siemens-str. 1
80333 Munchen
Activity type
Private for-profit entities (excluding Higher or Secondary Education Establishments)
CHRISTMANN INFORMATIONSTECHNIK + MEDIEN GMBH & CO KG
Germany
EU contribution
€ 925 375
Address
Ilseder Hutte 10
31241 Ilsede
Activity type
Private for-profit entities (excluding Higher or Secondary Education Establishments)
UNIVERSITE DE NEUCHATEL
Switzerland
EU contribution
€ 540 250
Address
Faubourg De L'hopital 41
2000 Neuchatel
Activity type
Higher or Secondary Education Establishments
UNIVERSITAET OSNABRUECK
Germany
EU contribution
€ 327 250
Address
Neuer Graben/schloss 29
49074 Osnabrueck
Activity type
Higher or Secondary Education Establishments
VEONEER SWEDEN AB
Sweden
EU contribution
€ 359 500
Address
Wallentinsvagen 22
447 37 Vargarda
Activity type
Private for-profit entities (excluding Higher or Secondary Education Establishments)
GOETEBORGS UNIVERSITET
Sweden
EU contribution
€ 354 250
Address
Vasaparken
405 30 Goeteborg
Activity type
Higher or Secondary Education Establishments
RISE RESEARCH INSTITUTES OF SWEDEN AB
Sweden
EU contribution
€ 589 718,75
Address
Brinellgatan 4
501 15 Boras
Activity type
Research Organisations
FCIENCIAS.ID - ASSOCIACAO PARA A INVESTIGACAO E DESENVOLVIMENTO DE CIENCIAS
Portugal
EU contribution
€ 370 345
Address
Campo Grande, Edificio C1, Piso 3
1749 016 Lisbon
Activity type
Research Organisations
ANTMICRO SP ZOO
Poland
EU contribution
€ 645 250
Address
Ul Zwierzyniecka 3
60 813 Poznan
Activity type
Private for-profit entities (excluding Higher or Secondary Education Establishments)