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Sensors 2017, 17(5), 1173; doi:10.3390/s17051173

Eyes of Things

1
VISILAB, University of Castilla-La Mancha, E.T.S.I.Industriales, Avda Camilo Jose Cela s/n, Ciudad Real 13071, Spain
2
Movidius, 1st Floor, O’Connell Bridge House, D’Olier Street, Dublin 2, Ireland
3
DFKI, Augmented Vision Research Group, Tripstaddterstr. 122, 67663 Kaiserslautern, Germany
4
Awaiba, Madeira Tecnopolo, 9020-105 Funchal, Portugal
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nViso SA, PSE-D, Site EPFL, CH-1015 Lausanne, Switzerland
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THALES Communications & Security, 4 Avenue des Louvresses, 92230 Gennevilliers, France
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Evercam, 6-7 Granby Row, Dublin 1, D01 FW20, Ireland
8
Fluxguide, Burggasse 7-9/9, 1070 Vienna, Austria
*
Author to whom correspondence should be addressed.
Academic Editors: Luca Roselli, Federico Alimenti and Stefania Bonafoni
Received: 30 March 2017 / Revised: 4 May 2017 / Accepted: 17 May 2017 / Published: 21 May 2017
(This article belongs to the Special Issue New Generation Sensors Enabling and Fostering IoT)

Abstract

Embedded systems control and monitor a great deal of our reality. While some “classic” features are intrinsically necessary, such as low power consumption, rugged operating ranges, fast response and low cost, these systems have evolved in the last few years to emphasize connectivity functions, thus contributing to the Internet of Things paradigm. A myriad of sensing/computing devices are being attached to everyday objects, each able to send and receive data and to act as a unique node in the Internet. Apart from the obvious necessity to process at least some data at the edge (to increase security and reduce power consumption and latency), a major breakthrough will arguably come when such devices are endowed with some level of autonomous “intelligence”. Intelligent computing aims to solve problems for which no efficient exact algorithm can exist or for which we cannot conceive an exact algorithm. Central to such intelligence is Computer Vision (CV), i.e., extracting meaning from images and video. While not everything needs CV, visual information is the richest source of information about the real world: people, places and things. The possibilities of embedded CV are endless if we consider new applications and technologies, such as deep learning, drones, home robotics, intelligent surveillance, intelligent toys, wearable cameras, etc. This paper describes the Eyes of Things (EoT) platform, a versatile computer vision platform tackling those challenges and opportunities. View Full-Text
Keywords: embedded computer vision; eyes of things; Internet of Things; computer vision embedded computer vision; eyes of things; Internet of Things; computer vision
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Deniz, O.; Vallez, N.; Espinosa-Aranda, J.L.; Rico-Saavedra, J.M.; Parra-Patino, J.; Bueno, G.; Moloney, D.; Dehghani, A.; Dunne, A.; Pagani, A.; Krauss, S.; Reiser, R.; Waeny, M.; Sorci, M.; Llewellynn, T.; Fedorczak, C.; Larmoire, T.; Herbst, M.; Seirafi, A.; Seirafi, K. Eyes of Things. Sensors 2017, 17, 1173.

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