Eyes of Things
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...
Autores principales: | , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5470918/ https://www.ncbi.nlm.nih.gov/pubmed/28531141 http://dx.doi.org/10.3390/s17051173 |
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author | Deniz, Oscar Vallez, Noelia Espinosa-Aranda, Jose L. Rico-Saavedra, Jose M. Parra-Patino, Javier Bueno, Gloria Moloney, David Dehghani, Alireza Dunne, Aubrey Pagani, Alain Krauss, Stephan Reiser, Ruben Waeny, Martin Sorci, Matteo Llewellynn, Tim Fedorczak, Christian Larmoire, Thierry Herbst, Marco Seirafi, Andre Seirafi, Kasra |
author_facet | Deniz, Oscar Vallez, Noelia Espinosa-Aranda, Jose L. Rico-Saavedra, Jose M. Parra-Patino, Javier Bueno, Gloria Moloney, David Dehghani, Alireza Dunne, Aubrey Pagani, Alain Krauss, Stephan Reiser, Ruben Waeny, Martin Sorci, Matteo Llewellynn, Tim Fedorczak, Christian Larmoire, Thierry Herbst, Marco Seirafi, Andre Seirafi, Kasra |
author_sort | Deniz, Oscar |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-5470918 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-54709182017-06-16 Eyes of Things Deniz, Oscar Vallez, Noelia Espinosa-Aranda, Jose L. Rico-Saavedra, Jose M. Parra-Patino, Javier Bueno, Gloria Moloney, David Dehghani, Alireza Dunne, Aubrey Pagani, Alain Krauss, Stephan Reiser, Ruben Waeny, Martin Sorci, Matteo Llewellynn, Tim Fedorczak, Christian Larmoire, Thierry Herbst, Marco Seirafi, Andre Seirafi, Kasra Sensors (Basel) Article 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. MDPI 2017-05-21 /pmc/articles/PMC5470918/ /pubmed/28531141 http://dx.doi.org/10.3390/s17051173 Text en © 2017 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Deniz, Oscar Vallez, Noelia Espinosa-Aranda, Jose L. Rico-Saavedra, Jose M. Parra-Patino, Javier Bueno, Gloria Moloney, David Dehghani, Alireza Dunne, Aubrey Pagani, Alain Krauss, Stephan Reiser, Ruben Waeny, Martin Sorci, Matteo Llewellynn, Tim Fedorczak, Christian Larmoire, Thierry Herbst, Marco Seirafi, Andre Seirafi, Kasra Eyes of Things |
title | Eyes of Things |
title_full | Eyes of Things |
title_fullStr | Eyes of Things |
title_full_unstemmed | Eyes of Things |
title_short | Eyes of Things |
title_sort | eyes of things |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5470918/ https://www.ncbi.nlm.nih.gov/pubmed/28531141 http://dx.doi.org/10.3390/s17051173 |
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