A Wireless Sensor Network for Vineyard Monitoring That Uses Image Processing

The first step to detect when a vineyard has any type of deficiency, pest or disease is to observe its stems, its grapes and/or its leaves. To place a sensor in each leaf of every vineyard is obviously not feasible in terms of cost and deployment. We should thus look for new methods to detect these...

Full description

Bibliographic Details
Main Authors:	Lloret, Jaime, Bosch, Ignacio, Sendra, Sandra, Serrano, Arturo
Format:	Online
Language:	English
Published:	Molecular Diversity Preservation International (MDPI) 2011
Online Access:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3231437/

id	pubmed-3231437
recordtype	oai_dc
spelling	pubmed-32314372011-12-07 A Wireless Sensor Network for Vineyard Monitoring That Uses Image Processing Lloret, Jaime Bosch, Ignacio Sendra, Sandra Serrano, Arturo Article The first step to detect when a vineyard has any type of deficiency, pest or disease is to observe its stems, its grapes and/or its leaves. To place a sensor in each leaf of every vineyard is obviously not feasible in terms of cost and deployment. We should thus look for new methods to detect these symptoms precisely and economically. In this paper, we present a wireless sensor network where each sensor node takes images from the field and internally uses image processing techniques to detect any unusual status in the leaves. This symptom could be caused by a deficiency, pest, disease or other harmful agent. When it is detected, the sensor node sends a message to a sink node through the wireless sensor network in order to notify the problem to the farmer. The wireless sensor uses the IEEE 802.11 a/b/g/n standard, which allows connections from large distances in open air. This paper describes the wireless sensor network design, the wireless sensor deployment, how the node processes the images in order to monitor the vineyard, and the sensor network traffic obtained from a test bed performed in a flat vineyard in Spain. Although the system is not able to distinguish between deficiency, pest, disease or other harmful agents, a symptoms image database and a neuronal network could be added in order learn from the experience and provide an accurate problem diagnosis. Molecular Diversity Preservation International (MDPI) 2011-06-07 /pmc/articles/PMC3231437/ /pubmed/22163948 http://dx.doi.org/10.3390/s110606165 Text en © 2011 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 license (http://creativecommons.org/licenses/by/3.0/).
repository_type	Open Access Journal
institution_category	Foreign Institution
institution	US National Center for Biotechnology Information
building	NCBI PubMed
collection	Online Access
language	English
format	Online
author	Lloret, Jaime Bosch, Ignacio Sendra, Sandra Serrano, Arturo
spellingShingle	Lloret, Jaime Bosch, Ignacio Sendra, Sandra Serrano, Arturo A Wireless Sensor Network for Vineyard Monitoring That Uses Image Processing
author_facet	Lloret, Jaime Bosch, Ignacio Sendra, Sandra Serrano, Arturo
author_sort	Lloret, Jaime
title	A Wireless Sensor Network for Vineyard Monitoring That Uses Image Processing
title_short	A Wireless Sensor Network for Vineyard Monitoring That Uses Image Processing
title_full	A Wireless Sensor Network for Vineyard Monitoring That Uses Image Processing
title_fullStr	A Wireless Sensor Network for Vineyard Monitoring That Uses Image Processing
title_full_unstemmed	A Wireless Sensor Network for Vineyard Monitoring That Uses Image Processing
title_sort	wireless sensor network for vineyard monitoring that uses image processing
description	The first step to detect when a vineyard has any type of deficiency, pest or disease is to observe its stems, its grapes and/or its leaves. To place a sensor in each leaf of every vineyard is obviously not feasible in terms of cost and deployment. We should thus look for new methods to detect these symptoms precisely and economically. In this paper, we present a wireless sensor network where each sensor node takes images from the field and internally uses image processing techniques to detect any unusual status in the leaves. This symptom could be caused by a deficiency, pest, disease or other harmful agent. When it is detected, the sensor node sends a message to a sink node through the wireless sensor network in order to notify the problem to the farmer. The wireless sensor uses the IEEE 802.11 a/b/g/n standard, which allows connections from large distances in open air. This paper describes the wireless sensor network design, the wireless sensor deployment, how the node processes the images in order to monitor the vineyard, and the sensor network traffic obtained from a test bed performed in a flat vineyard in Spain. Although the system is not able to distinguish between deficiency, pest, disease or other harmful agents, a symptoms image database and a neuronal network could be added in order learn from the experience and provide an accurate problem diagnosis.
publisher	Molecular Diversity Preservation International (MDPI)
publishDate	2011
url	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3231437/
_version_	1611492198732267520

A Wireless Sensor Network for Vineyard Monitoring That Uses Image Processing

Similar Items