Repository logo
 
Publication

Intelligent monitoring and management platform for the prevention of olive pests and diseases, including IoT with sensing, georeferencing and image acquisition capabilities through computer vision

2022Conference object Open access
Simple item page
dc.contributor.authorAlves, Adília
dc.contributor.authorMorais, A. Jorge
dc.contributor.authorFilipe, Vitor
dc.contributor.authorPereira, J.A.
dc.date.accessioned2021-10-29T10:52:46Z
dc.date.available2021-10-29T10:52:46Z
dc.date.issued2022
dc.description.abstractClimate change affects global temperature and precipitation patterns. These effects, in turn, influence the intensity and, in some cases, the frequency of extreme environmental events, such as forest fires, hurricanes, heat waves, floods, droughts, and storms. In general, these events can be particularly conducive to the appearance of plant pests and diseases. The availability of models and a data collection system is crucial to manage pests and diseases in sustainable agricul-tural ecosystems. Agricultural ecosystems are known to be complex, multivariable, and unpredict-able. It is important to anticipate crop pests and diseases in order to improve its control in a more ecological and economical way (e.g., precision in the use of pesticides). The development of an intel-ligent monitoring and management platform for the prevention of pests and diseases in olive groves at Trás-os- Montes region will be very beneficial. This platform must: a) integrate data from multi-ple data sources such as sensory data (e.g., temperature), biological observations (e.g., insect counts), georeferenced data (e.g., altitude) or digital images (e.g., plant images); b) systematize these data into a regional repository; c) provide relevant forecasts for pest and diseases. Convolutional Neural Networks (CNNs) can be a valuable tool for the identification and classi-fication of images acquired by Internet of Things (IoT).pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationAlves, Adília; Morais, A. Jorge; Filipe, Vitor; Pereira, J.A. (2022). Intelligent monitoring and management platform for the prevention of olive pests and diseases, including IoT with sensing, georeferencing and image acquisition capabilities through computer vision. In 18th International Symposium on Distributed Computing and Artificial Intelligence. Salamanca. vol. 2, p. 1-4. ISBN 978-303086886-4pt_PT
dc.identifier.doi10.1007/978-3-030-86887-1_23pt_PT
dc.identifier.issn978-303086886-4
dc.identifier.urihttp://hdl.handle.net/10198/24139
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherSpringerpt_PT
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectOlives sustainable productionpt_PT
dc.subjectInternet of thingspt_PT
dc.subjectConvolutional neural networkpt_PT
dc.subjectDeep learningpt_PT
dc.subjectComputer visionpt_PT
dc.titleIntelligent monitoring and management platform for the prevention of olive pests and diseases, including IoT with sensing, georeferencing and image acquisition capabilities through computer visionpt_PT
dc.typeconference object
dspace.entity.typePublication
oaire.citation.title18th International Symposium on Distributed Computing and Artificial Intelligencept_PT
person.familyNameAlves
person.familyNamePereira
person.givenNameAdília
person.givenNameJosé Alberto
person.identifier.ciencia-id0019-58CC-96C9
person.identifier.ciencia-id611F-80B2-A7C1
person.identifier.orcid0000-0002-3792-1968
person.identifier.orcid0000-0002-2260-0600
person.identifier.ridL-6798-2014
person.identifier.scopus-author-id57204366348
rcaap.rightsopenAccesspt_PT
rcaap.typeconferenceObjectpt_PT
relation.isAuthorOfPublicationf85c13a5-8370-4647-971d-00b44123739c
relation.isAuthorOfPublication7932162e-a2da-4913-b00d-17babbe51857
relation.isAuthorOfPublication.latestForDiscoveryf85c13a5-8370-4647-971d-00b44123739c

Files

Original bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
Intelligent Monitoring and Management Platform for the Prevention of Olive Pests and Diseases.pdf
Size:
228.36 KB
Format:
Adobe Portable Document Format
Download

Collections

CIMO - Publicações em Proceedings Indexadas à WoS/Scopus