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Sensor Networks For Aquaculture Monitoring Systems

2017Conference object Open access
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dc.contributor.authorBarros, F.M.
dc.contributor.authorMagalhães, Hugo
dc.contributor.authorMatos, Pedro
dc.contributor.authorNeves, Pedro
dc.contributor.authorFerreira, Carlos
dc.contributor.authorBaptista, Teresa
dc.contributor.authorRibeiro, Ana
dc.date.accessioned2023-10-03T11:04:56Z
dc.date.available2023-10-03T11:04:56Z
dc.date.issued2017
dc.description.abstractAquaculture is one of the fastest growing food producing sectors in the world, and its economic importance is increasing. Due to the increased demand for food, market pressure and growing concern about environmental and food quality issues, special techniques have been developed and applied to increase food production and improve product quality. Scientific advances in recent years in this sector have been facilitated largely by the application of science and the introduction of new technologies[1]. Emerging technologies in areas of sensor network, network computing and ubiquitous computing are enabling the development of practical and innovative solutions, improving monitoring and decision-making capabilities[2]. Innovations in water quality monitoring, fish feeding, biomass estimation, fish behavior monitoring, disease diagnosis and food waste management can not only improve the degree of automation of aquaculture and the level of scientific management, but also reduce the cost of production, improve environmental control and increase product quality[3]. Despite the great progress of science and technology, the optimization and management of production processes of aquaculture systems is facing great challenges[4]. The objectives of the present work are to review and analyze the currently scientific advances in technology applied in aquaculture systems, exploring the processes, architectures, the automation level and the role of sensors and new information technologies in this sector of activity.pt_PT
dc.description.sponsorshipResearch is supported by Portugal 2020 AQUATROPOLIS project. The “AQUATROPOLIS - Intelligent Management System for Sustainable Aquaculture” is an Incentive System for Research and Technological Development (SI I&DT) project in cooperation with the following entities: Compta - Emerging Business, S.A.; AlgaPlus - Production and Commercialization of Algae and its Derivatives Lda; Domatica - Global Solutions, S.A.; Polytechnic Institute of Leiria (IPL); Polytechnic Institute of Tomar (IPT) and Tagusvalley - Association for the Promotion and Development of the Tecnopolo Valley of the Tagus Valley. The main objective of the “Aquatropolis” project – Intelligent Management System for Sustainable Aquaculture – is to develop a disruptive solution for an intelligent, optimized and automated management of aquaculture operations, in order to promote the sustainable development of the Aquaculture industry in the countries of the Atlantic region.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.urihttp://hdl.handle.net/10400.26/46996
dc.language.isoengpt_PT
dc.titleSensor Networks For Aquaculture Monitoring Systemspt_PT
dc.typeconference object
dspace.entity.typePublication
oaire.citation.conferencePlacePorto, Portugalpt_PT
oaire.citation.startPage48pt_PT
oaire.citation.title2nd Aquaculture Research Workshoppt_PT
person.familyNameBarros
person.familyNameMatos
person.familyNameFerreira
person.givenNameManuel
person.givenNamePedro
person.givenNameCarlos Alberto Farinha
person.identifier.ciencia-id9B1F-422C-3A2B
person.identifier.ciencia-id261F-167D-09F6
person.identifier.ciencia-id621E-0FB1-CB55
person.identifier.orcid0000-0002-5891-1371
person.identifier.orcid0000-0002-2718-3279
person.identifier.orcid0000-0003-3948-2206
person.identifier.scopus-author-id35809734100
person.identifier.scopus-author-id57208757366
rcaap.rightsopenAccesspt_PT
rcaap.typeconferenceObjectpt_PT
relation.isAuthorOfPublicationd8559aa4-7a67-4357-9a01-cc3f2bd9e954
relation.isAuthorOfPublication14748744-5079-4d67-a9bd-7bb80f2e55ab
relation.isAuthorOfPublication0c77a86f-63c3-4fb0-892c-a9ea1f71d48d
relation.isAuthorOfPublication.latestForDiscoveryd8559aa4-7a67-4357-9a01-cc3f2bd9e954

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