Low-Cost Underwater Camera: Design and Development
The understanding of vision-based data acquisition and processing aids in developing predictive frameworks and decision support systems for efficient aquaculture monitoring and management. However, this emerging field is confronted by a lack of high-quality underwater visual data, whether from publi...
Gespeichert in:
Veröffentlicht in: | Journal of advanced computational intelligence and intelligent informatics 2022-09, Vol.26 (5), p.851-858 |
---|---|
Hauptverfasser: | , , , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | 858 |
---|---|
container_issue | 5 |
container_start_page | 851 |
container_title | Journal of advanced computational intelligence and intelligent informatics |
container_volume | 26 |
creator | Dadios, Elmer P. Almero, Vincent Jan II, Ronnie S. Concepcion Vicerra, Ryan Rhay P. Bandala, Argel A. Sybingco, Edwin |
description | The understanding of vision-based data acquisition and processing aids in developing predictive frameworks and decision support systems for efficient aquaculture monitoring and management. However, this emerging field is confronted by a lack of high-quality underwater visual data, whether from public or local setups and high cost of development. In this regard, an underwater camera that captures underwater images from an inland freshwater aquaculture setup was proposed. The components of the underwater camera system are primarily based on Raspberry Pi, an open-source computing platform. The underwater camera continuously provides a real-time video streaming link of underwater scenes, and the local processor periodically acquires and stores data from this link in the form of images. These data are stored locally and remotely. Based on the results of the developed low-cost underwater camera, it captures and differentiate fish region to its background before and after flushing as influenced by turbidity. Hence, the developed camera can be used for both aquarium and inland aquaculture pond setup for fish monitoring. |
doi_str_mv | 10.20965/jaciii.2022.p0851 |
format | Article |
fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_2715435647</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2715435647</sourcerecordid><originalsourceid>FETCH-LOGICAL-c399t-fe16443035754541ee2d34bb4e22419adb3cf885c77d3a0c092c3e5437c5ba753</originalsourceid><addsrcrecordid>eNotkE1LxDAQQIMouKz7BzwVPHedZJKm9SZVV2HBi3sOaTqVLtsPk66L_9649TRv4DEDj7FbDmsBRabu99a1bRsXIdYj5IpfsAXPc0xz4PIyMkpMgSNcs1UIe4DIIgPJF0xsh1NaDmFKdn1N_mQn8klpO_L2IXmi0H72ie3riN90GMaO-umGXTX2EGj1P5ds9_L8Ub6m2_fNW_m4TR0WxZQ2xDMpEVBpJZXkRKJGWVWShJC8sHWFrslz5bSu0YKDQjgkJVE7VVmtcMnu5rujH76OFCazH46-jy-N0DyKKpM6WmK2nB9C8NSY0bed9T-GgznnMXMe85fHnPPgL1UqV6c</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2715435647</pqid></control><display><type>article</type><title>Low-Cost Underwater Camera: Design and Development</title><source>DOAJ Directory of Open Access Journals</source><creator>Dadios, Elmer P. ; Almero, Vincent Jan ; II, Ronnie S. Concepcion ; Vicerra, Ryan Rhay P. ; Bandala, Argel A. ; Sybingco, Edwin</creator><creatorcontrib>Dadios, Elmer P. ; Almero, Vincent Jan ; II, Ronnie S. Concepcion ; Vicerra, Ryan Rhay P. ; Bandala, Argel A. ; Sybingco, Edwin ; Center for Engineering and Sustainability Development Research, De La Salle University (DLSU) 2401 Taft Avenue, Malate, Manila 1004, Philippines ; Department of Electronics and Computer Engineering, De La Salle University (DLSU) 2401 Taft Avenue, Malate, Manila 1004, Philippines ; Department of Manufacturing Engineering and Management, De La Salle University (DLSU) 2401 Taft Avenue, Malate, Manila 1004, Philippines</creatorcontrib><description>The understanding of vision-based data acquisition and processing aids in developing predictive frameworks and decision support systems for efficient aquaculture monitoring and management. However, this emerging field is confronted by a lack of high-quality underwater visual data, whether from public or local setups and high cost of development. In this regard, an underwater camera that captures underwater images from an inland freshwater aquaculture setup was proposed. The components of the underwater camera system are primarily based on Raspberry Pi, an open-source computing platform. The underwater camera continuously provides a real-time video streaming link of underwater scenes, and the local processor periodically acquires and stores data from this link in the form of images. These data are stored locally and remotely. Based on the results of the developed low-cost underwater camera, it captures and differentiate fish region to its background before and after flushing as influenced by turbidity. Hence, the developed camera can be used for both aquarium and inland aquaculture pond setup for fish monitoring.</description><identifier>ISSN: 1343-0130</identifier><identifier>EISSN: 1883-8014</identifier><identifier>DOI: 10.20965/jaciii.2022.p0851</identifier><language>eng</language><publisher>Tokyo: Fuji Technology Press Co. Ltd</publisher><subject>Aquaculture ; Cameras ; Data acquisition ; Decision support systems ; Fish ; Image acquisition ; Low cost ; Microprocessors ; Monitoring ; Turbidity ; Underwater ; Video transmission</subject><ispartof>Journal of advanced computational intelligence and intelligent informatics, 2022-09, Vol.26 (5), p.851-858</ispartof><rights>Copyright © 2022 Fuji Technology Press Ltd.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c399t-fe16443035754541ee2d34bb4e22419adb3cf885c77d3a0c092c3e5437c5ba753</citedby><cites>FETCH-LOGICAL-c399t-fe16443035754541ee2d34bb4e22419adb3cf885c77d3a0c092c3e5437c5ba753</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,860,27901,27902</link.rule.ids></links><search><creatorcontrib>Dadios, Elmer P.</creatorcontrib><creatorcontrib>Almero, Vincent Jan</creatorcontrib><creatorcontrib>II, Ronnie S. Concepcion</creatorcontrib><creatorcontrib>Vicerra, Ryan Rhay P.</creatorcontrib><creatorcontrib>Bandala, Argel A.</creatorcontrib><creatorcontrib>Sybingco, Edwin</creatorcontrib><creatorcontrib>Center for Engineering and Sustainability Development Research, De La Salle University (DLSU) 2401 Taft Avenue, Malate, Manila 1004, Philippines</creatorcontrib><creatorcontrib>Department of Electronics and Computer Engineering, De La Salle University (DLSU) 2401 Taft Avenue, Malate, Manila 1004, Philippines</creatorcontrib><creatorcontrib>Department of Manufacturing Engineering and Management, De La Salle University (DLSU) 2401 Taft Avenue, Malate, Manila 1004, Philippines</creatorcontrib><title>Low-Cost Underwater Camera: Design and Development</title><title>Journal of advanced computational intelligence and intelligent informatics</title><description>The understanding of vision-based data acquisition and processing aids in developing predictive frameworks and decision support systems for efficient aquaculture monitoring and management. However, this emerging field is confronted by a lack of high-quality underwater visual data, whether from public or local setups and high cost of development. In this regard, an underwater camera that captures underwater images from an inland freshwater aquaculture setup was proposed. The components of the underwater camera system are primarily based on Raspberry Pi, an open-source computing platform. The underwater camera continuously provides a real-time video streaming link of underwater scenes, and the local processor periodically acquires and stores data from this link in the form of images. These data are stored locally and remotely. Based on the results of the developed low-cost underwater camera, it captures and differentiate fish region to its background before and after flushing as influenced by turbidity. Hence, the developed camera can be used for both aquarium and inland aquaculture pond setup for fish monitoring.</description><subject>Aquaculture</subject><subject>Cameras</subject><subject>Data acquisition</subject><subject>Decision support systems</subject><subject>Fish</subject><subject>Image acquisition</subject><subject>Low cost</subject><subject>Microprocessors</subject><subject>Monitoring</subject><subject>Turbidity</subject><subject>Underwater</subject><subject>Video transmission</subject><issn>1343-0130</issn><issn>1883-8014</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>BENPR</sourceid><recordid>eNotkE1LxDAQQIMouKz7BzwVPHedZJKm9SZVV2HBi3sOaTqVLtsPk66L_9649TRv4DEDj7FbDmsBRabu99a1bRsXIdYj5IpfsAXPc0xz4PIyMkpMgSNcs1UIe4DIIgPJF0xsh1NaDmFKdn1N_mQn8klpO_L2IXmi0H72ie3riN90GMaO-umGXTX2EGj1P5ds9_L8Ub6m2_fNW_m4TR0WxZQ2xDMpEVBpJZXkRKJGWVWShJC8sHWFrslz5bSu0YKDQjgkJVE7VVmtcMnu5rujH76OFCazH46-jy-N0DyKKpM6WmK2nB9C8NSY0bed9T-GgznnMXMe85fHnPPgL1UqV6c</recordid><startdate>20220920</startdate><enddate>20220920</enddate><creator>Dadios, Elmer P.</creator><creator>Almero, Vincent Jan</creator><creator>II, Ronnie S. Concepcion</creator><creator>Vicerra, Ryan Rhay P.</creator><creator>Bandala, Argel A.</creator><creator>Sybingco, Edwin</creator><general>Fuji Technology Press Co. Ltd</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SP</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K7-</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>P5Z</scope><scope>P62</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope></search><sort><creationdate>20220920</creationdate><title>Low-Cost Underwater Camera: Design and Development</title><author>Dadios, Elmer P. ; Almero, Vincent Jan ; II, Ronnie S. Concepcion ; Vicerra, Ryan Rhay P. ; Bandala, Argel A. ; Sybingco, Edwin</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c399t-fe16443035754541ee2d34bb4e22419adb3cf885c77d3a0c092c3e5437c5ba753</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Aquaculture</topic><topic>Cameras</topic><topic>Data acquisition</topic><topic>Decision support systems</topic><topic>Fish</topic><topic>Image acquisition</topic><topic>Low cost</topic><topic>Microprocessors</topic><topic>Monitoring</topic><topic>Turbidity</topic><topic>Underwater</topic><topic>Video transmission</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Dadios, Elmer P.</creatorcontrib><creatorcontrib>Almero, Vincent Jan</creatorcontrib><creatorcontrib>II, Ronnie S. Concepcion</creatorcontrib><creatorcontrib>Vicerra, Ryan Rhay P.</creatorcontrib><creatorcontrib>Bandala, Argel A.</creatorcontrib><creatorcontrib>Sybingco, Edwin</creatorcontrib><creatorcontrib>Center for Engineering and Sustainability Development Research, De La Salle University (DLSU) 2401 Taft Avenue, Malate, Manila 1004, Philippines</creatorcontrib><creatorcontrib>Department of Electronics and Computer Engineering, De La Salle University (DLSU) 2401 Taft Avenue, Malate, Manila 1004, Philippines</creatorcontrib><creatorcontrib>Department of Manufacturing Engineering and Management, De La Salle University (DLSU) 2401 Taft Avenue, Malate, Manila 1004, Philippines</creatorcontrib><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Computer Science Collection</collection><collection>Computer Science Database</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><jtitle>Journal of advanced computational intelligence and intelligent informatics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Dadios, Elmer P.</au><au>Almero, Vincent Jan</au><au>II, Ronnie S. Concepcion</au><au>Vicerra, Ryan Rhay P.</au><au>Bandala, Argel A.</au><au>Sybingco, Edwin</au><aucorp>Center for Engineering and Sustainability Development Research, De La Salle University (DLSU) 2401 Taft Avenue, Malate, Manila 1004, Philippines</aucorp><aucorp>Department of Electronics and Computer Engineering, De La Salle University (DLSU) 2401 Taft Avenue, Malate, Manila 1004, Philippines</aucorp><aucorp>Department of Manufacturing Engineering and Management, De La Salle University (DLSU) 2401 Taft Avenue, Malate, Manila 1004, Philippines</aucorp><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Low-Cost Underwater Camera: Design and Development</atitle><jtitle>Journal of advanced computational intelligence and intelligent informatics</jtitle><date>2022-09-20</date><risdate>2022</risdate><volume>26</volume><issue>5</issue><spage>851</spage><epage>858</epage><pages>851-858</pages><issn>1343-0130</issn><eissn>1883-8014</eissn><abstract>The understanding of vision-based data acquisition and processing aids in developing predictive frameworks and decision support systems for efficient aquaculture monitoring and management. However, this emerging field is confronted by a lack of high-quality underwater visual data, whether from public or local setups and high cost of development. In this regard, an underwater camera that captures underwater images from an inland freshwater aquaculture setup was proposed. The components of the underwater camera system are primarily based on Raspberry Pi, an open-source computing platform. The underwater camera continuously provides a real-time video streaming link of underwater scenes, and the local processor periodically acquires and stores data from this link in the form of images. These data are stored locally and remotely. Based on the results of the developed low-cost underwater camera, it captures and differentiate fish region to its background before and after flushing as influenced by turbidity. Hence, the developed camera can be used for both aquarium and inland aquaculture pond setup for fish monitoring.</abstract><cop>Tokyo</cop><pub>Fuji Technology Press Co. Ltd</pub><doi>10.20965/jaciii.2022.p0851</doi><tpages>8</tpages><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | ISSN: 1343-0130 |
ispartof | Journal of advanced computational intelligence and intelligent informatics, 2022-09, Vol.26 (5), p.851-858 |
issn | 1343-0130 1883-8014 |
language | eng |
recordid | cdi_proquest_journals_2715435647 |
source | DOAJ Directory of Open Access Journals |
subjects | Aquaculture Cameras Data acquisition Decision support systems Fish Image acquisition Low cost Microprocessors Monitoring Turbidity Underwater Video transmission |
title | Low-Cost Underwater Camera: Design and Development |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-10T17%3A18%3A31IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Low-Cost%20Underwater%20Camera:%20Design%20and%20Development&rft.jtitle=Journal%20of%20advanced%20computational%20intelligence%20and%20intelligent%20informatics&rft.au=Dadios,%20Elmer%20P.&rft.aucorp=Center%20for%20Engineering%20and%20Sustainability%20Development%20Research,%20De%20La%20Salle%20University%20(DLSU)%202401%20Taft%20Avenue,%20Malate,%20Manila%201004,%20Philippines&rft.date=2022-09-20&rft.volume=26&rft.issue=5&rft.spage=851&rft.epage=858&rft.pages=851-858&rft.issn=1343-0130&rft.eissn=1883-8014&rft_id=info:doi/10.20965/jaciii.2022.p0851&rft_dat=%3Cproquest_cross%3E2715435647%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2715435647&rft_id=info:pmid/&rfr_iscdi=true |