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008 190601s2017 ||| o i|0| 0 eng d
035 _a(FR-PaOEC)
040 _aFR-PaOEC
_cES-MaONT
100 1 _aPalaniswami, Marimuthu
_93375
245 1 0 _aReal-time monitoring of the Great Barrier Reef using Internet of Things with big data analytics /
_cMarimuthu Palaniswami, Aravinda S. Rao and Scott Bainbridge
260 _aGeneva :
_bInternational Telecommunication Union,
_c2017.
300 _a10 p.
336 _atexto (visual)
_2isbdcontent
337 _aelectrónico
_2isbdmedia
338 _arecurso en línea
_2rdacarrier
520 3 _aThe Great Barrier Reef (GBR) of Australia is the largest size of coral reef system on the planet stretching over 2300 kilometers. Coral reefs are experiencing a range of stresses including climate change, which has resulted in episodes of coral bleaching and ocean acidification where increased levels of carbon dioxide from the burning of fossil fuels are reducing the calcification mechanism of corals. In this article, we present a successful application of big data analytics with Internet of Things (IoT)/wireless sensor networks (WSNs) technology to monitor complex marine environments of the GBR. The paper presents a two-tiered IoT/WSN network architecture used to monitor the GBR and the role of artificial intelligence (AI) algorithms with big data analytics to detect events of interest. The case study presents the deployment of a WSN at Heron Island in the southern GBR in 2009. It is shown that we are able to detect Cyclone Hamish patterns as an anomaly using the sensor time series of temperature, pressure and humidity data. The article also gives a perspective of AI algorithms from the viewpoint to monitor, manage and understand complex marine ecosystems. The knowledge obtained from the large-scale implementation of IoT with big data analytics will continue to act as a feedback mechanism for managing a complex system of systems (SoS) in our marine ecosystem.
650 0 _aTecnologías habilitadoras digitales
_918
653 4 _aScience and Technology
700 1 _aRao, Aravinda S.
_93376
700 1 _aBainbridge, Scott
_93377
773 0 _04843
_tITU Journal: ICT Discoveries
_gVol. 2018, no. 1, p. 23-32
_q2018:1<23
_x2616-8375
856 4 0 _aitu-ilibrary.org
_uhttps://www.itu.int/dms_pub/itu-s/opb/journal/S-JOURNAL-ICTS.V1I1-2017-3-PDF-E.pdf
_yAcceso al documento
_x0
_qpdf
942 _cART
_2udc