02605naa a22003258i 4500 5330 5330 00005330 FR-PaOEC 20211006062617.0 a o d i cr || |||m|n|| 190601s2017 ||| o i|0| 0 eng d (FR-PaOEC) FR-PaOEC ES-MaONT Palaniswami, Marimuthu 3375 Real-time monitoring of the Great Barrier Reef using Internet of Things with big data analytics / Marimuthu Palaniswami, Aravinda S. Rao and Scott Bainbridge Geneva : International Telecommunication Union, 2017. 10 p. texto (visual) isbdcontent electrónico isbdmedia recurso en línea rdacarrier The 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. Tecnologías habilitadoras digitales 18 Science and Technology Rao, Aravinda S. 3376 Bainbridge, Scott 3377 4843 ITU Journal: ICT Discoveries Vol. 2018, no. 1, p. 23-32 2018:1<23 2616-8375 itu-ilibrary.org https://www.itu.int/dms_pub/itu-s/opb/journal/S-JOURNAL-ICTS.V1I1-2017-3-PDF-E.pdf Acceso al documento 0 pdf ART udc 0 0 0 3 1 6280 01 01 online 2019-09-12 0 1000020175579 2019-09-12 00:00:00 2019-09-12 ART pdf