Key points are not available for this paper at this time.
The Internet of Things Technology (IoT) is developing so rapidly. One of IoT implementation is an Internet of Underwater Things (IoUT) which is used for underwater monitoring. This paper discuss an integrated smart environment system framework based on IoUT and big data that consist of open platform that processes data from Remotely Operated Vehicle (ROV) and portable sensor with water parameters sensors such an input device to collect and save the data of oxidation-reduction potential, pH, electrical conductivity, total dissolve solid, salinity, dissolved oxygen, and temperature in monitored rivers temporary. Coral Reef Monitoring used for preventing coral bleaching by using underwater camera to take some pictures that will be sent to data center and then analyze it, Wireless Mess Network Access Point used as the way ROVs `talking' to each other while doing a monitoring process in a wide river. Then all of the collected data from ROVs and portable sensor will be saved and analyzed to the data center platform based on Hadoop Multi-Node Cluster. The data will be visualized as a chart or a table and can be accessed world-wide We found that, the processing of the data used in the open platform to be relatively straightforward using a combination of SQL. However, the use of HDFS (Hadoop Distributed File System) as data center and more versatile frameworks such as Mapreduce, Hive, Spark, Redis and more flexible set component of features that particularly facilitate working with larger volumes and more heterogeneous data sources.
Berlian et al. (Thu,) studied this question.