2019
DOI: 10.1007/s00773-019-00632-5
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Abstract: Future vessels will be facilitated by modern internet of things (IoT) to collect various ship performance and navigation information. Such information is collected as large-scale data sets, so called Big Data and that should be utilized towards digitalization of the shipping industry. However, various data handling challenges are encountered by the shipping industry during the phase of digitalization, onboard as well as onshore. Data driven models, so called digital models, to support data handling frameworks … Show more

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Cited by 10 publications
(6 citation statements)
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“…It is a common issue in the automation and sensor systems that data can sometimes be of dubious or erroneous format. This is due to the fact that the sensor has failed or there is an abnormal event within the systems [23,28]. The data will not be carried out the quality checks which leads to the uncertainty of how much the output data is incorrect.…”
Section: A Challenges Of Big Data In the Shipping Industrymentioning
confidence: 99%
See 1 more Smart Citation
“…It is a common issue in the automation and sensor systems that data can sometimes be of dubious or erroneous format. This is due to the fact that the sensor has failed or there is an abnormal event within the systems [23,28]. The data will not be carried out the quality checks which leads to the uncertainty of how much the output data is incorrect.…”
Section: A Challenges Of Big Data In the Shipping Industrymentioning
confidence: 99%
“…These data clusters indicate navigational and operational information of vessel in respective scenarios (e.g., enginepropeller operating modes and trim-draft combination). The structure of each data cluster can be identified by data digital models [28]. Hence, the development of these data digital models plays pivotal role in the data handling process.…”
Section: Advanced Data Analyticsmentioning
confidence: 99%
“…Digital Models are another form of data driven networks developed to quantify ship performance and navigation conditions. Ship performance and navigation parameters collected by onboard IoT as data sets are considered to derive these networks [4]. A general representation of a digital model is presented in Figure 1.…”
Section: A Network Structurementioning
confidence: 99%
“…Secondly, the structural shapes of digital models can be used to support various shipping industrial applications, e.g. ship energy efficiency, emission control and system reliability [4]. Since these models are derived from ship performance and navigation data sets, that can be a representative model for vessel and ship system behavior.…”
Section: Data Anomaliesmentioning
confidence: 99%
“…Data cleaning is the first and most important step, avoiding the waste of analysis resources, or even the 'Garbage in, garbage out' phenomenon [24]. Perera et al proposed a new digital model and built a data handling framework with pre-processing and post-processing units, based on the proposed digital model [25]. Raptodimos et al proposed an integrated method based on an artificial neural network (ANN), which applies cross-clustering and selforganising mapping to cluster data, and then realises the main engine fault diagnosis [26].…”
Section: Introductionmentioning
confidence: 99%