TY  - GEN
AB  - Efficiency, performance and monitoring of vessels becomes of paramount importance around the globe. Assets security, vessels efficiency, new directives and legislation with regard to emissions quality and many others, urge the global maritime industry to take the right initiatives and make the appropriate investments to develop data ecosystems, that over time, if used intelligently, coherently and consistently, will allow owners and managers to reap tangible benefits such as, among others, significant cost savings, better vessel management and longer vessel life span. As of today, most shipowners and related stakeholders face huge challenges when it comes to data collection, processing, streaming, sharing and storage. Relevant data, if any, is isolated in distinct silos, in spurious and inconsistent formats with little or non-existent interconnectivity between such silos or storage mechanisms. In effect, to face the new challenging landscape, a fresh mindset and an open-minded approach is required. The paper uses data and relevant building blocks, related to vessel performance, assets tracking, route planning, engine monitoring, fuel consumptions, emissions quality, vessels tracking, performance alarms and notifications; that is a wide variety of data modules and reporting tools, that eventually serve pure reporting, real-time monitoring and visualization objectives; but also some additional, more powerful modules being used for analytics and strategic decision making. Such modules can leverage on historical data being captured over prolonged time periods, in the various interrelated data sources and by the relevant data collectors and, if deployed effectively, to construct supervised, unsupervised or even semi-supervised machine learning models. 
AU  - Theodossiou, S
AU  - Singh Rainu, N
DA  - 2019-11-05
ID  - 11109
JF  - Conference Proceedings of ICMET
L1  - https://library.imarest.org/record/11109/files/Paper%2017%20-%20Digital%20Initiatives%2C%20Infrastructures%20and%20Data%20Ecosystems%20in%20the%20Maritime.pdf
L2  - https://library.imarest.org/record/11109/files/Paper%2017%20-%20Digital%20Initiatives%2C%20Infrastructures%20and%20Data%20Ecosystems%20in%20the%20Maritime.pdf
L4  - https://library.imarest.org/record/11109/files/Paper%2017%20-%20Digital%20Initiatives%2C%20Infrastructures%20and%20Data%20Ecosystems%20in%20the%20Maritime.pdf
LK  - https://library.imarest.org/record/11109/files/Paper%2017%20-%20Digital%20Initiatives%2C%20Infrastructures%20and%20Data%20Ecosystems%20in%20the%20Maritime.pdf
N2  - Efficiency, performance and monitoring of vessels becomes of paramount importance around the globe. Assets security, vessels efficiency, new directives and legislation with regard to emissions quality and many others, urge the global maritime industry to take the right initiatives and make the appropriate investments to develop data ecosystems, that over time, if used intelligently, coherently and consistently, will allow owners and managers to reap tangible benefits such as, among others, significant cost savings, better vessel management and longer vessel life span. As of today, most shipowners and related stakeholders face huge challenges when it comes to data collection, processing, streaming, sharing and storage. Relevant data, if any, is isolated in distinct silos, in spurious and inconsistent formats with little or non-existent interconnectivity between such silos or storage mechanisms. In effect, to face the new challenging landscape, a fresh mindset and an open-minded approach is required. The paper uses data and relevant building blocks, related to vessel performance, assets tracking, route planning, engine monitoring, fuel consumptions, emissions quality, vessels tracking, performance alarms and notifications; that is a wide variety of data modules and reporting tools, that eventually serve pure reporting, real-time monitoring and visualization objectives; but also some additional, more powerful modules being used for analytics and strategic decision making. Such modules can leverage on historical data being captured over prolonged time periods, in the various interrelated data sources and by the relevant data collectors and, if deployed effectively, to construct supervised, unsupervised or even semi-supervised machine learning models. 
PY  - 2019-11-05
T1  - Digital Initiatives, Infrastructures and Data Ecosystems in the Maritime Sector
TI  - Digital Initiatives, Infrastructures and Data Ecosystems in the Maritime Sector
UR  - https://library.imarest.org/record/11109/files/Paper%2017%20-%20Digital%20Initiatives%2C%20Infrastructures%20and%20Data%20Ecosystems%20in%20the%20Maritime.pdf
VL  - ICMET 2019
Y1  - 2019-11-05
ER  -