Views provided by UsageCounts
In this paper we present a complete framework for modelling and estimating vessel GHG emissions and related air pollutants (i.e. CO2 and SOx, NOx and PM) in ports, based on data collected from the Automatic Identification System (AIS). Our approach adopts a modified lambda architecture approach, which consists of a knowledge extraction batch processing step and a real time emissions calculation step. The approach makes it possible to automatically identify the berths or ports where emissions are high in a consistent and uniform way across the globe. This research is part of the Project OPS Master Plan for Spanish Ports (2015-EU-TM-0417) which is co-financed by the Connecting Europe Facility (CEF) for the building of the European Union's Trans-European Transport Network (TEN-T).
http://poweratberth.eu/
Big Data; Vessel Emission Estimation; Real time Architecture;On-shore electricity supply
Big Data; Vessel Emission Estimation; Real time Architecture;On-shore electricity supply
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 2 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
| views | 13 |

Views provided by UsageCounts