Prasad C. Mahajan, A. Kiwelekar, L. Netak, Akshay Ghodake
{"title":"Applications of Predictive Analytics in Marine Transportation","authors":"Prasad C. Mahajan, A. Kiwelekar, L. Netak, Akshay Ghodake","doi":"10.1109/CCGE50943.2021.9776446","DOIUrl":null,"url":null,"abstract":"Automatic Identification System (AIS), the automated data collection system for vessel tracking, plays an essential role in marine traffic management. AIS system is generating an enormous volume of data which has rampant growth. The AIS data has the potential to drive transport activities, and significant hidden insights are possible to draw by analyzing the AIS data. Some of the tasks which can rely on the AIS data are predicting routes of vessels, predicting traffic intensity, estimating the time of arrival of a ship and transport of volume. The development of analytical techniques for AIS data would lead to the attainment of business goals such as increasing profit, optimally utilize human resources at a port and reducing traffic in the ocean. This paper reviews existing and emerging techniques used to analyze AIS data in the field of marine transportation.","PeriodicalId":130452,"journal":{"name":"2021 International Conference on Computing, Communication and Green Engineering (CCGE)","volume":"4 2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 International Conference on Computing, Communication and Green Engineering (CCGE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCGE50943.2021.9776446","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Automatic Identification System (AIS), the automated data collection system for vessel tracking, plays an essential role in marine traffic management. AIS system is generating an enormous volume of data which has rampant growth. The AIS data has the potential to drive transport activities, and significant hidden insights are possible to draw by analyzing the AIS data. Some of the tasks which can rely on the AIS data are predicting routes of vessels, predicting traffic intensity, estimating the time of arrival of a ship and transport of volume. The development of analytical techniques for AIS data would lead to the attainment of business goals such as increasing profit, optimally utilize human resources at a port and reducing traffic in the ocean. This paper reviews existing and emerging techniques used to analyze AIS data in the field of marine transportation.