JIPS (한국정보처리학회)
Current Result Document : 1 / 1
| 한글제목(Korean Title) |
DTG Big Data Analysis for Fuel Consumption Estimation |
| 영문제목(English Title) |
DTG Big Data Analysis for Fuel Consumption Estimation |
| 저자(Author) |
Wonhee Cho
Eunmi Choi
|
| 원문수록처(Citation) |
VOL 13 NO. 02 PP. 0285 ~ 0304 (2017. 04) |
한글내용
(Korean Abstract) |
|
영문내용
(English Abstract) |
Big data information and pattern analysis have applications in many industrial sectors. To reduce energy consumption effectively, the eco-driving method that reduces the fuel consumption of vehicles has recently come under scrutiny. Using big data on commercial vehicles obtained from digital tachographs (DTGs), it is possible not only to aid traffic safety but also improve eco-driving. In this study, we estimate fuel consumption efficiency by processing and analyzing DTG big data for commercial vehicles using parallel processing with the MapReduce mechanism. Compared to the conventional measurement of fuel consumption using the On-Board Diagnostics II (OBD-II) device, in this paper, we use actual DTG data and OBD-II fuel consumption data to identify meaningful relationships to calculate fuel efficiency rates. Based on the driving pattern extracted from DTG data, estimating fuel consumption is possible by analyzing driving patterns obtained only from DTG big data.
|
| 키워드(Keyword) |
Big Data Analysis
DTG
Eco-Driving
Fuel Economy
Fuel Consumption Estimation
MapReduce
|
| 파일첨부 |
PDF 다운로드
|
