[KSCI] Korea Science Citation Index Service

http://dx.doi.org/10.9708/jksci.2019.24.12.067

Design and Implementation of a Big Data Analytics Framework based on Cargo DTG Data for Crackdown on Overloaded Trucks

Kim, Bum-Soo (Dept. of Future Technology and Convergence Research, Korea Institute of Civil Engineering and Building Technology)

Publication Information

Journal of the Korea Society of Computer and Information / v.24, no.12, 2019 , pp. 67-74 More about this Journal

Abstract

In this paper, we design and implement an analytics platform based on bulk cargo DTG data for crackdown on overloaded trucks. DTG(digital tachograph) is a device that stores the driving record in real time; that is, it is a device that records the vehicle driving related data such as GPS, speed, RPM, braking, and moving distance of the vehicle in one second unit. The fast processing of DTG data is essential for finding vehicle driving patterns and analytics. In particular, a big data analytics platform is required for preprocessing and converting large amounts of DTG data. In this paper, we implement a big data analytics framework based on cargo DTG data using Spark, which is an open source-based big data framework for crackdown on overloaded trucks. As the result of implementation, our proposed platform converts real large cargo DTG data sets into GIS data, and these are visualized by a map. It also recommends crackdown points.

Keywords

Big data; Cargo DTG; Spark framework; Preprocessing; GIS;

Citations & Related Records

Reference

1	X. Wu, X. Zhu, G. Wu and W. Ding, "Data Mining with Big Data," IEEE Transactions on Knowledge and Data Engineering, Vol. 26, No. 1, pp. 97-107, Jan. 2014. DOI
2	T.-H. Kim, B.-S. Kim, and J.-U. Kim, "A Study on the Analysis Method for the Optimal Location of Overstrength Restrictions Using Cargo DTG," In Proc. of the KAIS Fall Conference, pp. 1-3, Nov. 2018.
3	Apache Spark, https://spark.apache.org/
4	Suwon National Territory Management Office, http://www.molit.go.kr/srocm/intro.do
5	H. Hu, Y. Wen, T.-S. Chua, and X. Li, "Toward Scalable Systems for Big Data Analytics: A Technology Tutorial," IEEE Access, Vol. 2, No. 8, pp. 652-687, July 2014. DOI
6	L. Dagum and R. Menon, "OpenMP: An Industry Standard API for Shared-Memory Programming," IEEE Comput. Sci. & Eng. Vol. 5, No. 1, pp. 46-55, Jan./Mar. 1998. DOI
7	G. Malewicz, M. H. Austern, A. J.C Bik, J. C. Dehnert, I. Horn, N. Leiser, and G. Czajkowski, "Pregel: a system for large-scale graph processing," in Proc. of the 2010 ACM SIGMOD Int'l Conf. on Manag. Data, Indianapolis, Indiana, pp. 135-146, June 2010.
8	J. Dean and S. Ghemawat, "MapReduce: Simplified Data Processing on Large Clusters," Communications of the ACM, Vol. 51, No. 1, pp. 107-113, Jan. 2008. DOI
9	Apache Hadoop, https://hadoop.apache.org/
10	Apache Mahout, http://mahout.apache.org/
11	J. Krumm, J. Letchner, and E. Horvitz, "Map Matching with Travel Time Constraints," SAE Technical Paper 2007-01-1102, 2007.
12	NGA Office of GEOINT Science (WGS 84), http://earthinfo.nga.mil/GandG/wgs84/index.html
13	D.-H. Han, S.-H. Kim, J.-J. Park, J.-H. Lee, and J.-H. Kim, "A Study on the Traffic Analysis Method Using Vehicle Trajectory Data," Expressway & Transportation Research Institute, 2017.
14	L. Cao and J. Krumm, "From GPS Traces to a Routable Road Map," in Proc. of the 17th ACM SIGSPATIAL Int'l Conf. on Adv. in Geo. Inf. Sys., Seattle, Washington, pp. 3-12, Nov. 2009.
15	S. R. Eddy, "Profile Hidden Markov models," Bioinformatics Review, Vol. 14, No. 9, pp. 755-763, Sept. 1998. DOI
16	S. Menard, "Applied Logistic Regression Analysis," SAGE Publishing, 2002.
17	OGC GeoServer, http://geoserver.org/
18	Y. Lou, C. Zhang, X. Xie, Y. Zheng, W. Wang, and Y. Huang, "Map-Matching for Low-Sampling-Rate GPS Trajectories," in Proc. of the 17th ACM SIGSPATIAL Int'l Conf. on Adv. in Geo. Inf. Sys., Seattle, Washington, pp. 352-361, Nov. 2009.
19	G., Branko, "Convex Polytopes, Graduate Texts in Mathematics," Springer, 2003.
20	Geocoding XGA Solution, http://www.openmate.co.kr/
21	Open Data Portal, https://www.data.go.kr/
22	Construction CALS System, https://www.calspia.go.kr/