ItemArticle

JP-DAP: An Intelligent Data Analytics Platform for Metro Rail Transport Systems

Title
JP-DAP: An Intelligent Data Analytics Platform for Metro Rail Transport Systems
Creator
Mulerikkal J.; Thandassery S.; Dixon K D.M.; Rejathalal V.; Ayyappan B.
Description
This paper deals with an intelligent data analytics platform-Jaison-Paul Data Analytics Platform (JP-DAP)-for metro rail transport systems. JP-DAP is intended to ensure smooth functioning, improved customer experience, ridership forecasting, and efficient administration of metro rail transportation systems by integrating and analysing its many data sources. It consists of a middleware which is built on the top of a Hadoop Distributed File System (HDFS) and Spark framework, along with a set of open-source software tools like Apache Hive, Pandas, Google TensorFlow and Spark ML-lib for real-time and legacy data processing. The benchmarking of JP-DAP was conducted using TestDFSIO and have found that it performs well according to industry standards. The specific use case for this project is Kochi Metro Rail Limited (KMRL). The analysis of Automated Fare Collection data from KMRL on JP-DAP framework have produced descriptive statistics visualisation of inflow and outflow analysis, travel patterns during weekdays and weekends, origin-destination matrix, etc.. Moreover JP-DAP framework is capable of producing short term passenger flow predictions using SVR machine learning algorithm with linear, radial basis function and polynomial kernels. Our experiments have shown that SVR linear kernel gives the most accurate results with the least errors in predicting the next day's passenger count using the previous five weekdays data. The station usage (one-to-all) prediction using Long Short-Term Memory (LSTM) is also integrated to this framework. The visualisation as well as analytical outcomes of JP-DAP framework have also been made available to the external world using a rich set of REST APIs and are projected on to a web-dashboard. 2000-2011 IEEE.
Source
IEEE Transactions on Intelligent Transportation Systems, Vol-23, No. 7, pp. 9146-9156.
Date
2022-01-01
Publisher
Institute of Electrical and Electronics Engineers Inc.
Subject
Big data analytics; Hadoop; intelligent transport systems; machine learning; metro rail; TestDFSIO
Coverage
Mulerikkal J., The Department of Computer Science, Rajagiri School of Engineering and Technology, Kochi, 682039, India; Thandassery S., The Department of Computer Science, Rajagiri School of Engineering and Technology, Kochi, 682039, India, The Department of Computer Science, Christ-Deemed to Be University, Bengaluru, 560029, India; Dixon K D.M., The Department of Computer Science, Jyothi Engineering College, Thrissur, 679531, India; Rejathalal V., The Department of Computer Science, Jyothi Engineering College, Thrissur, 679531, India; Ayyappan B., The Department of Information Technology, Rajagiri School of Engineering and Technology, Kochi, 682039, India
Rights
Restricted Access
Relation
ISSN: 15249050
Format
Online
Language
English
Type
Article

Collection

Articles

Citation

Mulerikkal J.; Thandassery S.; Dixon K D.M.; Rejathalal V.; Ayyappan B., “JP-DAP: An Intelligent Data Analytics Platform for Metro Rail Transport Systems,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 24, 2025, https://archives.christuniversity.in/items/show/15069.

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