Big Data Implementation of Smart Rapid Transit using CCTV Surveillance
Dahlan I.A.a, Hamami F.a, Supangkat S.H.a, Hidayat F.a
a Institut Teknologi Bandung, School of Electrical Engineering and Informatics, Bandung, Indonesia
Abstract
© 2019 IEEE.This paper presents the implementation on smart system for rapid transit using CCTV surveillance. Researchers proposed deep learning algorithms to detect objects with Convolutional Neural Network (CNN) and monitoring passengers’ behavior like flow analytics, avoiding dangerous areas, and preventing intruder visitor[1][2].Research of this paper also implemented in Railway Station in Bandung with multiple CCTV sources. The system aims to make station better and able to improve quality of service in many scope areas (safe, secure and convenient)[3].Objective of this research is to develop smart surveillance with CCTV in smart station. The system consists of deep learning algorithm and big data technologies such as Hadoop, Apache Kafka and Apache Spark.
Author keywords
CCTV surveillance,Dangerous area,Data implementation,Data technologies,Railway stations,Railways,Smart surveillance,Smart System
Indexed keywords
Big Data,Convolutional Neural Network,Deep Learning,Railways
Funding details
This research is partially funded by the Indonesian Ministry of Research, Technology and Higher Education under WCU Program managed by Bandung Institute of Technology also supported by LPDP RISPRO KOMERSIAL Ministry of Finance, and Smart City Community Lab in Bandung Institute of Technology (ITB) Bandung.