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Analysis of passenger flow prediction model using machine learning algorithms for sustainable development in smart railway system
K. Vijay Kumar Reddy, , K. Karthik, P. Shrivastava, A. Rajalingam
Published in Alpha Publishers
2020
Volume: 10
   
Issue: 11
Pages: 10214 - 10225
Abstract
In this paper, a smart railway system is developed to monitor fine collection, food wastage and sales flow in railway pantry, passenger flow, security etc., various sensors are used to count the number of passengers who board the train in a coach. The sensors placed in the door can detect the person boarding the train. The ATmega328 controller used to check the data of passengers entering and exiting the train sends data constantly to every station through wireless module. The smart pantry uses the previous sales data of the food items and uses the data to predict the sales of products in future. The data acquired by the sensors is sent to cloud platform using ESP8266 node mcu and prediction of sales of products is done using the data. The passenger prediction uses the past data of number of passengers travelled in the train and uses the data to predict passenger flow in the trains based on seasonal changes and the data can be used to add the passenger coaches. The system can be adapted for railways because the proposed system is relatively cheap and the system can work efficiently and does not require much space. © Alpha Publishers. All rights reserved.
About the journal
JournalJournal of Green Engineering
PublisherAlpha Publishers
ISSN19044720