Ticket Collection with Destination Prediction in Bus Services in Urban Areas using Time Based Predictive Algorithm
S. Jayakumar1, M. Srivathsan2, S. Samundar Ahmed3, Dhanish Kumar S M4, M. Karthikeyan5
1S. Jayakumar, Assistant Professor, Department of Computer Science and Engineering, SRM Institute of Science and Technology, Chennai (Tamil Nadu), India.
2M. Srivathsan, Student, Department of Computer Science and Engineering, SRM Institute of Science and Technology, Chennai (Tamil Nadu), India.
3S. Samundar Ahmed, Student, Department of Computer Science and Engineering, SRM Institute of Science and Technology, Chennai (Tamil Nadu), India.
4Dhanish Kumar S M, Student, Department of Computer Science and Engineering, SRM Institute of Science and Technology, Chennai (Tamil Nadu), India.
5M. Karthikeyan, Student, Department of Computer Science and Engineering, SRM Institute of Science and Technology, Chennai (Tamil Nadu), India.
Manuscript received on 24 November 2019 | Revised Manuscript received on 07 December 2019 | Manuscript Published on 14 December 2019 | PP: 126-131 | Volume-9 Issue-1S October 2019 | Retrieval Number: A10251091S19/19©BEIESP | DOI: 10.35940/ijeat.A1025.1091S19
Open Access | Editorial and Publishing Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In the new age of automation and machine assisted function of the human way of life people still tend to notice verification and checking of tickets in local land transport such as trains and buses to still be operated by man. This project is a proposal of a new platform and method to book these tickets of buses on a local level. This can lead to decrease in the overcrowding of buses, easy time management of commuters, and smooth functioning of the bus business. Initially the bank details of the passenger must be linked to the app. Machine learning predictive parsing algorithm in combination with data mining features enable the prediction of the passengers to and fro details on a daily and timely basis. Then a SMS alert for ticket payment proof is sent to the user. In admin side, they calculate amount details using this application. Per day amount details of specific route or bus can be calculated by accessing the database. There is also a provision where the IMEI numbers of the consumers is collected. Through GPS system the IMEI numbers of the mobiles inside the bus is checked with the IMEI numbers of those in the database. Ticket defaulters are identified if the IMEI numbers are not present in the database. The entire trail of the transit is on a non-paper sever.
Keywords: GPS, IMEI, Ticket.
Scope of the Article: Predictive Analysis