Wi-Fi Sniffer Based Commuters Statistics Collection System For Reliable Bus Scheduling System

Lim, Kim Chuan and Hoo, Jian Ea and Lee, Yin Hui (2016) Wi-Fi Sniffer Based Commuters Statistics Collection System For Reliable Bus Scheduling System. ARPN Journal Of Engineering And Applied Sciences, 11 (12). pp. 7883-7887. ISSN 1819-6608

Text Wi-Fi Sniffer Based Commuters Statistics Collection System For Reliable Bus Scheduling System.pdf - Published Version Download (552kB)

Abstract

Traffic congestion issues have always been a concern for the fast growing metropolitans in which more than 90 percent of trips are made entirely by private means of transportation i.e. by car and motorcycle. As the country is actively engaged in infrastructure development especially in the transportation network to facilitate the movements of people and goods, a high demand for better public transportation is needed to reduce the issue of road congestion (percentage of GDI lost due to man hour lost in the traffic). Therefore, a cost effective Wi-Fi sniffing based bus commuters’ statistic collection system is designed and developed to study the feasibility of predicting the necessity of scheduling additional bus services when the detected number of Wi-Fi enabled devices exceeded the bus capacity. The developed system is subsequently deployed to the busiest university bus stop and the obtained result shows that variation of sniffed MAC address exhibit parallelism to the actual number of commuters waiting at the bus station as observed in the captured bus station video images. Result also shows that the MAC address based counting system can help to alert the bus management for better scheduling when the commuter at the particular bus stop is traveling to the same destination.

Item Type:	Article
Uncontrolled Keywords:	Wi-Fi sniffing, raspberry pi sniffer, unique MAC addresses based commuter statistic collection system.
Subjects:	T Technology > T Technology (General) T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions:	Faculty of Electronics and Computer Engineering > Department of Industrial Electronics
Depositing User:	Mohd Hannif Jamaludin
Date Deposited:	29 Nov 2016 06:26
Last Modified:	15 Sep 2021 00:17
URI:	http://eprints.utem.edu.my/id/eprint/17710
Statistic Details:	View Download Statistic

Actions (login required)

View Item