The practicability of predicting the number of bus passengers by monitoring wi-fi signal from mobile devices with the polynomial regression

Oransirikul, Thongtat; Takada, Hideyuki

doi:10.1145/3341162.3344864

Cited by 3 publications

(1 citation statement)

References 3 publications

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“…More recently, researchers have been investigating the use of Wi-Fi MAC addresses to track riders through a transportation system such as bus systems [6], [7]. Other researchers focused on the pedestrian flow analysis system [8], [9]. Despite all efforts of using Wi-Fi technology, no one proposed a complete framework to build a sensing IoT (Internet of Things) device that is capable of sensing multiple parameters (e.g., speed, battery life, MAC address, phone fingerprint).…”

Section: Related Workmentioning

confidence: 99%

A Framework for Transit Monitoring System Using IoT Technology: Two Case Studies

El-Tawab

Arai

Salman

et al. 2020

2020 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops)

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With the fast increase of wireless technology, more new applications are developed targeting smart cities. It is clear that soon-to-be, each city will be covered with wireless capabilities besides the 5G cellular technology. In a modern city, the bus riders find themselves waiting for a significant amount of time for a bus while checking their smartphones. It is essential to use the numerous amount of data that can be gathered from these devices and surrounding to serve a better quality for the transportation system while preserving the ridership privacy.As to improve the quality of monitoring the transit buses system, we develop a framework using the Internet of Things (IoT) devices. In this paper, a framework is formed, and two case studies are investigated with various implementations. The goal is to use this framework to collect any data that can be used in smart cities to improve planning and increasing bus ridership through better scheduling. A complete comparison between the two case studies is provided with the performance measurement of each technique, and a hybrid methodology is suggested.

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