Open AccessLow‐cost bus seating information technology system
Author(s) -
Murdan Anshu Prakash,
Bucktowar Vicky,
Oree Vishwamitra,
Enoch Marcus P.
Publication year - 2020
Publication title -
iet intelligent transport systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.579
H-Index - 45
eISSN - 1751-9578
pISSN - 1751-956X
DOI - 10.1049/iet-its.2019.0529
Subject(s) - upload , usb , raspberry pi , embedded system , computer science , automatic vehicle location , vehicle tracking system , can bus , system bus , real time computing , microcomputer , interface (matter) , engineering , operating system , computer hardware , internet of things , global positioning system , telecommunications , software , chip , bubble , segmentation , artificial intelligence , maximum bubble pressure method
Public transport operators often struggle to provide a reliable and efficient transport service. A lack of comprehensive real‐time operational data is often cited as a major cause for this state of things. In this study, the authors report on the design, implementation and testing of an Internet of Things‐based system, named Bus Seating Information Technology system, which dynamically determines vehicle occupancy while the bus is in service. It uses an array of sensors for detecting events in the vehicle: infrared sensors ascertain whether passengers are entering or leaving the bus; force‐sensitive resistors facilitate seat‐occupancy detection; a Global Positioning System shield in conjunction with a Raspberry Pi microcomputer enables real‐time tracking of the bus; and a USB camera connected to the same Raspberry Pi assist in cross‐checking and validating the preceding information. The data collected is uploaded to an online IoT platform (thinger.io), through 3G or 4G if available, and can be visualised via an android app as well as through a desktop computer user interface. The planned functions of the system were tested in a 20‐seater bus. Results showed that the system can track the vehicle location, as well as vehicle occupancy in real‐time in most cases.