Framework for Passenger Seat Availability Using Face Detection in Passenger Bus
This work addresses traffic management and passenger convenience issues in intelligent transportation systems, but it is incremental as it applies existing face detection methods to a new domain.
The authors tackled the problem of passenger seat unavailability in buses by proposing a face detection framework to count empty and filled seats, achieving 90% accuracy in live tests.
Advancements in Intelligent Transportation System (IES) improve passenger traveling by providing information systems for bus arrival time and counting the number of passengers and buses in cities. Passengers still face bus waiting and seat unavailability issues which have adverse effects on traffic management and controlling authority. We propose a Face Detection based Framework (FDF) to determine passenger seat availability in a camera-equipped bus through face detection which is based on background subtraction to count empty, filled, and total seats. FDF has an integrated smartphone Passenger Application (PA) to identify the nearest bus stop. We evaluate FDF in a live test environment and results show that it gives 90% accuracy. We believe our results have the potential to address traffic management concerns and assist passengers to save their valuable time