Year: 2025
Type: article
Abstract: The "Intelligent Transit Management and Capacity Insights" project offers a novel way to deal with the problems of crowding and discomfort among passengers on public transit. The technology offers real-time monitoring of seat occupancy on buses by utilizing cameras linked to a Raspberry Pi and machine learning techniques. The technology precisely counts the number of occupied seats by evaluating the images taken by the cameras. This information is then subtracted from the overall seating capacity to provide correct information about seat availability. This feature greatly improves passenger comfort while traveling in addition to helping to reduce congestion. Because of the system's compatibility with Raspberry Pi, existing bus infrastructures may be seamlessly integrated, guaranteeing dependable data processing. Additionally, the system's use of machine learning enables steady performance and accuracy improvements over time. By combining advanced technologies such as machine learning, cameras, and Raspberry Pi, this integrated solution represents a significant step forward in the enhancement of public transportation systems, ultimately leading to improved operational efficiency, safety measures, and passenger satisfaction.
Author: T. H. Akshaya
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4408770466