Automatic Seat Identification System in Smart Transport using IoT and Image Processing

This project presents an innovative application of Raspberry Pi interfaced with a camera for passenger counting on buses using facial recognition technology. The system utilizes computer vision to identify and count the number of passengers on board by detecting and tracking faces. Once the counting process is complete, the Raspberry Pi controller uploads the passenger count data to a web server for further analysis and reporting. The core component of the system is a high-resolution camera installed inside the bus, continuously capturing images of passengers. The Raspberry Pi processes these images, employing facial recognition algorithms to identify individual faces and count the number of unique individuals present. This approach eliminates the need for manual counting, reducing errors and providing a more efficient and automated solution. And LCD present in the system will display the values.

After the passenger count is determined, the Raspberry Pi establishes a connection with a web server via the internet. The controller then securely uploads the passenger count data to the server's. This data can be accessed and analysed remotely, enabling transportation authorities to monitor bus occupancy levels, optimize routes, and improve passenger services. This Raspberry Pi-based bus passenger counting system offers, efficient, and cost effective solution for public transportation agencies to gather vital data for operational and planning purposes. It not only streamlines the passenger counting process but also contributes to enhanced public transportation services and improved overall efficiency in urban mobility management.

Keywords: Raspberry pi, camera, Bus Seat, Facial Recognition.