Year: 2024
Type: article
Abstract: -This study proposes an automated bus seat allocation system using the K-Nearest Neighbors (KNN) model to address inefficiencies in manual allocation. By leveraging historical data on enrollment, routes, and boarding patterns, the system classifies students based on travel habits, enabling personalized seat assignments. It adjusts allocations in real-time, optimizing bus usage, improving seat utilization, and enhancing student satisfaction. The system reduces administrative workload and ensures buses are neither underutilized nor overcrowded. This approach promotes a smoother and more organized commuting experience for students.
Authors: M Ratnakar Babu -, K.Spandana -, C.Anusha -, D.Srujana -, S.Aishwarya -
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4405979840