Smart College Bus Seat Allocation System Using KNN Classification

-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

Publication Details

Journal
International Journal For Multidisciplinary Research
Published
2024-12-31
DOI
https://doi.org/10.36948/ijfmr.2024.v06i06.34008
Primary Topic
Urban Transport and Accessibility
Type
article
Field-Weighted Citation Impact
0.00
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article

Smart College Bus Seat Allocation System Using KNN Classification

C. S. Anusha, S Aishwarya, Darla Srujana, K Spandana et al.
International Journal For Multidisciplinary Research
Urban Transport and Accessibility
article

Smart College Bus Seat Allocation System Using KNN Classification

C. S. Anusha, S Aishwarya, Darla Srujana, K Spandana, Manoj Babu
article en

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.

International Journal For Multidisciplinary ResearchVol. 6(6)
Openalex Percentile: Top 77%
Urban Transport and Accessibility
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