Vehicle Prediction for BUS Identification Output from our Route Testing Real Time Algorithm

Traffic generation in Indian cities is of a mixed nature, comprising over a dozen types of vehicles that can be broadly categorized into slow-moving and fast-moving vehicles. This study highlights the challenges associated with the inefficient operation of the existing bus system. GPS and mobile networks form integral components of the current system, enabling data storage and management using PostgreSQL. The system provides robust and reliable data to fulfill requests from other software applications. Operating on cloud platforms, it is compatible with all major web browsers. The proposed algorithm continuously tracks the real-time location of buses and their corresponding WMS (Web Map Service) location, alerting users through marker notifications. This paper also explores measures to evaluate the efficiency and effectiveness of bus services. Recognizing that an inadequate public transport system impedes economic growth and development, this study emphasizes the need to enhance the overall quality and accessibility of public transportation. The findings aim to improve the operational efficiency of bus services, contributing to a more effective and sustainable transport system.

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Publication Details

Published
2024-12-11
DOI
https://doi.org/10.1109/icscna63714.2024.10864046
Citations
2
Primary Topic
Traffic Prediction and Management Techniques
Type
article
Field-Weighted Citation Impact
0.53
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Vehicle Prediction for BUS Identification Output from our Route Testing Real Time Algorithm

J. Kavitha, R. Ramya, Joel Dickson, K. Udayakumar et al.
2 citations
Traffic Prediction and Management Techniques
0.53
article

Vehicle Prediction for BUS Identification Output from our Route Testing Real Time Algorithm

J. Kavitha, R. Ramya, Joel Dickson, K. Udayakumar, L. Sharmila, M. Misba
article en
2 citations

Abstract

Traffic generation in Indian cities is of a mixed nature, comprising over a dozen types of vehicles that can be broadly categorized into slow-moving and fast-moving vehicles. This study highlights the challenges associated with the inefficient operation of the existing bus system. GPS and mobile networks form integral components of the current system, enabling data storage and management using PostgreSQL. The system provides robust and reliable data to fulfill requests from other software applications. Operating on cloud platforms, it is compatible with all major web browsers. The proposed algorithm continuously tracks the real-time location of buses and their corresponding WMS (Web Map Service) location, alerting users through marker notifications. This paper also explores measures to evaluate the efficiency and effectiveness of bus services. Recognizing that an inadequate public transport system impedes economic growth and development, this study emphasizes the need to enhance the overall quality and accessibility of public transportation. The findings aim to improve the operational efficiency of bus services, contributing to a more effective and sustainable transport system.

Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology (IN), Saint Joseph's College (US)
Openalex Percentile: Top 32%
Traffic Prediction and Management Techniques
0.53
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Vehicle Prediction for BUS Identification Output from our Route Testing Real Time Algorithm — J. Kavitha, R. Ramya, et al. · (2024) | TGRS Research Map | TGRS