ItemConference Paper

Towards Smarter Transit Systems: An Artificial Intelligence based IoT Approach

Title
Towards Smarter Transit Systems: An Artificial Intelligence based IoT Approach
Creator
Joy, Salna; Rajesh, Siddharth; Neethu, P.S.; Sumanth, S.; Sagar; Swarup, M.; Dhananjay, R.
Description
Transportation today is paramount, and difficulties such as unreliable bus schedules and overcrowding are still found due to inadequate managerial practices. While cities are confronted with rapid urbanization and population growth, public transit remains a strong reliance of the middle class, especially in India. Individuals are subsequently subjected to overcrowded, and unreliable modes of transit, which lead them to seek private solutions that ultimately leads to increased private vehicle usage, which is directly related to more congestion and pollution. Therefore, utilising an IoT/machine learning based solution which provides commuters with updated bus locations and occupancy via their mobile phones to make more informed travel decisions, thus reducing wait times is proposed. Accurately tracking the buses via gps, is beneficial for providing timely information, where sensors are used for estimating occupancy based on passenger counts. The traffic prediction provided to users is generated from a Random Classifier machine learning model that would otherwise improve commuting efficiency and urban mobility. The model is found to have 98% accurate on cross-validation and 99% on test data, while the average F1-score over various traffic situations is 0.99. The described solution assists transit users by providing up to date service information improving the passengers quality of travel, heightened their sense of safety, and creates a more integrated urban experience, which promotes long-term sustainable development to meet the interconnectedness challenges cities confront with rapid urban expansion. 2025 IEEE.
Source
Proceedings of International Conference on Digital Innovations for Sustainable Solutions, ICDISS 2025;
Date
01-01-2025
Publisher
Institute of Electrical and Electronics Engineers Inc.
Subject
IoT; Machine Learning; Random Forest; Real-time seat tracking; Traffic prediction model
Coverage
Joy S., Department of Computer Science and Engineering, New Horizon College of Engineering, Bengaluru, India; Rajesh S., Department of Electronics and Communication Engineering, New Horizon College of Engineering, Bengaluru, India; Neethu P.S., Department of AIML and Data Science, School of Engineering and Technology, Christ University, Bengaluru, India; Sumanth S., Department of Electronics and Communication Engineering, New Horizon College of Engineering, Bengaluru, India; Sagar, Department of Electrical and Electronics Engineering, New Horizon College of Engineering, Bengaluru, India; Swarup M., Department of Electronics and Communication Engineering, New Horizon College of Engineering, Bengaluru, India; Dhananjay R., Department of Electrical and Electronics Engineering, New Horizon College of Engineering, Bengaluru, India
Rights
Restricted Access; Hardcopy may be available in the library
Relation
ISBN: 979-833155641-9;
Format
online
Language
English
Type
Conference paper

Citation

Joy, Salna; Rajesh, Siddharth; Neethu, P.S.; Sumanth, S.; Sagar; Swarup, M.; Dhananjay, R., “Towards Smarter Transit Systems: An Artificial Intelligence based IoT Approach,” CHRIST (Deemed To Be University) Institutional Repository, accessed June 19, 2026, https://archives.christuniversity.in/items/show/25966.

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