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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM41703
Volume:
9 |
2 |
Feb 2025
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
The Bus Crowd Analyzer and Rescheduling System is an innovative solution aimed at improving public transport efficiency by managing passenger flow and rescheduling buses based on real-time crowd data. This system utilizes Arduino-controlled ultrasonic sensors placed at the entry and exit doors of buses to count the number of passengers boarding and alighting. The real-time data collected from the sensors helps monitor bus occupancy levels, enabling the system to predict crowd trends and manage passenger loads efficiently. Additionally, an emergency button is provided to open or close the doors manually during unforeseen circumstances, ensuring safety and accessibility. The system also incorporates GPS tracking to monitor the bus location, allowing authorities to reschedule buses dynamically based on passenger demand and real-time data. An LED display installed on the bus provides passengers with information regarding door status, indicating whether the door is open or closed. This smart integration of technology ensures smoother operations by optimizing bus routes, reducing overcrowding, and improving the overall commuting experience for passengers. By gathering data on passenger numbers and bus location, this system helps to identify overcrowded buses and suggests better scheduling. The goal is to reduce wait times, manage crowd levels, and enhance the overall passenger experience by ensuring that buses are dispatched more efficiently based on real-time demand. This project offers a cost-effective, scalable solution for intelligent transportation systems, contributing to smarter urban mobility. This project proposes a real-time bus crowd analyzer and rescheduling system, leveraging IoT sensors and data analytics to optimize bus operations and enhance passenger experience. The system collects data on bus occupancy, traffic patterns, and passenger demand, analyzing it to identify crowded routes and schedules. Based on insights gained, the system automatically reschedules buses to mitigate congestion, reducing travel times and improving service reliability. The proposed system aims to increase passenger satisfaction, reduce fuel consumption, and optimize bus fleet utilization, providing a smarter, more efficient public transportation solution.
KEYWORDS
Publication Date
2/20/2025
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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