ADAPTIVE URBAN TRANSIT OPTIMIZATION VIA REAL-TIME PASSENGER FLOW INTELLIGENCE

Mrs.G.Vijayalaxmi , CHETLA ROSHINI , AMANCHA DHRUVATEJA , BISWAS VISHESH SANJAY , BISWAS VISHESH SANJAY

IoT, RFID, Passenger Flow Monitoring, ESP8266, Smart Transit System, Cloud Analytics, Automatic Passenger Counting

This system employs advanced sensing technologies such as RFID readers and passenger load sensors to automatically monitor and regulate bus occupancy, route scheduling, and station-level crowd distribution based on live transit conditions and commuter behaviour. The prototype integrates a microcontroller, OLED display module, and cloud connectivity to create a cost-effective, energy-efficient, and commuter-friendly solution. It ensures compliance with modern smart city transit standards, including Automatic Passenger Counting (APC), while enhancing route visibility, timely dispatching, and operational convenience for transit operators and passengers. The Adaptive Urban Transit Optimization System is designed to intelligently manage all transit monitoring functions in a public transport vehicle without the need for manual intervention. Using an RFID-based passenger identification system, the solution continuously tracks passenger boarding and alighting events and transmits occupancy data to a cloud platform for real-time analytics. This feature is particularly useful when managing peak-hour surges, station bottlenecks, or route diversions where passenger flow shifts suddenly. A passenger load evaluation algorithm is employed to detect overcrowding thresholds or underutilization patterns, automatically triggering route optimization alerts dispatched to transit control centers. The system can also be integrated with the vehicle's ignition and GPS modules to ensure that Automatic Passenger Counting (APC) is active from the moment the bus departs, complying with smart transit norms and enabling dynamic scheduling decisions.

Volume 14 Issue 4, April-2026

Pages : i126-i134