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Cloud-Integrated Smart Traffic Control for Ambulance Prioritization Using IoT and Modular Microcontrollers

Nishad Amonkar, Mayuresh Govekar, Omkar Naik , Gaurav Nemlekar, Prathamesh Bhat, Needhi Gaonkar

Electronics and Communication , Agnel Institute of Technology and Design.

Abstract - Traffic congestion in cities creates major delays for emergency response units which reduces essential life-saving operations. The research paper develops a strong cloud-based IoT system that optimizes ambulance transit through controlled traffic intersections. The system includes GPS tracking through a mobile application and cloud processing via AWS as well as dynamic traffic signal control through ESP32 and Arduino Uno microcontrollers. When drivers successfully log in their app sends GPS data to AWS which identifies the closest intersection and establishes lane prioritization. The ESP32 module receives commands to trigger signal adjustments through the Arduino Uno for unobstructed ambulance passage. The system underwent extensive testing in controlled environments to evaluate both latency performance and reliability and failure response capabilities. The system demonstrates effective ambulance movement with two main challenges regarding multiple intersection control and network connection needs. The current system architecture shows potential for development into a scalable smart city emergency services platform.

Key Words:  Emergency Vehicle Prioritization, Ambulance Transit Optimization, Smart Traffic Control, IoT-Based System , Cloud Computing , AWS Integration, GPS Tracking , ESP32 , Arduino Uno , Urban Mobility , Lane Clearance Automation , Real-Time Traffic Management , Smart City Infrastructure, Vehicle-to-Infrastructure Communication (V2I) , Intelligent Transportation Systems (ITS)