ITSC 2025 Paper Abstract

Paper TH-EA-T26.3

Rehman, Anis ur (Griffith University), Sanjari, Mohammad (Griffith University), Du, Bo (Griffith University), Lu, Junwei (Griffith University)

Internet of Things-Based Accident Detection and Hazard Response System for Intelligent Transportation

Scheduled for presentation during the Regular Session "S26b-Motion Planning, Trajectory Optimization, and Control for Autonomous Vehicles" (TH-EA-T26), Thursday, November 20, 2025, 14:10−14:30, Broadbeach 1&2

2025 IEEE 28th International Conference on Intelligent Transportation Systems (ITSC), November 18-21, 2025, Gold Coast, Australia

This information is tentative and subject to change. Compiled on October 18, 2025

Keywords Real-time Motion Planning and Control for Autonomous Vehicles in ITS Networks, IoT-based Traffic Sensors and Real-time Data Processing Systems, IoT for ITS Infrastructure: Smart Traffic Lights, Sensors, and Actuators

Abstract

This research addresses key challenges in accident detection, location tracking and hazard response systems through Internet of Things (IoT). The system is composed of four integrated modules: (1) a fire detection unit that automatically identifies fire incidents, (2) a ventilation system for raised carbon monoxide levels, (3) an automatic braking mechanism for emergencies and (4) accident detection and location tracking module that immediately identifies the accident site for emergency response. The complete prototype is implemented on an Android-controlled electric vehicle robot, utilising ESP32 microcontrollers, global positioning system modules and various sensors. Each component is individually tested and calibrated and experimental results demonstrate the effectiveness of the proposed prototype in real-time accident detection, hazard management, and precise location-based alerting.