AI-Powered IoT Framework for Vehicle Breakdown Alerts: Advancing Digital Social Transformation in Intelligent Transportation Systems

Abstract

Purpose— Artificial Intelligence (AI) and Internet of Things (IoT) technologies are changing the transportation systems into intelligent, socially connected ecosystems. This study presents an AI-empowered Internet of Vehicles (IoV) framework for real-time vehicle breakdown information sharing, designed to enhance digital social transformation in mobility.

Study Design/methodology/approach— The proposed model enables vehicles to detect breakdown events via onboard sensors and AI-driven diagnostics, automatically generating geolocation-based alerts. These alerts are transmitted through vehicular clouds and roadside units (RSUs) to other vehicles, service stations, and the driver’s designated social network (e.g., family, friends, office contacts). The system was tested using twenty simulated vehicles in an urban setting using the Simulation of Urban Mobility (SUMO) platform and OpenStreetMap (OSM) data.

Findings— Findings indicate that the AI-IoT solution is highly effective in terms of reducing the response time and enhancing communication coverage as opposed to traditional breakdown reporting techniques.

Research Practical Implications— The framework explains how the AI can augment the Social Internet of Vehicles (SIoV) by attaining context-aware, proactive, and socially connected safety interventions. It is designed to enhance digital social transformation in mobility.

Originality/value— This study presents an AI-empowered Internet of Vehicles (IoV) framework for real-time vehicle breakdown information sharing. The research falls within the new field of Intelligent Transportation Systems (ITS) based on AI and the role of socially intelligent networks in the evolution of transportation safety, efficiency, and user experience.