Proceedings of International Conference on Applied Innovation in IT
2025/07/26, Volume 13, Issue 3, pp.105-113

Blockchain-Enabled Data Analytics-Based Demand Service Optimization for Vehicular Safety


La Ode Bariun, Haeruddin Haeruddin and Mahmoud A. Mahmoud


Abstract: Vehicle safety and demand optimization are being explored using blockchain-enabled data analytics due to the rapid growth of connected vehicle technologies. This system establishes a robust and scalable framework for next-generation intelligent transportation systems (ITS), leveraging cutting-edge data analytics, IoT integration, and decentralized technologies to optimize resource allocation, enhance operational efficiency, and strengthen safety protocols. By harnessing real-time data processing and predictive modeling, the framework enables dynamic traffic flow optimization, reduces congestion, and minimizes environmental impact. Furthermore, the paper explores the integration of blockchain technology within vehicular networks, highlighting its transformative potential in ensuring secure, tamper-proof data exchange among vehicles, infrastructure, and service providers. Key applications include enhanced collision avoidance systems, automated toll collection, and fraud-resistant vehicle-to-everything (V2X) communication. The study also investigates blockchain’s role in improving emergency response coordination by enabling instant, verifiable data sharing between first responders, traffic authorities, and connected vehicles. These advancements not only increase road safety and traffic management precision but also lay the foundation for fully autonomous and decentralized transportation ecosystems in smart cities.

Keywords: Blockchain Technology, Vehicular Safety, Data Analytics, Demand Service Optimization, Intelligent Transportation Systems.

DOI: Under Indexing

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