Harmonized Data Drive: Standardizing and Unifying Smart Car Information Storage for Enhanced Forensics and Interoperability

The proliferation of smart car technology has intro-duced significant challenges in managing high-volume, heteroge-neous data, including issues with interoperability, secure storage, and real-time analytics. This paper proposes the Harmonized Data Drive (HDD), a unified and scalable framework designed to address these challenges through efficient data ingestion, hierarchical metadata structuring, and end-to-end encryption. HDD ensures data integrity, accessibility, and compliance with regulatory standards, making it particularly valuable for applications in digital forensics and automotive data analysis. The framework's performance was evaluated using the NYC Yellow Taxi Trip Record dataset, showcasing its ability to achieve ingestion rates of approximately 1 million rows per second while maintaining a minimal storage overhead of approximately 19% from encryption. HDD also supports real-time query execution with an average latency of 0.65-1.23 seconds per query. Compared to existing systems, HDD demonstrates better scalability, forensic usability, and analytical capabilities while offering robust interoperability via standardized export formats like JSON and Parquet. These results position HDD as a robust and future-ready solution for addressing the complexities of smart car data ecosystems.