Dynamic data monetization model for ITS based on Distributed Ledger Technologies

The rise of Intelligent Transportation Systems (ITS) and the Internet of Vehicles (IoV) has introduced significant
opportunities to improve transportation efficiency and safety. The exponential growth of vehicular data offers multiple
oportunities for new services and products. However, utilization of this data poses challenges related to privacy,
scalability, and effective data monetization. This paper proposes a decentralized and scalable data monetization
model for vehicular data, integrating Distributed Ledger Technologies (DLT). DLT ensures secure, transparent, and
tamper-proof transactions. The proposed model introduces a Reverse Data Monetization Logic and Dynamic Pricing
Mechanism to address the real-time valuation of vehicular data based on its contextual relevance and utility. Key
components include a Data Fabric Layer for decentralized storage and computation, a DLT-Enabled Meta-Space for
smart contracts and data valuation, and incentive-driven stakeholder collaboration mechanisms. A scenario-based
analysis demonstrates how the model could be applied to real-time traffic management, showcasing its ability to
foster trust, ensure privacy, and optimize stakeholder engagement in a decentralized data marketplace. By bridging
existing research gaps, this work provides a robust, secure, and economically viable approach to unlocking the value
of vehicular data while ensuring privacy and trust within ITS ecosystems.