Core Viewpoint - The rapid development of data assetization is driven by the integration of the Internet of Things (IoT) and Real Data Assets (RDA), which is reshaping the industrial logic of data assetization [1][2][5]. Group 1: Data Assetization and RDA - RDA (Real Data Assets) extends the concept of RWA (Real World Assets) by focusing on the authenticity verification and value enhancement of data, encapsulating operational data from physical assets to improve credit, transparency, and regulatory compliance [5][6]. - The true breakthrough of RDA is fueled by the real-time data continuously released by IoT devices, which serve as a natural "data mine" and "value factory" for RDA [7][8]. - RDA aims to complete the entire process of data ownership, value realization, and financialization, requiring data assets to have clear ownership, traceable sources, and continuous flow to participate in capital market transactions [8][9]. Group 2: Role of IoT in RDA - IoT enables real-time data collection from various physical assets, providing high credibility, strong relevance, and traceable foundational data for RDA, facilitating the transformation of data from a "resource" to an "asset" [7][8]. - The collaboration between IoT and RDA will gradually reveal its synergistic effects in specific application scenarios, such as dynamic transparency in battery lifecycle management and real-time operational data in offshore wind power maintenance [9][10]. Group 3: Financial Implications and Innovations - The integration of IoT, stablecoins, and RDA/RWA creates a closed-loop for machine economy, allowing devices to autonomously participate in value flow and enabling real-time settlement without traditional financial intermediaries [13][14]. - The emergence of stablecoins as a financial infrastructure will significantly enhance autonomous trading and automatic settlement among devices, improving industrial collaboration efficiency [14][15]. - The dynamic credit era will see IoT devices transition from passive data contributors to active data asset owners, leading to a transformation in asset valuation and credit assessment [16][17]. Group 4: Challenges and Future Outlook - The distributed nature of data asset circulation and pricing may introduce new risk management challenges, such as data falsification, necessitating the implementation of hardware trust mechanisms to ensure data authenticity [19][20]. - The evolution of data assetization and pricing power presents both challenges and opportunities for IoT companies, potentially allowing them to transition from "data producers" to "data bankers" [20][21].