Platform framework for blockchain-enhanced healthcare AIoT systems

Blockchain and Artificial Intelligence (AI) technologies offer immense potential when integrated with the Internet of Things (IoT) across multiple sectors, including healthcare. Blockchain remains an active research topic, particularly regarding its scalability and the time efficiency of its verification process. However, limited attention has been given to the practical challenges of integrating blockchain with AIoT (AI with IoT) in healthcare applications, that face persistent privacy and security challenges due to the sensitive nature of personal data. These challenges include time-consuming data retrieval and increased memory usage, which impact the practical implementation of blockchain-based AIoT systems. To address these challenges, this paper proposes a platform framework that integrates edge AI with a sharding-based proof-of-authority (PoA) blockchain for healthcare systems. The proposed framework incorporates three key strategies for blockchain applications in healthcare: 1) a blockchain version manager for AI adaptors, 2) IoT preprocessing for blockchain data management, and 3) the Shall Fragment Cube (SFC) approach for blockchain decision archiving. Theoretical analysis demonstrates that the use of a sharding blockchain significantly enhances memory efficiency and reduces data retrieval time in healthcare AIoT applications. Moreover, simulation results indicate that the SFC approach reduces data retrieval time by approximately 50%. Thus, the proposed system design provides a practical and reliable solution for integrating blockchain into future healthcare AIoT systems, unlocking transformative potential across multiple application domains.