Abstract: With the advent of new sensor device designs, IoT based medical applications are increasingly being employed. This study introduces BlockFaaS: a Blockchain-assisted serverless framework that incorporates advanced AI models in latency sensitive healthcare applications with confidentiality, energy efficiency, and real-time decision-making. This framework combines the structure of AIBLOCK with dynamic sharding and zero knowledge proofs to make the framework strongly scalable with health-assured data inviolability with HealthFaaS, a serverless platform for cardiovascular risk detection. Explainable AI and federated learning models are introduced into the system to retain an equilibrium between data privacy and interpretability. All layers of communication use the Transport Layer Security protocol to ensure security. This proposed system is validated by new performance metrics such as real-time response rates and energy consumption, proving to be superior to the existing HealthFaaS and AIBLOCK technologies.

Akash Ghosh, Abhraneel Dalui, Lalbihari Barik, Jatinderkumar R. Saini, Sunil Kumar Sharma, Bibhuti Bhusan Dash, Satyendr Singh, Namita Dash, Susmita Patra and Sudhansu Shekhar Patra, “Blockchain-Assisted Serverless Framework for AI-Driven Healthcare Applications” International Journal of Advanced Computer Science and Applications(IJACSA), 16(5), 2025. http://dx.doi.org/10.14569/IJACSA.2025.0160546

@article{Ghosh2025,
title = {Blockchain-Assisted Serverless Framework for AI-Driven Healthcare Applications},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2025.0160546},
url = {http://dx.doi.org/10.14569/IJACSA.2025.0160546},
year = {2025},
publisher = {The Science and Information Organization},
volume = {16},
number = {5},
author = {Akash Ghosh and Abhraneel Dalui and Lalbihari Barik and Jatinderkumar R. Saini and Sunil Kumar Sharma and Bibhuti Bhusan Dash and Satyendr Singh and Namita Dash and Susmita Patra and Sudhansu Shekhar Patra}
}