A Design of HFMCD Model to Establish the Sustainable Healthcare System

Interoperability, security, and privacy of patient data in healthcare systems may all be enhanced by the incorporation of Blockchain technology and the Internet of Things (IoT) into a secure medical infrastructure. To address the unique requirements and challenges faced by the healthcare sector, this innovative framework makes use of the benefits of both blockchain (BC), fuzzy logic and Internet of Things (IoT) technology. This study suggests a deep learning and nature-inspired algorithm-enhanced blockchain-based safe medical care system powered by the Internet of Things. In the first part of the investigation, a user identification system and secure data storage system based on blockchain are introduced, together with the ability to forecast health state. After the data has been min-max normalised, the Dwarf Mongoose Optimisation (DMO) approach facilitates feature extraction and selection. The condition of health is then divided into normal and pathological states utilizing the Improved Bumble Bee Mating Optimisation Algorithm and Bi-Long Short-Term Memory (IBBMO-Bi-LSTM) and hybrid fuzzy evaluation. This ensures that medical data is safely preserved using blockchain technology. Any aberrant measurements are temporarily stored for later use on the patient’s allocated blockchain. The suggested approach is rigorously validated against many baseline techniques, exhibiting improved encryption and decryption efficiency and accuracy rates. Through the use of these novel techniques, the framework achieves an elevated degree of security, hence supporting the integrity and confidentiality of medical records.