The broad adaptation of cloud computing in healthcare has deeply aroused serious concerns about privacy and security, particularly in managing sensitive patient data. This paper proposes a state-ofthe-art architecture that integrates cloud infrastructure with edge computing for secure healthcare monitoring using Wireless Body Area Networks. The proposed architecture based on an edge node ensures the preservation of privacy through anonymization techniques, which is achieved through the integrated ARX toolkit with advanced techniques including l-diversity, t-closeness, and δ presence. In our framework, a matrix-based access control system was introduced to manage permissions precisely. It also employed the Attribute-Based Signcryption for secure data transmission. The system will process the vital medical parameters through specialized functions at the edge nodes. It adopts a computation approach that balances efficiency in processing with privacy requirements in a very effective way. It integrates fuzzy logic into the architecture for diagnosis in medicine while considering compliance to healthcare regulations. These include a multi-layered mechanism for the preservation of privacy, a lean edge-based processing system for the parameters of medicine, and an integrated access control strategy. This work has contributed to the field of secure healthcare systems by showing how edge computing can improve both privacy and efficiency in the processing of medical data while imposing strict security standards at the cloud.