JoWUA

Abstract

In the age of intelligent gadgets and interconnected communities, the widespread surveillance and provision of healthcare to patients are made feasible through the Internet of Medical Things (IoMT). The number of implanted electronic devices that can be monitored remotely is increasing, leading to a rise in the amount and intricacy of biological data. The collected data can offer valuable diagnostic information that can be used to intervene and maintain implanted devices promptly, therefore enhancing the quality of treatment provided. Current remote monitoring processes are not fully using device diagnostics because of the lack of compatibility and data integration between exclusive applications and Digital Health Record (DHR) platforms. Establishing a technology framework that establishes information and enhances interoperability has the potential to strengthen remote monitoring. This article introduces the Medical Data Integration and Interoperability via Remote Monitoring of Healthcare Devices (MDII-RMHD) framework, which facilitates the collaboration of healthcare devices. MDII-RMHD enhances a cloud-based IoMT system using conversion resources at the network's boundary. This is achieved through the use of inquiring and conversion agents. The investigating devices keep track of a list of MDII-RMHD devices on the regional network and allow one device to seek information conversion from another gadget when the requesting device cannot do the task independently. The converting agent transforms the data into the necessary format and returns it to the original entity. These agents enable IoMT devices to utilize their surplus computational capabilities for data translations, reducing the need for cloud access.  Conventional devices are compatible with fog resource managers that have MDII-RMHD support. We assess the MDII-RMHD framework by rigorous experimentation under different scenarios. The obtained results demonstrate that the proposed framework decreases the amount of uplink traffic and enhances the response time. This improvement in response time is significant for real-time healthcare applications.