A Systematic Survey on Fog and IoT Driven Healthcare: Open Challenges and Research Issues

Technological advancements have made it possible to monitor, diagnose, and treat patients remotely. The vital signs of patients can now be collected with the help of Internet of Things (IoT)-based wearable sensor devices and then uploaded on to a fog server for processing and access by physicians for recommending prescriptions and treating patients through the Internet of Medical Things (IoMT) devices. This research presents the outcome of a survey conducted on healthcare integrated with fog computing and IoT to help researchers understand the techniques, technologies and performance parameters. A comparison of existing research focusing on technologies, procedures, and findings has been presented to investigate several aspects of fog computing in healthcare IoT-based systems, such as increased temporal complexity, storage capacity, scalability, bandwidth, and latency. Additionally, strategies, tools, and sensors used in various diseases such as heart disease, chronic disease, chikungunya viral infection, blood pressure, body temperature, pulse rate, diabetes, and type 2 diabetes have been compared.

Automated summary

Advancements in technology have enabled remote monitoring, diagnosis, and treatment of patients. Through the use of Internet of Things (IoT) and fog computing, physicians can access and process patients' vital signs remotely to recommend prescriptions and treatment plans. This research investigates the techniques, technologies, and performance parameters of fog computing in healthcare IoT-based systems, and compares strategies, tools, and sensors used in various diseases.