Title: Internet of things and cloud computing in medical devices

Body sensors or wearable sensors are now normally used as ingestible, wearable andimplantable devices for medical diagnosis and uninterrupted physiological monitoring.However, they usually have limited resources. Recent advancements in technologies provide apossible solution to overcome the resource limitation of these devices by connecting them withsmart mobiles and cloud services. To estimate the feasibility of the cloud-enabled body sensornetworks, this paper presents simulation results on testing the feasibility of ۲۴-hour operatingtime and parallel user support for the cloud-enabled applications. A cloud is a new paradigmfor IoT-based WSN۱ that overcomes several limitations of traditional WSN and decouples theowners of the physical sensors from the network users. This paper proposes a cloud-basedInternet of Medical Devices (IoMD), a novel architecture for the healthcare system to validatethe efficiency of sensor-cloud virtualization technique. IoT, cloud computing and fog are thethree key technologies that make up the framework outlined in this paper. IoT and medicaldevices are integrated into our cloud-based architecture, and deep learning algorithms are usedto process the collected data. A deep learning neural network method called GenerativeAdversarial Network (GAN) model that runs in both fog and cloud platforms and is capable ofprocessing massive data in a fast and efficient manner. The suggested GAN is trained on a real-data set from the UCI Machine Learning Repository.

کلیدواژه ها:

cloud-based internet of medical device ، cloud computing ، wirelesssensor network ، sensor data and fog computing.