Design and Implementation of Smart E-Health System Based on Cloud Computing to Monitor the Vital Signs in Real-Time and Measurements Validation

Abstract

Wearable devices used to monitor patients are classified as part of mobile health, one of the branches of e-health. They are widely used to monitor the vital signs of patients outside of the health institutions environment. The aim of this paper is to design a device that can be worn at low cost and of small size to provide comfort to the patient. The accuracy of this device should be high compared to the benchmark. Also, this study takes into account real-time remote monitoring based on the wireless sensor network and cloud computing where cloud computing is integrated with the Internet of Things to solve the problem of the flow of the huge amount of data. The Wearable Remote Vital Signs Monitoring System (WRVSMS) was manufactured by a printed circuit board, where the ESP01, MAX30100, NTC, OLED, and Li-ion battery were used. The WRVSMS was connected to the cloud server via the HTTP protocol where the data was stored and analysed. The WRVSMS works on basis the combining data of vital signs through which the stakeholders to whom the alert is sent will be assigned based on the patient‘s case where the alert will be sent, which is short message to the stakeholders that are important in rescuing the patient when the patient‘s vital signs are outside threshold. The results showed that the device is 99.37% accurate and statistical analysis was performed to test the error.

IoT + DBMS = Periodic Summary of the Health Status of Remote Patients

“…The field m_description comprises the following data: FName, LName, YoB (Year of Birth), Weight, and Height, while the field m_value collects data about temp (temperature), HRate (heart rate), SPO2 (oxygen saturation), SBP (Systolic Blood Pressure), and DBP (Diastolic Blood Pressure). This set of human physiological parameters is systematically taken into account in studies concerning the monitoring of patients' health status (see, for instance, [8][9][10]). The measures were taken over the 24 h of a single day (6 June 2023); moreover (without loss of generality), the timestamps are the same for each patient (i.e., '2023-06-01 00:01:01', '2023-06-01 01:01:01', and so on).…”

Real-time Face Recognition for Enhanced Law-Enforcement Services in Cities

“…Raspberry Pi3 Model B, which is similar in size to a credit card and could be connected to a TV, along with a keyboard and a mouse [3], could be thought of as a little Mastercard-sized PC. A camera module could be thought of as a small PCB, which provides connection for the camera linked through cable for taking still images or videos in real time [4] [5].…”

Smart Door for Handicapped People via Face Recognition and Voice Command Technique

“…The raspberry pi can be considered as a small Mastercard measured PC, the Raspberry Pi3 Model B can be a PC the same size as a credit card which can be connected to the television, as well as a mouse and keyboard [3]. The Camera Module can be considered as a little PCB that supplies connection for a camera that is connected via cable for shooting fixed pictures or videos and it gives voice commands, which is suitable for real-time [4], applications of smart home [5].…”