The health monitoring system has become increasingly popular in recent years due to its unique features and wide range of medical applications. The OneLife IoT-based self-monitoring healthcare system is a smart health monitoring system to detect and predict diseases by monitoring various health-related data such as body temperature, pulse rate, heartbeat, blood pressure, oxygen levels, and sugar levels. It helps track a patient's specific metrics every day and provides analysis for a week, month, and year to predict the patient's condition. It is implemented and tested on two groups of five patients each and achieves accuracy by measuring the general parameters in a controlled environment. It provides the users with the measured results, on LCD including heart rate, blood sugar level, temperature, etc. By incorporating internet of things-based self-monitoring healthcare systems into educational systems, the health of the students can be easily monitored.
TopIntroduction
Ensuring human health is a top priority for a good quality of life. With an increasing number of people suffering from chronic diseases, it is crucial to monitor physiological indicators of health to provide early medical care and potentially save lives. In-patient care costs are on the rise due to the growing demand for modern resources from medical service providers. Additionally, factors such as aging, daily workload, stress, anxiety, and other diseases force people to take medication less frequently, leading to longer recovery times. Patient health monitoring is becoming increasingly important to leverage the resources of current technology. Vital factors, such as pulse rate, body temperature, heart rate, heartbeat, oxygen levels, blood pressure, and sugar, are physiological characteristics that indicate a person’s health status. These measures can be used to detect any health problems (Ball et al., 2023; El-Rashid et al., 2020; Harun et al., 2020; Hongru & Goyea, 2020; Hypoxemia, 2020; Lee et al., 2017; Pourhomayoun et al., 2016; Rizzo, 2020; Serpanos & Wolf, 2019; Thailand Medical News, n.d.). The current Internet of Things (IoT) technology and the increasing number of mobile users worldwide enable remote monitoring of a patient’s health. Any sensitive patient information must be kept secure in such healthcare systems.
In present days, healthcare systems are frequently utilizing IoT technology. This process involves the collection, storage, and maintenance of sensitive patient data in electronic health record systems through the advantages of IoT networks (Arulananth & Shilpa, 2017; Evans, 2020; Islam et al., 2020; Khan, 2020; Wrist worn pulse oximeter, n.d.). In an IoT environment, biomedical healthcare systems use sensor technologies and microcontroller-based engineering systems to transfer patient data to any remote location. This data is then utilized to monitor the patient’s energy levels and notify the doctor or other nurses if anything seems abnormal (Components101., n.d.-c; Pierleoni et al., 2014; Prasath, 2013; Reza et al., 2017; Senith Electronics, n.d.; Srinivasan et al., 2020; Srividya, & Satyanarayana,, 2018; Sutradhar et al., 2019; Tamilselvi, 2020; Yatsenkov, 2018). These proactive technology-assisted self-monitoring measures are aimed at improving the medical services offered by healthcare units.
The IoT-based Health Monitoring System (HMS) involves self-monitoring of the user using a smartphone application to keep track of vital body parameters such as body temperature, pulse rate, blood pressure, heartbeat, heart rate, and sugar levels. The gathered data from sensors is analyzed and processed by the doctor for diagnosis and treatment. Display devices such as Liquid Crystal Displays (LCDs) or Light-Emitting Diodes (LEDs) exhibit the sensor data, which is a part of the IoT system. There are various systems available to monitor chronic illnesses (Components101, n.d.-a; Components101, n.d.-b; Dharmik et al., 2021; Simel et al., 2020). For instance, the Self-Monitoring Healthcare System (SMHS) is used to check the glucose level in diabetes blood. The parameters such as heartbeat, pulse rate, and heart rate are used to determine the state of the heart and how well it is functioning. Additionally, a blood oxygen level test is used to assess lung operation and determine the blood’s acid-base balance. Oxygen levels are used to identify underlying health issues. On the other side, the IoT-based self-monitoring healthcare systems play a crucial role in shaping the future of learning as one continues to embrace innovation in education. So, integrating IoT-based self-monitoring healthcare systems into educational settings can improve education in several ways through intelligent systems and data-driven instruction (Dharmik et al., 2021; Gope & Hwang, 2015). Here are a few main benefits: