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Smart Health Application for Remote Tracking of Ambulatory Patients
Shariq Aziz Butt1*, Muhammad Waqas Anjum2, Syed Areeb Hassan3, Arindam Garai4 and Edeh Michael Onyema5
1 The University of Lahore, Lahore, Pakistan
2NCBA&E, Lahore, Pakistan
3 The Superior University, Lahore, Pakistan
4 Dept. of Mathematics, Sonarpur Mahavidyalaya, Kolkata, India
5 Dept. of Mathematics and Computer Science, Coal City University, Enugu, Nigeria
Abstract
The Internet of Things (IoT) has amalgam with many fields. One of these is the eHealth monitoring of patients. mHealth monitoring is the most prominent subdomain of eHealth. In mHealth, IoT enables the merging of various devices, including wearables (watch and sensors) and holding (smart mobile phone) devices. Therefore, the application development of mHealth is a penetrated domain in the research community. Different research work exists to develop mHealth applications to monitor different diseases either remotely or physically. Mostly the mHealth applications work with the context of the patient that includes the type of disease and observing the environment. The development of these applications faces several issues, such as security, smartness, decision making, size of the application, and timely actions. This study presents the issue with the health sector and with fuzzy logic while using for health enhancements. Moreover, this work highlights key factors to be addressed in mHealth such as mobilityawareness, location-based medication, and the security of eHealth’s data, distance, and measurement. These all features are very imperative for the health application to improve wellness.
Keywords: Smart health, mobility of patient, remote monitoring, fuzzy concepts for health
2.1 Introduction
Due to the growing of the Internet of Things (IoT), it has created revolutionary inventions and modifications in the health section. It makes healthy smart health in terms of eHealth and mHealth. Due to the technological encroachments the health professional adopts the technology very vastly for monitoring and improve the patients’ health. The internet technology made the patient’s life very easy to monitor and treat. In mHealth and eHealth, IoT enables the merging of various devices, including wearables (watch and sensors) and holding (smart mobile phone) devices. Therefore, the application development of mHealth is a penetrated domain in the research community. Technology also improves health for special kinds of patients who are known as ambulatory patients. These patients need monitoring at their location remotely. It becomes possible with the mHealth application that supports the medical professionals to monitor, treat patients, and send the medication in the case of any abnormality occurrence. It helps the patients to receive tele-medication services from doctors at their location in case of any emergency. But on the other hand instead of all these facilities and supports of internet technology to the health domain still many challenges need to be addressed to enhance the health sector. These challenges include the Emergency Support, Issue with the Chronic Disease Monitoring, Issue with the Tele-Medication, Issue with the Tele-Medication, Mobility of Doctor, Data Storage Issue, Application User Interface issue, and Security Threats. In this chapter, we discuss the health sector, improvements in health, issues with the health domain, and fuzzy-based security solutions to overcome the security issues.
2.2 Literature Work
The prolonged future alongside the increasing multifaceted nature of medication and wellbeing services raises wellbeing costs in general meaningfully. Evolution in pervasive computing applications in blend with the exploitation of modern astute sensor systems may give a premise to help. While the smart wellbeing idea can bolster the awareness of the growing P4-medication (precautionary, sharing, prophetic, and modified), advanced medication creates a lot of high-dimensional, pitifully planned data collections and monstrous actions of formless information [1–3].
Close to the pervasive, multifaceted existence of human administration systems and the reality that front-line drugs are evolving into a data-enhanced science, conventional strategies handling this “enormous data” can no longer hold demand awake, raising the likelihood of unsatisfactory findings being passed on. Consequently, sharp systems are critical for adapting to this growing flood of data [4, 5].
Specifically, the cutting-edge mobile phone methodology, groundbreaking ubiquitous astute sensors, and the reduction of data sparing costs have provoked a persistent illustration of capturing all kinds of close and dear biomedical data over time [9, 10]. In addition, these records contribute to the development of a proportion of indicated longitudinal data, in any case known as time course of action data, in the structure territory.
A significant future pattern is moving the human-insider loop [17], for a valid justification, as the two people and PCs have altogether different qualities, however, both together can undoubtedly be all the more remarkable. Everywhere when scaled this way joins the better of two universes: subjective science with software engineering.
Late specialized advances in sorted out sensors, low-power facilitated circuits, besides, remote correspondences have enabled the structure of simplicity, littler than ordinary, lightweight, and brilliant physiological sensor center points [20]. All of these enhancements leave tremendous wants to our future. Smart conditions will have the alternative to therefore follow our prosperity and will, to some expand, move the reason for care away from clinician’s work environments—thusly in a perfect world be of fiscal relieve of the much over-concentrated on clinical center structures what’s progressive, moving the preventive point of view into the closer view.
From expressly estimating your critical well-being to sensors that fade in the background and track essential steps, there is a shift in perspective.
2.3 Smart Computing for Smart Health for Ambulatory Patients
Intelligent computing gives huge prospects to building up Smart wellbeing benefits as necessary pieces of future consideration ideas [41], which are tested by our maturing society. In this unique situation, specifically brilliant homecare conditions are frequently proliferated as a promising answer for dealing with older or incapacitated individuals. Sensors and new collaboration innovations flawlessly incorporated in such situations offer different structures of customized and setting adjusted average help, including help to complete ordinary exercises, checking individual wellbeing conditions, improving patient security, as well as gaining admittance to social, clinical and crisis frameworks. Brilliant social insurance applications have the potential to deliver clinical, social and conservative benefits to different partners by providing a wide range of administrations. The goals vary from enhancing convenience, encouraging improvement of self-governance to crisis support, including identification, counteraction and forecasting [37, 38].
After a certain age and due to some specific diseases the patients need some care at their locations (at home, at any remote place). These patients are known as ambulatory patients, who after a certain treatment need continuous monitoring using the smart applications. The applications are designed according to every disease and patient’s conditions that include its disease parameters. After setting these parameters, there is a need for remote monitoring done by the application remotely at the patient’s current location. Therefore, currently, the health is growing
