Internet of Things for Healthcare Using Effects of Mobile Computing: A Systematic Literature Review <s> S. No <s> Drug compliance and adverse drug reactions (ADR) are two of the most important issues regarding patient safety throughout the worldwide healthcare sector. ADR prevalence is 6.7 % throughout hospitals worldwide, with an international death rate of 0.32 % of the total of the patients. This rate is even higher in Ambient Assisted Living environments, where 15 % of the patients suffer clinically significant interactions due to patient non-compliance to drug dosage and schedule of intake in addition to suffering from polypharmacy. These instances increase with age and cause risks of drug interactions, adverse effects, and toxicity. However, with a tight follow-up of the drug treatment, complications of incorrect drug use can be reduced. For that purpose, we propose an innovative system based on the Internet of Things (IoT) for the drug identification and the monitoring of medication. IoT is applied to examine drugs in order to fulfill treatment, to detect harmful side effects of pharmaceutical excipients, allergies, liver/renal contradictions, and harmful side effects during pregnancy. The IoT design acknowledges that the aforementioned problems are worldwide so the solution supports several IoT identification technologies: barcode, Radio Frequency Identification, Near Field Communication, and a new solution developed for low-income countries based on IrDA in collaboration with the World Health Organization. These technologies are integrated in personal devices such as smart-phones, PDAs, PCs, and in our IoT-based personal healthcare device called Movital. <s> BIB001 </s> Internet of Things for Healthcare Using Effects of Mobile Computing: A Systematic Literature Review <s> S. No <s> Pervasive healthcare applications utilizing body sensor networks generate a vast amount of data that need to be managed and stored for processing and future usage. Cloud computing among with the Internet of Things (IoT) concept is a new trend for efficient managing and processing of sensor data online. This paper presents a platform based on Cloud Computing for management of mobile and wearable healthcare sensors, demonstrating this way the IoT paradigm applied on pervasive healthcare. <s> BIB002 </s> Internet of Things for Healthcare Using Effects of Mobile Computing: A Systematic Literature Review <s> S. No <s> Childhood obesity has become a major problem around the world. In many cases children develop unhealthy eating patterns, resulting in excess energy intake, because they eat alone without their parents or teachers advice. In this paper we propose a mobile health (mhealth) platform intended to increase children's health awareness by tracking their food intake and sending proper notifications and messages based on their food choices. The platform is based on the Internet of Things concept in order to facilitate capturing food information using intelligent tags instead of doing manual entries. <s> BIB003 </s> Internet of Things for Healthcare Using Effects of Mobile Computing: A Systematic Literature Review <s> S. No <s> In-home healthcare services based on the Internet-of-Things (IoT) have big potential in business. To exploit this opportunity, an ecosystem should be established first. Technical solutions should aim for a cooperative ecosystem by addressing the interoperability, security, and system integration. In this paper, we propose an ecosystem-driven design strategy and apply it in the design of an open-platform based solution. In particular, a cooperative ecosystem is formulated by merging the traditional healthcare and mobile internet ecosystems. Utilizing the existing standardization efforts, the interfaces between actors can be simplified. To balance the control and avoid monopoly, ecosystem-driven security schemes are proposed including the public-based authentication, repository-based credential management, SE-based cryptography, and non-invasive message handover. In order to achieve the economy of scale, an open platform-based in-home healthcare station is proposed. The proposed methodology and solution are demonstrated in implemented prototype system and field trials. <s> BIB004 </s> Internet of Things for Healthcare Using Effects of Mobile Computing: A Systematic Literature Review <s> S. No <s> The paper outlines the application of ZigBee and Radio Frequency Identification (RFID) technologies using the Internet of Things (IoT) in a healthcare environment. The Internet of Things, RFID, ZigBee and Cloud computing are emerging technologies in computing, and the association between them can be used to control complex human interaction and to reduce cost and task times through connecting Smart devices to the Internet. The extraordinary growth of those technologies has made it possible to identify, locate and track objects in various environments. These technologies could allow pervasive computing systems to be more efficiently managed in terms of locating and tracking of objects in future operations. RFID technology is a non-contact identification that does not require direct line of sight to the target object. RFID is cheap ( <s> BIB005 </s> Internet of Things for Healthcare Using Effects of Mobile Computing: A Systematic Literature Review <s> S. No <s> In recent years, we have witnessed a rapid surge in assisted living technologies due to a rapidly aging society. The aging population, the increasing cost of formal health care, the caregiver burden, and the importance that the individuals place on living independently, all motivate development of innovative-assisted living technologies for safe and independent aging. In this survey, we will summarize the emergence of `ambient-assisted living” (AAL) tools for older adults based on ambient intelligence paradigm. We will summarize the state-of-the-art AAL technologies, tools, and techniques, and we will look at current and future challenges. <s> BIB006 </s> Internet of Things for Healthcare Using Effects of Mobile Computing: A Systematic Literature Review <s> S. No <s> The proliferation of mobile devices, ubiquitous internet, and cloud computing has sparked a new era of Internet of Things (IoT), thus allowing researchers to create application-specific solutions based on the interconnection between physical objects and the internet. Recently, wearable devices are rapidly emerging and forming a new segment-“Wearable IoT (WIoT)” due to their capability of sensing, computing and communication. Future generations of WIoT promise to transform the healthcare sector, wherein individuals are seamlessly tracked by wearable sensors for personalized health and wellness information-body vital parameters, physical activity, behaviors, and other critical parameters impacting quality of daily life. This paper presents an effort to conceptualize WIoT in terms of their design, function, and applications. We discuss the building blocks of WIoT-including wearable sensors, internet-connected gateways and cloud and big data support-that are key to its future success in healthcare domain applications. We also present a new system science for WIoT that suggests future directions, encompassing operational and clinical aspects. <s> BIB007 </s> Internet of Things for Healthcare Using Effects of Mobile Computing: A Systematic Literature Review <s> S. No <s> In-home healthcare services based on the Internet-of-Things (IoT) have great business potentials. To turn it into reality, a business ecosystem should be established first. Technical solutions should therefore aim for a cooperative ecosystem by meeting the interoperability, security, and system integration requirements. In this paper, we propose an ecosystem-driven design strategy and apply it in the design of an open-platform-based in-home healthcare terminal. A cooperative business ecosystem is formulated by merging the traditional healthcare and mobile internet ecosystems. To support the ecosystem in practical technology and business development, ecosystem-driven standardization efforts, security mechanisms, terminal design principles, and data handling schemes are analyzed and corresponding solutions or guidelines are presented. Thirdly, to verify the proposed design strategy and guidelines, an open-platform-based terminal is implemented and demonstrated by a prototyping system. <s> BIB008 </s> Internet of Things for Healthcare Using Effects of Mobile Computing: A Systematic Literature Review <s> S. No <s> The rapid development of Internet of things (IoT) technology makes it possible for connecting various smart objects together through the Internet and providing more data interoperability methods for application purpose. Recent research shows more potential applications of IoT in information intensive industrial sectors such as healthcare services. However, the diversity of the objects in IoT causes the heterogeneity problem of the data format in IoT platform. Meanwhile, the use of IoT technology in applications has spurred the increase of real-time data, which makes the information storage and accessing more difficult and challenging. In this research, first a semantic data model is proposed to store and interpret IoT data. Then a resource-based data accessing method (UDA-IoT) is designed to acquire and process IoT data ubiquitously to improve the accessibility to IoT data resources. Finally, we present an IoT-based system for emergency medical services to demonstrate how to collect, integrate, and interoperate IoT data flexibly in order to provide support to emergency medical services. The result shows that the resource-based IoT data accessing method is effective in a distributed heterogeneous data environment for supporting data accessing timely and ubiquitously in a cloud and mobile computing platform. <s> BIB009 </s> Internet of Things for Healthcare Using Effects of Mobile Computing: A Systematic Literature Review <s> S. No <s> In recent years, healthcare sector has emerged as a major application area of Internet-of-Things (IoT). IoT aims to automate healthcare services through remote monitoring of patients using several vital sign sensors. Remotely collected patient records are then conveyed to the hospital servers through the user's smartphones. Healthcare IoT can thus reduce a lot of overhead while allowing people to access healthcare services all the time and everywhere. However, healthcare IoT exchanges data over the IP-centric Internet which has vulnerabilities related to security, privacy, and mobility. Those features are added to the Internet as external add-ons. In order to solve this problem, in this paper, we propose to use Named Data Networking (NDN), which is a future Internet paradigm based on Content-Centric Networking (CCN). NDN has in-built support for user mobility which is well-suited for mobile patients and caregivers. NDN also ensures data security instead of channel security earlier provided by the Internet. In this paper, we have developed NDNoT, which is an IoT solution for smart mobile healthcare using NDN. Our proof-of-concept prototype shows the usability of our proposed architecture. <s> BIB010 </s> Internet of Things for Healthcare Using Effects of Mobile Computing: A Systematic Literature Review <s> S. No <s> Recently, the popular use of wearable devices and mobile apps makes the effectively capture of lifelogging physical activity data in an Internet of Things (IoT) environment possible. The effective collection of measures of physical activity in the long term is beneficial to interdisciplinary healthcare research and collaboration from clinicians, researchers to patients. However, due to heterogeneity of connected devices and rapid change of diverse life patterns in an IoT environment, lifelogging physical activity information captured by mobile devices usually contains much uncertainty. In this paper, we provide a comprehensive review of existing life-logging physical activity measurement devices, and identify regular and irregular uncertainties of these activity measures in an IoT environment. We then project the distribution of irregular uncertainty by defining a walking speed related score named as Daily Activity in Physical Space (DAPS). Finally, we present an ellipse fitting model based validity improvement method for reducing uncertainties of life-logging physical activity measures in an IoT environment. The experimental results reflect that the proposed method effectively improves the validity of physical activity measures in a healthcare platform. <s> BIB011 </s> Internet of Things for Healthcare Using Effects of Mobile Computing: A Systematic Literature Review <s> S. No <s> In this paper we describe the mobile health (m-health) system in the context of Internet of Things (IoT). We describe the fundamental characteristics of m-health devices such as compactness, IP connectivity, low-power consumption and security. We discuss acquisition of mobile health data via medical gadgets and wearables and application of this data in monitoring various health conditions such as blood sugar level, ECG, blood-pressure, asthma, etc. Security is very critical for IoT based m-health system. We address the issues of confidentiality, privacy, and security in the context of secure m-health system. We listed several measures to protect the information of patients and m-health system. The m-health system will benefit the patients in many ways such as quick diagnosis, remote monitoring and home rehabilitation. Overall m-health system will significantly reduces healthcare cost and unnecessary hospitalizations. <s> BIB012 </s> Internet of Things for Healthcare Using Effects of Mobile Computing: A Systematic Literature Review <s> S. No <s> The advances in information technology have facilitated great progress in healthcare technologies in various domains. However, these new technologies have also made healthcare data not only much larger in size but also substantially more difficult to handle and process. Moreover, because the data are created from a variety of devices within a short time span, these data are stored in different formats and created quickly, which can to a large extent be regarded as a big data problem. This paper discusses how to develop intelligent patientcentric healthcare applications and services from the perspectives of mobile computing and big data analytics technologies. This healthcare system consists of a data collection layer with a unified standard, a data management layer for distributed storage and parallel computing, and a data-oriented service layer. Furthermore, various healthcare applications are discussed to show that mobile computing and big data technologies enhance the performance of the system toward improving a humans well-being. <s> BIB013 </s> Internet of Things for Healthcare Using Effects of Mobile Computing: A Systematic Literature Review <s> S. No <s> Developments in information and communication technologies have led to the wider usage of Internet of Things (IoT). In the modern health care applications, the usage of IoT technologies brings physicians and patients together for automated and intelligent daily activity monitoring for elderly people. Mobile devices and wearable body sensors are gradually implemented for the monitoring of personal health care and wellbeing. One of the main technologies of IoT improvements in healthcare monitoring system is the wearable sensor technology. Furthermore, integration of IoT in healthcare has led to initiate smart applications such as mobile healthcare (m-Healthcare) and intelligent healthcare monitoring systems. In this study an intelligent m-healthcare system based on IoT technology is presented to provide pervasive human activity recognition by using data mining techniques. In this paper, we present a user-dependent data mining approach for off-line human activity classification and a robust and precise human activity recognition model is developed based on IoT technology. The proposed model utilizes the dataset contains body motion and vital signs recordings for ten volunteers of diverse profile while performing 12 physical activities for human activity recognition purpose. Results show that the proposed system is superior in performance with 99.89 % accuracy and is highly effective, robust and reliable in delivering m-Healthcare services during different activities. <s> BIB014 </s> Internet of Things for Healthcare Using Effects of Mobile Computing: A Systematic Literature Review <s> S. No <s> Abstract Currently, we are experiencing a technological shift, which is expected to change the way we program and interact with the world. Cloud computing and mobile computing are two prominent research areas that have already had such an impact. The Internet of Things (IoT), which is concerned with building a network of Internet-enabled devices to promote a smart environment, is another promising area of research. Numerous emerging computing paradigms related to those areas of research and/or their intersections have come into play. These include Mobile Cloud Computing (MCC), cloudlet computing, mobile clouds, mobile IoT computing, IoT cloud computing, fog computing, Mobile Edge Computing (MEC), edge computing, the Web of Things (WoT), the Semantic WoT (SWoT), the Wisdom WoT (W2T), opportunistic sensing, participatory sensing, mobile crowdsensing, and mobile crowdsourcing. Unfortunately, those paradigms suffer from the lack of standard definitions, and so we frequently encounter a single term referring to various paradigms or several terms referring to a single paradigm. Accordingly, this paper attempts to disambiguate those paradigms and explain how and where they fit in the above three areas of research and/or their intersections before it becomes a serious problem. They are tracked back to their inception as much as possible. This is in addition to discussing research directions in each area. The paper also introduces technologies related to the IoT such as ubiquitous and pervasive computing, the Internet of Nano Things (IoNT), and the Internet of Underwater Things (IoUT). <s> BIB015
 Ref# Title 105 BIB007 Wearable Internet of ings: Concept, architectural components and promises for person-centered healthcare 106 BIB008 Ecosystem-driven design of in-home terminals based on open platform for the Internet-of-ings 107 BIB009 Ubiquitous data accessing method in IoT-based information system for emergency medical services 108 BIB001 Drug identification and interaction checker based on IoT to minimize adverse drug reactions and improve drug compliance 109 BIB004 Ecosystem analysis in the design of open platform-based in-home healthcare terminals towards the Internetof-ings 110  Security and privacy mechanism for health Internet of ings 111 BIB005 Application of ZigBee and RFID Technologies in Healthcare in Conjunction with the Internet of ings 112 BIB006 A survey on ambient-assisted living tools for older adults 113 BIB002 Bringing IoT and cloud computing towards pervasive healthcare 114  Privacy and security issues in IoT healthcare applications for the disabled users a survey 115 BIB003 A proposal for using the Internet of ings concept to increase children's health awareness 116  e potential of Internet of m-health ings "m-IoT" for non-invasive glucose level sensing maximum level of relevance pertaining to the providing details about answering RQ-1. e "0.5 score" represents the moderate level of details in terms of details relevant to the answer of RQ-1, and "0 score" shows no details exist in the selected research papers. Among the selected papers for RQ-1, 17 papers contain more detail, and 14 papers contain medium level of details. So, total 31 papers have been studied for the purpose of providing a comprehensive answer to RQ-1. e details provided by research papers in order to answer RQ-1 have been displayed in Figure 8 . Mobile computing is a new technological trend and its applications are in multiple disciplines and are involved in many areas. Mobile computing is about providing quality information services like processing, storage, information, and query to the phone users as well as users of laptops, pagers, and mobile phones that are geographically distantly located. Mobile computing is a type of new technology that enables computers and other information devices to send data without any physical connection to a fixed device. Internet of ings is an intelligent sensing technology that provides vital support for sending and receiving of mobile medical support BIB013 . e mobile computing affects the IoT by providing various services, applications, and devices. ere are various mobile applications that have been developed by the research community for various areas of application. Two noticeable examples are m-health and BIB015 . e concept of m-health in the context of Internet of ings, combined form m-IoT, is applied in the health management system, and it produces the good results by making full and timely use of available and limited resources in order to provide best and more services to the patients. IoT-based m-health services provide convenience to the patients by saving time and money without physical visits to the hospitals, unless their conditions become severe. ese smart medical devices are capable to monitor various health parameters like level of sugar in blood, blood pressure, and pulse rate. ese m-health devices, for the purpose of doing these tasks, are connected to the IoT server. e list of those devices and their functionalities are given in Table 5 BIB012 . Mobile health is a medical health infrastructure that is formed by mobile devices and IoT, and it includes the uses of a mobile phone's core utility of general packet radio service (GPRS), 4G systems, global positioning system (GPS), and Bluetooth technology. M-health makes the decision based on the available data, and these data are gathered by using sensors in environment of IoT. e M-health dataset contains vital sign recordings and the movement of the body when it gets involved in many physical activities. ese sensors can be placed at various positions of the body like the left ankle, right wrist, and chest to track the movement of the subject BIB014 . In order to provide an answer to RQ-1, the focus was to select those papers out of 112 covering the mobile-health or m-health in context of IoT. So, from our collated studies, we identified 16 papers and their definition level of m-health in light of IoT in healthcare scenario. For this purpose, among 16 papers, 10 (62%) papers provided answer to RQ-2, 4 (25%) answered to RQ-2 partially, and 2 (13%) did not define any concepts pertaining to RQ-2, as shown in Figure 9 . ese papers were analysed based on trends in m-health in such a way that 2 papers from 2019, 6 papers from 2018, 2 papers from 2017, 1 paper 2016, and 2 from 2015 were selected, as given in Figure 10 . e use of mobile apps in IoT environment has been remained significant. Mobile apps provide a user interface to the data collected by various sensors or wearable devices. e most significant use of the mobile app is in PHS-personalized healthcare system, where various sensors such as accelerometers, gyroscopes, altimeters, and other low-cost portable devices are capable of being connected in an IoT environment. e concept of IoT-based PHS has become more popular due to the elevated rise of commercial wearable devices and mobile applications. ese healthcare systems use a set of interconnected devices to create an IoT network for performing healthcare activities, such as diagnosis, monitoring, and surgeries at distance  . e mobile computing contributes to IoT by using the concept of smart healthcare. e smart healthcare is connected with low-power wireless technologies to build IoT, which becomes SmartHealthIoT. e patients can connect to the SmartHealthIoT through their smartphones, and the patients can be monitored, ubiquitously, either in their comfortable home environment or even on the move, by using the vital sign sensors connected to their smartphones. SmartHealthIoT is beneficial whenever the people require continuous monitoring and care, such as people with disabilities, aged, frail people living alone, children of dissimilar ages, and adults who are susceptible to near-fatal falls or sudden increases in blood pressure, heart rates, stress level, and so on. In case of emergency, a patient's location can be traced using his/her GPS coordinates. e SmartHealthIoT offers enhanced care and services at very low cost BIB010 . e modern mobile apps and third party API furnish limitless function in order to track the intensity of physical activity such as pace of walking. In this regard, the Fitbit is used which classifies the intensity of daily activities into categories like Very Active, Moderately Active, Lightly Active, and Sedentary; Moves records a series of walking segments containing duration, distance, and speed BIB011 .