Towards fog-driven IoT eHealth:Promises and challenges of IoT in medicine and healthcare

Internet of Things (IoT) offers a seamless platform to connect people and objects to one another for enriching and making our lives easier. This vision carries us from compute-based centralized schemes to a more distributed environment offering a vast amount of applications such as smart wearables, smart home, smart mobility, and smart cities. In this paper we discuss applicability of IoT in healthcare and medicine by presenting a holistic architecture of IoT eHealth ecosystem. Healthcare is becoming increasingly difficult to manage due to insufficient and less effective healthcare services to meet the increasing demands of rising aging population with chronic diseases. We propose that this requires a transition from the clinic-centric treatment to patient-centric healthcare where each agent such as hospital, patient, and services are seamlessly connected to each other. This patient-centric IoT eHealth ecosystem needs a multi-layer architecture: (1) device, (2) fog computing and (3) cloud to empower handling of complex data in terms of its variety, speed, and latency. This fog-driven IoT architecture is followed by various case examples of services and applications that are implemented on those layers. Those examples range from mobile health, assisted living, e-medicine, implants, early warning systems, to population monitoring in smart cities. We then finally address the challenges of IoT eHealth such as data management, scalability, regulations, interoperability, device–network–human interfaces, security, and privacy

INTEGRATION OF INTERNET OF THINGS AND HEALTH RECOMMENDER SYSTEMS

The Internet of Things (IoT) has become a part of our lives and has provided many enhancements to day-to-day living. In this project, IoT in healthcare is reviewed. IoT-based healthcare is utilized in remote health monitoring, observing chronic diseases, individual fitness programs, helping the elderly, and many other healthcare fields. There are three main architectures of smart IoT healthcare: Three-Layer Architecture, Service-Oriented Based Architecture (SoA), and The Middleware-Based IoT Architecture. Depending on the required services, different IoT architecture are being used. In addition, IoT healthcare services, IoT healthcare service enablers, IoT healthcare applications, and IoT healthcare services focusing on Smartwatch are presented in this research. Along with IoT in smart healthcare, Health Recommender Systems integration with IoT is important. Main Recommender Systems including Content-based filtering, Collaborative-based filtering, Knowledge-based filtering, and Hybrid filtering with machine learning algorithms are described for the Health Recommender Systems. In this study, a framework is presented for the IoT-based Health Recommender Systems. Also, a case is investigated on how different algorithms can be used for Recommender Systems and their accuracy levels are presented. Such a framework can help with the health issues, for example, risk of going to see the doctor during pandemic, taking quick actions in any health emergencies, affordability of healthcare services, and enhancing the personal lifestyle using recommendations in non-critical conditions. The proposed framework can necessitate further development of IoT-based Health Recommender Systems so that people can mitigate their medical emergencies and live a healthy life

A multivariant secure framework for smart mobile health application

This is an accepted manuscript of an article published by Wiley in Transactions on Emerging Telecommunications Technologies, available online: https://doi.org/10.1002/ett.3684 The accepted version of the publication may differ from the final published version.Wireless sensor network enables remote connectivity of technological devices such as smart mobile with the internet. Due to its low cost as well as easy availability of data sharing and accessing devices, the Internet of Things (IoT) has grown exponentially during the past few years. The availability of these devices plays a remarkable role in the new era of mHealth. In mHealth, the sensors generate enormous amounts of data and the context-aware computing has proven to collect and manage the data. The context aware computing is a new domain to be aware of context of involved devices. The context-aware computing is playing a very significant part in the development of smart mobile health applications to monitor the health of patients more efficiently. Security is one of the key challenges in IoT-based mHealth application development. The wireless nature of IoT devices motivates attackers to attack on application; these vulnerable attacks can be denial of service attack, sinkhole attack, and select forwarding attack. These attacks lead intruders to disrupt the application's functionality, data packet drops to malicious end and changes the route of data and forwards the data packet to other location. There is a need to timely detect and prevent these threats in mobile health applications. Existing work includes many security frameworks to secure the mobile health applications but all have some drawbacks. This paper presents existing frameworks, the impact of threats on applications, on information, and different security levels. From this line of research, we propose a security framework with two algorithms, ie, (i) patient priority autonomous call and (ii) location distance based switch, for mobile health applications and make a comparative analysis of the proposed framework with the existing ones.Published onlin

Understanding User Perception and Intention to Use Smart Homes for Energy Efficiency: A Survey

The positive impact of Smart Homes on energy efficiency is heavily dependent on how consumers use the system after adoption. While the technical aspects of Smart Home systems and their potential to reduce energy usage is a focus of various studies, there is a limited consideration of behavioral psychology while designing systems for energy management. To investigate users' perception and intention to use Smart Homes to support energy efficiency, we design a research model by combining a theory of planned behavior and the norm activation model. We design a questionnaire and conduct a survey targeting current smart home users (over 350 responses). To analyze the survey results, we extend the partial least squares structural equation modeling (PLS-SEM) by a random forest algorithm. The findings suggest that personal norms have the strongest influence on behavioral intention to use Smart Homes for energy efficiency, followed by the ascription of responsibility. Furthermore, the results support the effects of attitudes, subjective norms, awareness of consequences, as well as the moderating effect of past behavior on the relationship between personal norms and behavioral intentions

How does a (Smart) Age-Friendly Ecosystem Look in a Post-Pandemic Society?

COVID-19 has impacted not only the health of citizens, but also the various factors that make up our society, living environments, and ecosystems. This pandemic has shown that future living will need to be agile and flexible to adapt to the various changes in needs of societal populations. Digital technology has played an integral role during COVID-19, assisting various sectors of the community, and demonstrating that smart cities can provide opportunities to respond to many future societal challenges. In the decades ahead, the rise in aging populations will be one of these challenges, and one in which the needs and requirements between demographic cohorts will vary greatly. Although we need to create future smart age-friendly ecosystems to meet these needs, technology still does not feature in the WHO eight domains of an age-friendly city. This paper extends upon Marston and van Hoof’s ‘Smart Age-friendly Ecosystem’ (SAfE) framework, and explores how digital technology, design hacking, and research approaches can be used to understand a smart age-friendly ecosystem in a post-pandemic society. By exploring a series of case studies and using real-life scenarios from the standpoint of COVID-19, we propose the ‘Concept of Age-friendly Smart Ecologies (CASE)’ framework. We provide an insight into a myriad of contemporary multi-disciplinary research, which are capable to initiate discussions and bring various actors together with a positive impact on future planning and development of age-friendly ecosystems. The strengths and limitations of this framework are outlined, with advantages evident in the opportunity for towns, regions/counties, provinces, and states to take an agile approach and work together in adopting and implement improvements for the greater benefits of residents and citizens

Towards an ethical framework for the design and development of inclusive home-based smart technology for smart spaces for older adults and people with disabilities

Unique ethical, privacy and safety implications arise for people who are reliant on home-based smart technology due to health conditions or disabilities. As a result we need to carefully reflect on our approaches to ethical issues over the life cycle of smart home technology design and the wider living context for end users and relevant stakeholders. In this position paper we highlight a need for a reflective, inclusive ethical framework for the design of inclusive smart spaces. We present key ethical considerations in the design, development and deployment of smart home-based technology for older adults and people with disabilities. We propose a novel ethical framework for the development of inclusive home-based smart technology which combines these key considerations with existing models of design

No soldiers left behind: An IoT-based low-power military mobile health system design

© 2013 IEEE. There has been an increasing prevalence of ad-hoc networks for various purposes and applications. These include Low Power Wide Area Networks (LPWAN) and Wireless Body Area Networks (WBAN) which have emerging applications in health monitoring as well as user location tracking in emergency settings. Further applications can include real-Time actuation of IoT equipment, and activation of emergency alarms through the inference of a user\u27s situation using sensors and personal devices through a LPWAN. This has potential benefits for military networks and applications regarding the health of soldiers and field personnel during a mission. Due to the wireless nature of ad-hoc network devices, it is crucial to conserve battery power for sensors and equipment which transmit data to a central server. An inference system can be applied to devices to reduce data size for transfer and subsequently reduce battery consumption, however this could result in compromising accuracy. This paper presents a framework for secure automated messaging and data fusion as a solution to address the challenges of requiring data size reduction whilst maintaining a satisfactory accuracy rate. A Multilayer Inference System (MIS) was used to conserve the battery power of devices such as wearables and sensor devices. The results for this system showed a data reduction of 97.9% whilst maintaining satisfactory accuracy against existing single layer inference methods. Authentication accuracy can be further enhanced with additional biometrics and health data information

Ten questions concerning age-friendly cities and communities and the built environment

The development of ‘age-friendly cities’ has become a major area of work in the field of ageing and the built environment. This movement is driven by the observation that cities are home to an ever-increasing ageing population. Over the past decade, a multitude of age-friendly initiatives have been developed with the aim of making physical and social environments more favourable for older people's well-being, health and ability to live in the community. This article explores ten key questions associated with the age-friendly cities and communities' movement, with a particular focus on the built environment. It provides an overview of the history of the age-friendly cities' movement and the underlying models, the aspects of the built environment that are relevant for age-friendly cities, the ways age-friendliness can be evaluated, and the interactions between age-friendly cities initiatives and other strategic agendas such as smart cities. The paper concludes by discussing future perspectives and possible directions for further development of the age-friendly movement

Perceptions of Adult Patients Accessing Telehealth in an Urban Medical Group

Problem: Although implementation of in-patient electronic healthcare records is nearly complete in the United States, this achievement has not translated into consumer-to-business telehealth in the primary care setting. Because there are few studies that describe how and why patients select telehealth, the aim of this study was to learn about perceptions of adult patients in an urban setting when telehealth options are available. Research questions included a) How do patients select any type of appointment? b) How do patients perceive and use telehealth options? c) How and when might telehealth be useful in the future? Methods: A qualitative study design was used to collect data through semi-structured open-ended interviews from 21 patients in a primary care practice. Interviews were transcribed and analyzed using grounded theory methodology. Results: The theory of weighing options emerged from the data. The process of weighing options explains how patients balance factors of urgency, timing/scheduling, relationships, distance, convenience, and various technical aspects before selecting a telehealth encounter or not. If all the factors show a benefit, then the decision is made to use telehealth. Information obtained from the patient perspective may identify strategies to support increased use of telehealth. Conclusion: The benefit of this study will be to facilitate awareness among patients about telehealth options. This information can be used by providers and nurses to maintain caring while supporting patients who choose virtual care