TCitySmartF: A comprehensive systematic framework for transforming cities into smart cities

A shared agreed-upon definition of "smart city" (SC) is not available and there is no "best formula" to follow in transforming each and every city into SC. In a broader inclusive definition, it can be described as an opportunistic concept that enhances harmony between the lives and the environment around those lives perpetually in a city by harnessing the smart technology enabling a comfortable and convenient living ecosystem paving the way towards smarter countries and the smarter planet. SCs are being implemented to combine governors, organisations, institutions, citizens, environment, and emerging technologies in a highly synergistic synchronised ecosystem in order to increase the quality of life (QoL) and enable a more sustainable future for urban life with increasing natural resource constraints. In this study, we analyse how to develop citizen- and resource-centric smarter cities based on the recent SC development initiatives with the successful use cases, future SC development plans, and many other particular SC development solutions. The main features of SC are presented in a framework fuelled by recent technological advancement, particular city requirements and dynamics. This framework - TCitySmartF 1) aims to aspire a platform that seamlessly forges engineering and technology solutions with social dynamics in a new philosophical city automation concept - socio-technical transitions, 2) incorporates many smart evolving components, best practices, and contemporary solutions into a coherent synergistic SC topology, 3) unfolds current and future opportunities in order to adopt smarter, safer and more sustainable urban environments, and 4) demonstrates a variety of insights and orchestrational directions for local governors and private sector about how to transform cities into smarter cities from the technological, social, economic and environmental point of view, particularly by both putting residents and urban dynamics at the forefront of the development with participatory planning and interaction for the robust community- and citizen-tailored services. The framework developed in this paper is aimed to be incorporated into the real-world SC development projects in Lancashire, UK

A smartwater metering deployment based on the fog computing paradigm

In this paper, we look into smart water metering infrastructures that enable continuous, on-demand and bidirectional data exchange between metering devices, water flow equipment, utilities and end-users. We focus on the design, development and deployment of such infrastructures as part of larger, smart city, infrastructures. Until now, such critical smart city infrastructures have been developed following a cloud-centric paradigm where all the data are collected and processed centrally using cloud services to create real business value. Cloud-centric approaches need to address several performance issues at all levels of the network, as massive metering datasets are transferred to distant machine clouds while respecting issues like security and data privacy. Our solution uses the fog computing paradigm to provide a system where the computational resources already available throughout the network infrastructure are utilized to facilitate greatly the analysis of fine-grained water consumption data collected by the smart meters, thus significantly reducing the overall load to network and cloud resources. Details of the system's design are presented along with a pilot deployment in a real-world environment. The performance of the system is evaluated in terms of network utilization and computational performance. Our findings indicate that the fog computing paradigm can be applied to a smart grid deployment to reduce effectively the data volume exchanged between the different layers of the architecture and provide better overall computational, security and privacy capabilities to the system

ICT Framework to Support a Patient-Centric approach in Public Healthcare: A Case Study of Malawi

Although Information and Communication Technologies (ICTs) in the healthcare sector are extensively deployed globally, they are not used effectively in developing countries. Many resource poor countries face numerous challenges in implementing the ICT interventions. For instance, many health applications that have been deployed are not user-centric. As a result, such ICT interventions do not benefit many health consumers. The lack of an ICT framework to support patient-centric healthcare services in Malawi renders the e-health and mhealth interventions less sustainable and less cost effective. The aim of the study was therefore to develop an ICT Framework that could support patient-centric healthcare services in the public health sector in Malawi. The comprehensive literature review and semi-structured interviews highlighted many challenges underlying ICT development in Malawi. An ICT framework for patient-centric healthcare services is therefore proposed to ensure that eHealth and mobile health interventions are more sustainable and cost effective. The framework was validated by five experts selected from different areas of expertise including mhealth application developers, ICT policy makers and public health practitioners. Results show that the framework is relevant, useful and applicable within the setting of Malawi. The framework can also be implemented in various countries with similar settings

Healthcare 5.0 Security Framework: Applications, Issues and Future Research Directions

Healthcare 5.0 is a system that can be deployed to provide various healthcare services. It does these services by utilising a new generation of information technologies, such as Internet of Things (IoT), Artificial Intelligence (AI), Big data analytics, blockchain and cloud computing. Due to the introduction of healthcare 5.0, the paradigm has been now changed. It is disease-centered to patient-centered care where it provides healthcare services and supports to the people. However, there are several security issues and challenges in healthcare 5.0 which may cause the leakage or alteration of sensitive healthcare data. This demands that we need a robust framework in order to secure the data of healthcare 5.0, which can facilitate different security related procedures like authentication, access control, key management and intrusion detection. Therefore, in this review article, we propose the design of a secure generalized healthcare 5.0 framework. The details of various applications of healthcare 5.0 along with the security requirements and threat model of healthcare 5.0 are provided. Next, we discuss about the existing security mechanisms in healthcare 5.0 along with their performance comparison. Some future research directions are finally discussed for the researchers working in healthcare 5.0 domain

Wearable Technologies and AI at the Far Edge for Chronic Heart Failure Prevention and Management: A Systematic Review and Prospects

Smart wearable devices enable personalized at-home healthcare by unobtrusively collecting patient health data and facilitating the development of intelligent platforms to support patient care and management. The accurate analysis of data obtained from wearable devices is crucial for interpreting and contextualizing health data and facilitating the reliable diagnosis and management of critical and chronic diseases. The combination of edge computing and artificial intelligence has provided real-time, time-critical, and privacy-preserving data analysis solutions. However, based on the envisioned service, evaluating the additive value of edge intelligence to the overall architecture is essential before implementation. This article aims to comprehensively analyze the current state of the art on smart health infrastructures implementing wearable and AI technologies at the far edge to support patients with chronic heart failure (CHF). In particular, we highlight the contribution of edge intelligence in supporting the integration of wearable devices into IoT-aware technology infrastructures that provide services for patient diagnosis and management. We also offer an in-depth analysis of open challenges and provide potential solutions to facilitate the integration of wearable devices with edge AI solutions to provide innovative technological infrastructures and interactive services for patients and doctors

A patient agent controlled customized blockchain based framework for internet of things

Although Blockchain implementations have emerged as revolutionary technologies for various industrial applications including cryptocurrencies, they have not been widely deployed to store data streaming from sensors to remote servers in architectures known as Internet of Things. New Blockchain for the Internet of Things models promise secure solutions for eHealth, smart cities, and other applications. These models pave the way for continuous monitoring of patient’s physiological signs with wearable sensors to augment traditional medical practice without recourse to storing data with a trusted authority. However, existing Blockchain algorithms cannot accommodate the huge volumes, security, and privacy requirements of health data. In this thesis, our first contribution is an End-to-End secure eHealth architecture that introduces an intelligent Patient Centric Agent. The Patient Centric Agent executing on dedicated hardware manages the storage and access of streams of sensors generated health data, into a customized Blockchain and other less secure repositories. As IoT devices cannot host Blockchain technology due to their limited memory, power, and computational resources, the Patient Centric Agent coordinates and communicates with a private customized Blockchain on behalf of the wearable devices. While the adoption of a Patient Centric Agent offers solutions for addressing continuous monitoring of patients’ health, dealing with storage, data privacy and network security issues, the architecture is vulnerable to Denial of Services(DoS) and single point of failure attacks. To address this issue, we advance a second contribution; a decentralised eHealth system in which the Patient Centric Agent is replicated at three levels: Sensing Layer, NEAR Processing Layer and FAR Processing Layer. The functionalities of the Patient Centric Agent are customized to manage the tasks of the three levels. Simulations confirm protection of the architecture against DoS attacks. Few patients require all their health data to be stored in Blockchain repositories but instead need to select an appropriate storage medium for each chunk of data by matching their personal needs and preferences with features of candidate storage mediums. Motivated by this context, we advance third contribution; a recommendation model for health data storage that can accommodate patient preferences and make storage decisions rapidly, in real-time, even with streamed data. The mapping between health data features and characteristics of each repository is learned using machine learning. The Blockchain’s capacity to make transactions and store records without central oversight enables its application for IoT networks outside health such as underwater IoT networks where the unattended nature of the nodes threatens their security and privacy. However, underwater IoT differs from ground IoT as acoustics signals are the communication media leading to high propagation delays, high error rates exacerbated by turbulent water currents. Our fourth contribution is a customized Blockchain leveraged framework with the model of Patient-Centric Agent renamed as Smart Agent for securely monitoring underwater IoT. Finally, the smart Agent has been investigated in developing an IoT smart home or cities monitoring framework. The key algorithms underpinning to each contribution have been implemented and analysed using simulators.Doctor of Philosoph

Cenários comunicacionais baseados em IOT para a promoção do bem-estar físico, psicológico e social dos séniores

The main objective of this research is to design and validate IoT based social hybrid scenario model that has the potential to promote psychological and physical wellbeing among older adults. The main reason to design and validate the model is age growth, older adults face psychological, physical and social well-being problems that increase mild cognitive impairment and frailty among older adults. Thus, to overcome older adults' problems, the study proposes and validates an IoT-based social hybrid scenario model. The model's features contain passive communication in which Drs, caregivers, and family members can monitor older adults' physical data from long distances. The model's features also contained intentional communication in which Older adults can interact online by text, audio, video calls, sharing images, and online activities such as painting, exercises and cooking. Moreover, older adults can do outdoor activities by inviting peers, friends or family members; the activities can be location-based IoT games, city tours, groups gardening and dinners. The outcomes of model validation will indicate how IoT characteristics can promote physical, psychological and social well-being and provide an opportunity for older adults to spend their life independently. The research that embodies this thesis includes 411 senior Portuguese Universities which are located mainland and on the island of Portugal. Using descriptive research methodology, where quantitative results are analysed, the results indicated a holistic scenario of passive and intentional communication in the context of well-being promotion among olderadults. from here, the social hybrid scenario is outlined, a hybrid model that offers passive and intentional communication between olderadults, family and medical doctors in the context of well-being promotion. The design and characteristics of the model are based on the existing knowledg, and needs of older adults, family members and also medical doctors. Such as model is a compound of passive and intentional characteristics that helps to reduce problem-related mental and physical health. The Passive and intentional communication characteristics are capable to create an environment for older adultsto take care of their psychological and physical health without any intervention and also increase their social physical and online activities, these activities help to promote the well-being of olderadults andd improve the daily lifestyle.O principal objetivo desta pesquisa é projetar e validar um modelo de cenário híbrido social baseado em IoT que tenha o potencial de promover o bem-estar psicológico e físico entre os idosos. A principal razão para projetar e validar o modelo é o crescimento da idade, os idosos enfrentam problemas psicológicos, físicos e de bem-estar social que aumentam o comprometimento cognitivo leve e a fragilidade entre os idosos. Assim, para superar os problemas dos idosos, o estudo propõe e valida um modelo de cenário híbrido social baseado em IoT. Os recursos do modelo contêm comunicação passiva na qual médicos, cuidadores e familiares podem monitorar os dados físicos dos idosos a longas distâncias. As características do modelo também contemplam comunicação intencional em que os idosos podem interagir online por meio de texto, áudio, videochamadas, compartilhamento de imagens e atividades online como pintura, exercícios e culinária. Além disso, os idosos podem fazer atividades ao ar livre convidando colegas, amigos ou familiares; as atividades podem ser jogos de IoT baseados em localização, passeios pela cidade, jardinagem em grupo e jantares. Os resultados da validação do modelo indicam como as características da IoT podem promover o bem-estar físico, psicológico e social e fornecer uma oportunidade para os idosos passarem sua vida de forma independente. A investigação que dá corpo a esta tese inclui 411 universidades portuguesas seniores localizadas no continente e na ilha de Portugal. Utilizando metodologia de pesquisa descritiva, onde são analisados resultados quantitativos, os resultados indicaram um cenário holístico de comunicação passiva e intencional no contexto da promoção do bem-estar entre idosos. a partir daqui, delineia-se o cenário social híbrido, um modelo híbrido que oferece comunicação passiva e intencional entre idosos, médicos de família e médicos no contexto da promoção do bem-estar. O desenho e as características do modelo baseiam-se no conhecimento existente e nas necessidades dos idosos, familiares e também médicos. Tal modelo é um composto de características passivas e intencionais que ajuda a reduzir os problemas relacionados com a saúde mental e física. As características de comunicação passiva e intencional são capazes de criar um ambiente para que os idosos cuidem de sua saúde psicológica e física e também aumentem suas atividades sociais físicas e online, essas atividades ajudam a promover o bem-estar dos idosos e melhorar o estilo de vida diário.Programa Doutoral em Informação e Comunicação em Plataformas Digitai

Personalized data analytics for internet-of-things-based health monitoring

The Internet-of-Things (IoT) has great potential to fundamentally alter the delivery of modern healthcare, enabling healthcare solutions outside the limits of conventional clinical settings. It can offer ubiquitous monitoring to at-risk population groups and allow diagnostic care, preventive care, and early intervention in everyday life. These services can have profound impacts on many aspects of health and well-being. However, this field is still at an infancy stage, and the use of IoT-based systems in real-world healthcare applications introduces new challenges. Healthcare applications necessitate satisfactory quality attributes such as reliability and accuracy due to their mission-critical nature, while at the same time, IoT-based systems mostly operate over constrained shared sensing, communication, and computing resources. There is a need to investigate this synergy between the IoT technologies and healthcare applications from a user-centered perspective. Such a study should examine the role and requirements of IoT-based systems in real-world health monitoring applications. Moreover, conventional computing architecture and data analytic approaches introduced for IoT systems are insufficient when used to target health and well-being purposes, as they are unable to overcome the limitations of IoT systems while fulfilling the needs of healthcare applications. This thesis aims to address these issues by proposing an intelligent use of data and computing resources in IoT-based systems, which can lead to a high-level performance and satisfy the stringent requirements. For this purpose, this thesis first delves into the state-of-the-art IoT-enabled healthcare systems proposed for in-home and in-hospital monitoring. The findings are analyzed and categorized into different domains from a user-centered perspective. The selection of home-based applications is focused on the monitoring of the elderly who require more remote care and support compared to other groups of people. In contrast, the hospital-based applications include the role of existing IoT in patient monitoring and hospital management systems. Then, the objectives and requirements of each domain are investigated and discussed. This thesis proposes personalized data analytic approaches to fulfill the requirements and meet the objectives of IoT-based healthcare systems. In this regard, a new computing architecture is introduced, using computing resources in different layers of IoT to provide a high level of availability and accuracy for healthcare services. This architecture allows the hierarchical partitioning of machine learning algorithms in these systems and enables an adaptive system behavior with respect to the user's condition. In addition, personalized data fusion and modeling techniques are presented, exploiting multivariate and longitudinal data in IoT systems to improve the quality attributes of healthcare applications. First, a real-time missing data resilient decision-making technique is proposed for health monitoring systems. The technique tailors various data resources in IoT systems to accurately estimate health decisions despite missing data in the monitoring. Second, a personalized model is presented, enabling variations and event detection in long-term monitoring systems. The model evaluates the sleep quality of users according to their own historical data. Finally, the performance of the computing architecture and the techniques are evaluated in this thesis using two case studies. The first case study consists of real-time arrhythmia detection in electrocardiography signals collected from patients suffering from cardiovascular diseases. The second case study is continuous maternal health monitoring during pregnancy and postpartum. It includes a real human subject trial carried out with twenty pregnant women for seven months