ConTaaS: An Approach to Internet-Scale Contextualisation for Developing Efficient Internet of Things Applications

The Internet of Things (IoT) is a new internet evolution that involves connecting billions of sensors and other devices to the Internet. Such IoT devices or IoT things can communicate directly. They also allow Internet users and applications to access and distil their data, control their functions, and harness the information and functionality provided by multiple IoT devices to offer novel smart services. IoT devices collectively generate massive amounts of data with an incredible velocity. Processing IoT device data and distilling high-value information from them presents an Internet-scale computational challenge. Contextualisation of IoT data can help improve the value of information extracted from IoT. However, existing contextualisation techniques can only handle small datasets from a modest number of IoT devices. In this paper, we propose a general-purpose architecture and related techniques for the contextualisation of IoT data. In particular, we introduce a Contextualisation-as-a-Service (ConTaaS) architecture that incorporates scalability improving techniques, as well as a proof-of-concept implementation of all these that utilises elastic cloud-based infrastructure to achieve near real-time contextualisation of IoT data. Experimental evaluations validating the efficiency of ConTaaS are also provided in this paper

IoT Platform for COVID-19 Prevention and Control: A Survey

As a result of the worldwide transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), coronavirus disease 2019 (COVID-19) has evolved into an unprecedented pandemic. Currently, with unavailable pharmaceutical treatments and vaccines, this novel coronavirus results in a great impact on public health, human society, and global economy, which is likely to last for many years. One of the lessons learned from the COVID-19 pandemic is that a long-term system with non-pharmaceutical interventions for preventing and controlling new infectious diseases is desirable to be implemented. Internet of things (IoT) platform is preferred to be utilized to achieve this goal, due to its ubiquitous sensing ability and seamless connectivity. IoT technology is changing our lives through smart healthcare, smart home, and smart city, which aims to build a more convenient and intelligent community. This paper presents how the IoT could be incorporated into the epidemic prevention and control system. Specifically, we demonstrate a potential fog-cloud combined IoT platform that can be used in the systematic and intelligent COVID-19 prevention and control, which involves five interventions including COVID-19 Symptom Diagnosis, Quarantine Monitoring, Contact Tracing & Social Distancing, COVID-19 Outbreak Forecasting, and SARS-CoV-2 Mutation Tracking. We investigate and review the state-of-the-art literatures of these five interventions to present the capabilities of IoT in countering against the current COVID-19 pandemic or future infectious disease epidemics.Comment: 12 pages; Submitted to IEEE Internet of Things Journa

IoMT amid COVID-19 pandemic: Application, architecture, technology, and security

In many countries, the Internet of Medical Things (IoMT) has been deployed in tandem with other strategies to curb the spread of COVID-19, improve the safety of front-line personnel, increase efficacy by lessening the severity of the disease on human lives, and decrease mortality rates. Significant inroads have been achieved in terms of applications and technology, as well as security which have also been magnified through the rapid and widespread adoption of IoMT across the globe. A number of on-going researches show the adoption of secure IoMT applications is possible by incorporating security measures with the technology. Furthermore, the development of new IoMT technologies merge with Artificial Intelligence, Big Data and Blockchain offers more viable solutions. Hence, this paper highlights the IoMT architecture, applications, technologies, and security developments that have been made with respect to IoMT in combating COVID-19. Additionally, this paper provides useful insights into specific IoMT architecture models, emerging IoMT applications, IoMT security measurements, and technology direction that apply to many IoMT systems within the medical environment to combat COVID-19

Review on the Use of ICT Driven Solutions Towards Managing Global Pandemics

A pandemic is a contagious disease outbreak that happens over a large geographic area and affects a great portion of the population while new pathogens appear for which people have less immunity and no vaccines are available. The disease can spread from person to person in a very short time. Health workers are at greater risk of infection because of patients who are carriers. In the 21st century, where everyone is connected through digital technologies, information and communication technology (ICT) plays a critical role in improving healthcare for individuals and larger communities. ICT can be divided into a wide variety of application domains that signify its importance as a major technological paradigm. It is currently drawing large attention because of its potential to alleviate the burden on healthcare systems caused by the rise in chronic diseases, aging populations and pandemic situations. This study surveyed substantial knowledge on how effective ICT healthcare solutions can be used towards managing global pandemics. In order to make it more comprehensive, we also present a four-phase strategic framework that can be deployed to alleviate the strain on healthcare resources during a pandemic, which was derived from the reviewed literature. Further, we also discuss how ICT technologies can be used towards managing pandemic situations chronographically during the transformation from a simple disease outbreak into a global pandemic

IoT for Global Development to Achieve the United Nations Sustainable Development Goals: The New Scenario After the COVID-19 Pandemic

COVID-19 has not affected all countries equally: developing countries have been more disadvantaged by the pandemic. Regarding global development, the COVID-19 pandemic has forced a step back in the path to attaining the Sustainable Development Goals (SDGs). The SDGs most negatively affected by the pandemic are identified here: education, health, and work. Then using the SDGs as a reference, this research explores the new challenges faced by developing countries and the impact of the Internet of Things (IoT) after COVID-19's emergence. IoT solutions carried out in developing countries during the pandemic have been identified and reviewed. Successful Internet of Things for Development (IoT4D) projects, in relation to the SDGs, are highlighted. New social and technical challenges that have emerged for the IoT4D as a consequence of the pandemic are then studied. This work concludes that the future of IoT4D in the wake of COVID-19 should focus on the use of low-cost IoT devices for the SDGs most affected by the pandemic. After an exhaustive study, the Intelligent Internet of Things (IIoT) has been determined to be a key actor in the pandemic's wake, with a leading role in the health sector. The proposed approach includes an extensive study of the new role of the IoT4D for achieving the SDGs in our forever changed world.This work was supported by the European Commission through Urban Innovative Actions of the EPIU Getafe Project under Grant UIA04-212. The work of Ascensión López-Vargas was supported by the University of Jaén, ``Ayudas de la EDUJA para la realización de estancias para la obtención de Mención Internacional,'' in 2019. The work of Agapito Ledezma was supported by the Agencia Estatal de Investigación (AEI) under Grant RTI2018-096036-B-C22/AEI/10.13039/501100011033. The work of Araceli Sanchis was supported by the Agencia Estatal de Investigación (AEI) under Grant PID2019-104793RB-C31/AEI/10.13039/501100011033

Nano-enabled biosensing systems for intelligent healthcare: towards COVID-19 management

Biosensors are emerging as efficient (sensitive and selective) and affordable analytical diagnostic tools for early-stage disease detection, as required for personalized health wellness management. Low-level detection of a targeted disease biomarker (pM level) has emerged extremely useful to evaluate the progression of disease under therapy. Such collected bioinformatics and its multi-aspects-oriented analytics is in demand to explore the effectiveness of a prescribed treatment, optimize therapy, and correlate biomarker level with disease pathogenesis. Owing to nanotechnology-enabled advancements in sensing unit fabrication, device integration, interfacing, packaging, and sensing performance at point-of-care (POC) has rendered diagnostics according to the requirements of disease management and patient disease profile i.e. in a personalized manner. Efforts are continuously being made to promote the state of art biosensing technology as a next-generation non-invasive disease diagnostics methodology. Keeping this in view, this progressive opinion article describes personalized health care management related analytical tools which can provide access to better health for everyone, with overreaching aim to manage healthy tomorrow timely. Considering accomplishments and predictions, such affordable intelligent diagnostics tools are urgently required to manage COVID-19 pandemic, a life-threatening respiratory infectious disease, where a rapid, selective and sensitive detection of human beta severe acute respiratory system coronavirus (SARS-COoV-2) protein is the key factor

Edge Intelligence for Empowering IoT-based Healthcare Systems

The demand for real-time, affordable, and efficient smart healthcare services is increasing exponentially due to the technological revolution and burst of population. To meet the increasing demands on this critical infrastructure, there is a need for intelligent methods to cope with the existing obstacles in this area. In this regard, edge computing technology can reduce latency and energy consumption by moving processes closer to the data sources in comparison to the traditional centralized cloud and IoT-based healthcare systems. In addition, by bringing automated insights into the smart healthcare systems, artificial intelligence (AI) provides the possibility of detecting and predicting high-risk diseases in advance, decreasing medical costs for patients, and offering efficient treatments. The objective of this article is to highlight the benefits of the adoption of edge intelligent technology, along with AI in smart healthcare systems. Moreover, a novel smart healthcare model is proposed to boost the utilization of AI and edge technology in smart healthcare systems. Additionally, the paper discusses issues and research directions arising when integrating these different technologies together.Comment: This paper has been accepted in IEEE Wireless Communication Magazin