In recent years, the Internet of Things (IoT) has gained convincing research ground as a new research topic in a wide variety of academic and industrial disciplines, especially in healthcare. The IoT revolution is reshaping modern healthcare systems by incorporating technological, economic, and social prospects. It is evolving healthcare systems from conventional to more personalized healthcare systems through which patients can be diagnosed, treated, and monitored more easily. The current global challenge of the pandemic caused by the novel severe respiratory syndrome coronavirus 2 presents the greatest global public health crisis since the pandemic influenza outbreak of 1918. At the time this paper was written, the number of diagnosed COVID-19 cases around the world had reached more than 31 million. Since the pandemic started, there has been a rapid effort in different research communities to exploit a wide variety of technologies to combat this worldwide threat, and IoT technology is one of the pioneers in this area. In the context of COVID-19, IoT-enabled/linked devices/applications are utilized to lower the possible spread of COVID-19 to others by early diagnosis, monitoring patients, and practicing defined protocols after patient recovery. This paper surveys the role of IoT-based technologies in COVID-19 and reviews the state-of-the-art architectures, platforms, applications, and industrial IoT-based solutions combating COVID-19 in three main phases, including early diagnosis, quarantine time, and after recovery.

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Internet of Things for Current COVID-19 and Future Pandemics: an Exploratory Study.

A reliable IoT system for Personal Healthcare Devices

Artificial intelligence (AI) is a powerful concept still in its infancy that has the potential, if utilised responsibly, to provide a vehicle for positive change that could promote sustainable transitions to a more resource-efficient livability paradigm. AI with its deep learning functions and capabilities can be employed as a tool which empowers machines to solve problems that could reform urban landscapes as we have known them for decades now and help with establishing a new era; the era of the “smart city”. One of the key areas that AI can redefine is transport. Mobility provision and its impact on urban development can be significantly improved by the employment of intelligent transport systems in general and automated transport in particular. This new breed of AI-based mobility, despite its machine-orientation, has to be a user-centred technology that “understands” and “satisfies” the human user, the markets and the society as a whole. Trust should be built, and risks should be eliminated, for this transition to take off. This paper provides a novel conceptual contribution that thoroughly discusses the scarcely studied nexus of AI, transportation and the smart city and how this will affect urban futures. It specifically covers key smart mobility initiatives referring to Connected and Autonomous Vehicles (CAVs), autonomous Personal and Unmanned Aerial Vehicles (PAVs and UAVs) and Mobility-as-a-Service (MaaS), but also interventions that may work as enabling technologies for transport, such as the Internet of Things (IoT) and Physical Internet (PI) or reflect broader transformations like Industry 4.0. This work is ultimately a reference tool for researchers and city planners that provides clear and systematic definitions of the ambiguous smart mobility terms of tomorrow and describes their individual and collective roles underpinning the nexus in scope.

Artificial Intelligence, Transport and the Smart City: Definitions and Dimensions of a New Mobility Era

Geologic hazards (geohazards) are naturally occurring or human-activity-induced geologic conditions capable of causing damage or loss of property and/or life. geohazards, such as landslides, surface subsidence, and earthquakes, can seriously affect and threaten life, property, or public safety. geohazards prevention is the application of geologic engineering principles and existing and emerging technologies to reduce, minimize, or prevent the effects of various geologic hazards. Monitoring and early warning are the most common strategies for geohazards prevention. With the development of the Internet of Things (IoT), an emerging new idea is to apply IoT technology to enhance the accuracy and efficiency of monitoring and early warning systems for geohazards prevention. This article aims to present a comprehensive survey of relevant research and technological developments of the IoT applied in geohazards prevention. It first surveys the applications of the IoT in the monitoring and early warning of seven types of common geohazards, including landslides, debris flow, rockfall, surface subsidence, surface collapse, surface cracks, and earthquakes, then investigates the key technologies in geohazards prevention when utilizing the IoT, and finally summarizes the challenges in IoT-based monitoring and early warning systems for geohazards prevention. Moreover, this article also highlights the future directions for employing the IoT for geohazards prevention.

A Survey of Internet of Things (IoT) for Geohazard Prevention: Applications, Technologies, and Challenges

In recent years, the Internet of Things (IoT) has drawn convincing research ground as a new research topic in a wide variety of academic and industrial disciplines, especially in healthcare. The IoT revolution is reshaping modern healthcare systems by incorporating technological, economic, and social prospects. It is evolving healthcare systems from conventional to more personalized healthcare systems through which patients can be diagnosed, treated, and monitored more easily. The current global challenge of the pandemic caused by the novel severe contagious respiratory syndrome coronavirus 2 presents the greatest global public health crisis since the pandemic influenza outbreak of 1918. At the time this paper was written, the number of diagnosed COVID-19 cases around the world had reached more than 31 million. Since the pandemic started, there has been a rapid effort in different research communities to exploit a wide variety of technologies to combat this worldwide threat, and IoT technology is one of the pioneers in this area. In the context of COVID-19, IoT enabled /linked devices/applications are utilized to lower the possible spread of COVID-19 to others by early diagnosis, monitoring patients, and practicing defined protocols after patient recovery. This paper surveys the role of IoT-based technologies in COVID-19 and reviews the state-of-the-art architectures, platforms, applications, and industrial IoT-based solutions combating COVID-19 in three main phases, including early diagnosis, quarantine time, and after recovery.

Internet of Things for Current COVID-19 and Future Pandemics: An Exploratory Study

In this paper, we seek to highlight the concept of Internet of Things (IoT) in general, as well as reviewing the main challenges of the IoT environment by focusing on the recent research directions in this topic. Recently, IoT has emerged as a new technology that is used to express a modern wireless telecommunication network, and it can be defined as an intelligent and interoperability node interconnected in a dynamic global infrastructure network, also it seeks to implement the connectivity concept of anything from anywhere at anytime. Indeed, the IoT environment possesses a large spectrum of challenges has a broad impact on their performance, which can be divided into two categories, namely, i) General challenges: such as communication, heterogeneity, virtualization and security; and ii) Unique challenges: such as wireless sensor network (WSN), Radio Frequency Identification (RFID), and finally Quality of service (QoS) that is considered as a common factor between both general and special challenges. In addition, this paper highlights the main applications of the IoT.

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Internet of Things (IoT): Definitions, Challenges and Recent Research Directions

The proliferation of ubiquitous sensing technology is bringing a rising number of the innovative models that have unique characteristics of the utility computing. These models have offered great opportunities to improve IT industries and business processes through the convergence of cloud computing and internet of things (IoT). Although this convergence establishes seamless intelligent interaction among physical and virtual entities, it has difficulty not only to meet the required level of quality of service(QoS) but also to satisfy the user’s complex demands. As a result, the predisposition to create a dynamic service-oriented environment has become a fundamental design issue. The main objective of this study is to introduce a dynamic QoS provisioning framework (QoPF) for service-oriented IoT using backtracking search optimization algorithm (BSOA). The QoPF framework is proposed to maximize the composite service quality in IoT application layer by making a balance between service reliability and acceptable cost of the computational time. The effectiveness of the QoPF framework is evaluated using a number of performance metrics such as throughput, delay time, and jitter. The experimental results demonstrate that worthiness of the QoPF to meet QoS requirements more than other state-of-the-art techniques in the literature review.

QoS provisioning framework for service-oriented internet of things (IoT)

The convergence initiatives of cloud technology and the Internet of Things (IoT) have demonstrated a massive rise of the futuristic technologies which ensure sustainable production development of IoT applications such as intelligent transportation, smart cities, smart healthcare, and other applications. These real-time applications are employing the information and communication technology as an efficient utility to support a ubiquitous approach in the industry so that any apparatus can seamlessly interact with different cyber-physical systems and may also share its information effortlessly. Although the amalgamation of cloud and IoT offers robustness pervasive computing scenarios that can achieve the composite service with high quality and acceptable cost, it may face several challenges and issues not only in performance but also in architecture. The main aim of this study is to offer a stander framework to investigator and application designer that how sustainability can be achieved using different quality of service metrics. This is an overview of some crucial issues of IoT and the relation between it and other technologies based on various platforms. Focus is given in this study to three of the most important IoT applications that require highly successful sustainability procedures which are presented. A brief discussion and statistical categories of the research techniques published from 2000 to 2020, which highlight sustainable IoT applications, are also introduced. The contributions of this study are as follows: (i) summarizing the organization and methodology of the most important sustainable IoT applications, (ii) discussing the main challenges of the sustainable growth of IoT applications, (iii) highlighting future research directions in the field of IoT, and introducing guidelines for open business opportunities.

Towards sustainable smart IoT applications architectural elements and design: opportunities, challenges, and open directions

The Internet of Things (IoT) is a new telecommunication paradigm to enable the remote connectivity between dozens of smart objects so that any physical object can interact with each other unmanned-wise. The innovative design for the IoT paradigm has mainly based on “Virtualization technology” to provide the full interaction for the user within the system environment. Meanwhile, it alleviates potential system complications. In this end, this paper seeks to introduce a new vision of an IoT virtualization framework based on Sensor-as-a-Service (SenaaS) to maximize the utilization of sensor functionalities. Moreover, the paper offers an adaptor oriented structure technique by using ITA Sensor Fabric (aka Information Fabric) which relies on Publish/Subscribe mechanism to realize an oriented communication between things. In our proposed framework, ITA Sensor Fabric used as a parallel measure with the semantic approach for mitigating the principle issues in the sensor arena. Furthermore, the proposed framework uses Backtracking Search Optimization Algorithm (BSA) to enhance the SenaaS performance with the time-sensitive services and ensure the required level of the Quality of Service (QoS). The effectiveness of the proposed framework tested by using MATLAB and NS2-based simulations in terms of delay time, packet delivery ratio, throughput, and jitter. Finally, all the experimental results proved that BSA has a significant influence on the time-sensitive services more than their analogues of algorithms.

A New Proposed the Internet of Things (IoT) Virtualization Framework Based on Sensor-as-a-Service Concept

Intelligent Transportation Systems have gained significant attention among Internet of Things applications due to its specific features and its high capability to promote the innovation of the automotive industries. As part of smart cities, smart mobility initiatives offer new opportunities for intelligent transportation systems to maximize the utilization of the time-sensitive data that are streaming out of different sensory transport resources to support “newcasting” instead of “forecasting” technique. As a result, efficient information dissemination has become the new production factor, notably in terms of mitigating traffic congestion, maximizing bandwidth utilization, and reducing transmission power consumption over the network. Cloud Computing and its counterparts have been established as relatively stable environments for proving a wide number of tackled solutions. However, the limitations of network bandwidth as well as the rapid expansion into the data transfer rate are still the bottlenecks of vehicular networks. The main contribution of this study is to improve Vehicular Ad hoc Network performance in real-time using a geographically distributed computing architecture based on fog technology. This architecture presents a set of novel techniques from different points of view. These novelties include, (i) a flexible registration methodology for improving the navigation process among mobile vehicles; (ii) a generic distributed mechanism to adjust the communication range and the network connectivity; and (iii) a new mathematical model to ensure transmission reliability through establishing powerful communication channels between the vehicular entities and fog layer. The effectiveness of the proposed architecture is evaluated using several performance metrics such as throughput, delay time, and jitter. The experimental results reveal that the worthiness of the proposed architecture to meet the quality of service requirements is more than other state-of-the-art techniques in the literature review.

Zainab Hassan Ali

Papers

Internet of Things (IoT): Definitions, Challenges and Recent Research Directions

QoS provisioning framework for service-oriented internet of things (IoT)

Towards sustainable smart IoT applications architectural elements and design: opportunities, challenges, and open directions

A New Proposed the Internet of Things (IoT) Virtualization Framework Based on Sensor-as-a-Service Concept

A novel geographically distributed architecture based on fog technology for improving Vehicular Ad hoc Network (VANET) performance