Intelligent data-intensive IoT: A survey

Xiao, Bin; Rahmani, Rahim; Li, Yuhong; Gillblad, Daniel; Kanter, Theo

doi:10.1109/compcomm.2016.7925122

Cited by 9 publications

(3 citation statements)

References 49 publications

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“…Multiple services can be dynamically created and provided through this platform. From this perspective, network softwarization benefits not only IoT but also other technologies such as big data and digital money, hence creating a vast wave of modernization within all industries and fostering towards a digital society [26].…”

Section: Network Function Virtualization For Iotmentioning

confidence: 99%

Virtualizing the Iot Ecosystem: A Brief Review, Addressing NFV Strategies

Ruambo¹,

Mwakatobe²

2019

IJEAST

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Pervasiveness in computing, connectivity, and use of Internet Protocol (IP) contributes highly to the rapid growth of the Internet of things (IoT). The deployment of IoT and its applications range not only from smart cities to ubiquitous healthcare but also to the internet itself, thus resulting in a complex physical infrastructure of diversified network systems. The complicated IoT ecosystem infrastructure poses several challenges in effectively controlling and monitoring the system network functions and services. This triggers the need for dynamic and efficient solutions for management and configuration. The emerging strategy that promises to address the aforementioned challenges is by orchestrating the system network functions and services automatically. In the recent past, automating management and configuration processes to deliver system network functions and services has been an interesting research topic and extensively researched. It is achievable through virtualization technologies namely Network Function Virtualization (NFV) and Software Defined Networks (SDN). In this article, a brief overview of the NFV strategies towards virtualizing the IoT ecosystem is addressed. In addition, challenges and insights upon adopting NFV to virtualize the IoT ecosystem are highlighted. The review reveals that, in order to virtualize IoT ecosystem efficiently, there is a need for building an integrated IoT-NFV based framework with in-built automation capabilities by incorporating appropriate virtualization technologies whilst embracing the best design, performance and security principles and practices.

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Section: Network Function Virtualization For Iotmentioning

confidence: 99%

Virtualizing the Iot Ecosystem: A Brief Review, Addressing NFV Strategies

Ruambo¹,

Mwakatobe²

2019

IJEAST

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“…Big Data was defined by IBM in 2012 [36] by the properties of the volume, velocity and variety of the dataset. Big Data analysis requires the development of deep knowledge of their installations and operations together with robust and complex algorithms [37,38].…”

Section: Introductionmentioning

confidence: 99%

Use of UIoT for Offshore Surveys Through Autonomous Vehicles

Sánchez

Márquez

Govindara

et al. 2021

Polish Maritime Research

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The ENDURUNS project is a European Research project of the Horizon 2020 framework, which has as its main objective to achieve the optimum and intelligent use of green hydrogen energy for long-term ocean surveys. The ENDURUNS system comprises an Unmanned Surface Vehicle (USV) and an Autonomous Underwater Vehicle (AUV) with gliding capability. The power pack of the USV integrates Li-ion batteries with photovoltaic panels, whilst the AUV employs Li-ion batteries and a hydrogen fuel cell. It is essential to develop a continuous monitoring ca-pability for the different systems of the vehicles. Data transmission between the devices onboard presents challenges due to the volume and structure of the different datasets. A telecommunications network has been designed to manage the operational components considered in the project. The autonomous vehicles perform measurements, providing their position and other data wirelessly. The system will generate a great volume of various signals during the survey. The Remote Control Centre needs to be interfaced with the vehicles in order to receive, manage and store the acquired data. An Underwater Internet of Things (IoT) platform is designed to establish efficient and smart data management. This study presents an exhaustive survey to analyse the telecommunication systems employed in the autonomous vehicles, including the back-end, user interface and mobile units. This paper presents the novel design of the hardware and software structure of the ENDURUNS project with regard to the literature, where its components and their in-terconnection layers are detailed, which is a novel scientific and technological approach for autonomous seabed surveying in deep oceans or in coastal areas.

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“…The IoT concept is based on data sharing between several different devices, be they vehicles or, in their simplest form, smartphones. Thus, shared data can be treated in a way that generates different interpretations and providing significant indicators to, for example, influence users behavior [9]. Then, the device can be part of several IoT networks and with intelligence to infer actions.…”

Section: Introductionmentioning

confidence: 99%

Inference of driver behavior using correlated IoT data from the vehicle telemetry and the driver mobile phone

Silva

Torres

Pinheiro

et al. 2019

Proceedings of the 2019 Federated Conference on Computer Science and Information Systems

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Drivers' behavior in traffic is a determining factor for the rate of accidents on roads and highways. This paper presents the design of an intelligent IoT system capable of inferring and warning about road traffic risks and danger zones, based on data obtained from the vehicles and their drivers mobile phones, thus helping to avoid accidents and seeking to preserve the lives of the passengers. The proposed approach is to collect vehicle telemetry data and mobile phone sensors data through an IoT network and then to analyze the driver's behavior while driving, along with data from the environment. The results of the inference serve to alert drivers about incidents in their trajectory as well as to provide feedback on how they are driving. The proposal is validated using a developed prototype to test its data collection and inference features in a small scale experiment.

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Intelligent data-intensive IoT: A survey

Cited by 9 publications

References 49 publications

Virtualizing the Iot Ecosystem: A Brief Review, Addressing NFV Strategies

Virtualizing the Iot Ecosystem: A Brief Review, Addressing NFV Strategies

Use of UIoT for Offshore Surveys Through Autonomous Vehicles

Inference of driver behavior using correlated IoT data from the vehicle telemetry and the driver mobile phone

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