‘Big Data’, the ‘Internet of Things’ and the ‘Internet of Signs’

O’Leary, Daniel E.

doi:10.1002/isaf.1336

Cited by 116 publications

(47 citation statements)

References 17 publications

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“…With the recent rapid development of internet and cloud computing, we are entering the era of 'big data' with the 'Internet of Things' and People (O'Leary, 2013). 'Internet of Things' is configured to include inputs from humans and many different things linked to the internet (O'Leary, 2013).…”

Section: Pedestrian Activity 'Big Data' and Google Street View Imagesmentioning

confidence: 99%

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‘Big data’ for pedestrian volume: Exploring the use of Google Street View images for pedestrian counts

et al. 2015

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Section: Pedestrian Activity 'Big Data' and Google Street View Imagesmentioning

confidence: 99%

“…'Internet of Things' is configured to include inputs from humans and many different things linked to the internet (O'Leary, 2013). 'Big data' was described as data gathered from different online sources by Goodchild (2013).…”

Section: Pedestrian Activity 'Big Data' and Google Street View Imagesmentioning

confidence: 99%

‘Big data’ for pedestrian volume: Exploring the use of Google Street View images for pedestrian counts

et al. 2015

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“…This massive and heterogeneous dataset, generated by IoT environments, presents a number challenges regarding storage and processing. In this context, the data volume generated and consumed by IoT applications can be characterized as Big Data and the IoT instances as a Big Data sources [14,15]. …”

Section: Big Data Management For Iot Middlewarementioning

confidence: 99%

Distributed Data Service for Data Management in Internet of Things Middleware

Huacarpuma

Sousa

Holanda

et al. 2017

Sensors

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The development of the Internet of Things (IoT) is closely related to a considerable increase in the number and variety of devices connected to the Internet. Sensors have become a regular component of our environment, as well as smart phones and other devices that continuously collect data about our lives even without our intervention. With such connected devices, a broad range of applications has been developed and deployed, including those dealing with massive volumes of data. In this paper, we introduce a Distributed Data Service (DDS) to collect and process data for IoT environments. One central goal of this DDS is to enable multiple and distinct IoT middleware systems to share common data services from a loosely-coupled provider. In this context, we propose a new specification of functionalities for a DDS and the conception of the corresponding techniques for collecting, filtering and storing data conveniently and efficiently in this environment. Another contribution is a data aggregation component that is proposed to support efficient real-time data querying. To validate its data collecting and querying functionalities and performance, the proposed DDS is evaluated in two case studies regarding a simulated smart home system, the first case devoted to evaluating data collection and aggregation when the DDS is interacting with the UIoT middleware, and the second aimed at comparing the DDS data collection with this same functionality implemented within the Kaa middleware.

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“…They are: Volume, Variety, Value, Velocity, Veracity and Variability (Bellini et al, 2013;Demchenko et al, 2013;Jean-François Lavignon, 2013;O'Leary, 2013;Jagadish et al, 2014):…”

Section: Characteristics Implementation and Technology Of Big Datamentioning

confidence: 99%

Confluences among Big Data, Finite Element Analysis and High Performance Computing

Wang¹,

Wang²,

Alexander³

2015

American Journal of Engineering and Applied Sciences

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Big Data analyzes correlations from huge raw data and predicts outcomes. It has great impacts on scientific discoveries and value creation. High Performance Computing (HPC) uses parallel processing and advanced programs or software packages to complete complicated jobs quickly. Finite Element Method (FEM) is very powerful in scientific computation and engineering analysis. It has created huge values in almost every area of engineering. In a lot of applications, Finite Element Analysis (FEA) strongly relies on advanced computer technology and HPC. Big Data will play an important role in FEA and HPC. This paper presents confluences among Big Data, FEA and HPC.

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‘Big Data’, the ‘Internet of Things’ and the ‘Internet of Signs’

Cited by 116 publications

References 17 publications

‘Big data’ for pedestrian volume: Exploring the use of Google Street View images for pedestrian counts

‘Big data’ for pedestrian volume: Exploring the use of Google Street View images for pedestrian counts

Distributed Data Service for Data Management in Internet of Things Middleware

Confluences among Big Data, Finite Element Analysis and High Performance Computing

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