Towards a Big Data Analytics Framework for IoT and Smart City Applications

Strohbach, Martin; Ziekow, Holger; Gazis, Vangelis; Akiva, Navot

doi:10.1007/978-3-319-09177-8_11

Cited by 123 publications

(45 citation statements)

References 27 publications

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“…Finally, we have study and analyze an integrated Big Data analytical framework for IoT and Smart City application, which contributes three things: (1) we provide an overview of Big Data and IoT technologies including a summary of their relationships; (2) we present a case study in the smart grid domain that illustrates the high‐level requirements towards such an analytical Big Data framework; and (3) we present an initial version of such a framework mainly addressing the volume and velocity challenge. Finally, they present the findings of extended results from the European Union (EU)‐funded project BIG and the German‐funded project PEC . As a conclusion, we have study the combination of the technologies of Mobile Cloud Computing, Big Data, and IoT, and we have study some analysation of existing components and methods of securely integrating Big Data processing with cloud machine‐to‐machine systems based on remote telemetry units .…”

Section: Related Workmentioning

confidence: 95%

Recent advances delivered by Mobile Cloud Computing and Internet of Things for Big Data applications: a survey

2016

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SUMMARYThe Internet of Things (IoT) is a new technology that is growing rapidly in the field of telecommunications and especially in the modern field of wireless telecommunications. The main goal of the interaction and cooperation between things and objects sent through the wireless networks is to fulfill the objective set to them as a combined entity. In addition, based on the technology of wireless networks, both the technologies of Mobile Cloud Computing (MCC) and IoT develop rapidly. In this paper, we combine the two aforementioned technologies (i.e., MCC and IoT) with the technology of the Big Data in order to examine the common features and tο discover which of the MCC and IoT benefits improve the use of the Big Data applications. Finally, we present the contribution of MCC and IoT individually to the technology of Big Data.

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Section: Related Workmentioning

confidence: 95%

Recent advances delivered by Mobile Cloud Computing and Internet of Things for Big Data applications: a survey

2016

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“…In short a storage solution designed for M2M scenarios should provide both kinds of information accesses [28]. The most common solution is using a lambda architecture 1 .…”

Section: Storage Time Constrainsmentioning

confidence: 99%

Scalable semantic aware context storage

Antunes

Gomes

Aguiar

2016

Future Generation Computer Systems

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The number of connected devices collecting and distributing real-world information through various systems, is expected to soar in the coming years. As the number of such connected devices grows, it becomes increasingly difficult to store and share all these new sources of information. Several context representation schemes try to standardize this information, but none of them have been widely adopted. In previous work we addressed this challenge, however our solution had some drawbacks: poor semantic extraction and scalability. In this paper we discuss ways to efficiently deal with representation schemes' diversity and propose a novel d-dimension organization model. Our evaluation shows that d-dimension model improves scalability and semantic extraction.

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“…The researchers from academia and industry also take into consideration the issue of how to integrate other information technologies to make IoT systems an ecosystem, such as a smart city environment. These technologies include wireless sensor network (WSN), cloud computing, data mining, big data analytics, machine learning technologies, and other kinds of information systems (Kim, ; Strohbach et al, ). More precisely, the WSN plays the role of monitoring and gathering data from environment.…”

Section: Data Mining For Iotmentioning

confidence: 99%

Data analytics for internet of things: A review

Tsai

Chiang

et al. 2018

WIREs Data Min & Knowl

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The internet of things (IoT), which provides a way to connect every “thing” via the internet to further develop a convenient environment, has been around for more than a decade. The trend of the development of IoT nowadays is to focus not only on its devices and systems but also on data analysis. The main reason is that data from sensors or systems typically contain valuable information that is very useful for improving the system performance or providing a better service to the user if we come up with a good “data analysis” solution. This paper begins with a brief review of data mining technologies for IoT. Then, a reference data analytics architecture is given to show how data analysis technologies can be applied to an IoT system. Finally, applications, open issues, and possible research directions are addressed. This article is categorized under: Application Areas > Internet and Web‐Based Applications Fundamental Concepts of Data and Knowledge > Key Design Issues in Data Mining Technologies > Computational Intelligence Technologies > Machine Learning

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Towards a Big Data Analytics Framework for IoT and Smart City Applications

Cited by 123 publications

References 27 publications

Recent advances delivered by Mobile Cloud Computing and Internet of Things for Big Data applications: a survey

Recent advances delivered by Mobile Cloud Computing and Internet of Things for Big Data applications: a survey

Scalable semantic aware context storage

Data analytics for internet of things: A review

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