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A unified framework for real-time streaming and processing of IoT data
Linnaeus University, Faculty of Technology, Department of Media Technology.
2017 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

The emergence of the Internet of Things (IoT) is introducing a new era to the realm of computing and technology. The proliferation of sensors and actuators that are embedded in things enables these devices to understand the environments and respond accordingly more than ever before. Additionally, it opens the space to unlimited possibilities for building applications that turn this sensation into big benefits, and within various domains. From smart cities to smart transportation and smart environment and the list is quite long. However, this revolutionary spread of IoT devices and technologies rises big challenges. One major challenge is the diversity in IoT vendors that results in data heterogeneity. This research tackles this problem by developing a data management tool that normalizes IoT data. Another important challenge is the lack of practical IoT technology with low cost and low maintenance. That has often limited large-scale deployments and mainstream adoption. This work utilizes open-source data analytics in one unified IoT framework in order to address this challenge. What is more, billions of connected things are generating unprecedented amounts of data from which intelligence must be derived in real-time. This unified framework processes real-time streams of data from IoT. A questionnaire that involved participants with background knowledge in IoT was conducted in order to collect feedback about the proposed framework. The aspects of the framework were presented to the participants in a form of demonstration video describing the work that has been done. Finally, using the participants’ feedback, the contribution of the developed framework to the IoT was discussed and presented.

Place, publisher, year, edition, pages
2017. , p. 65
Keywords [en]
Internet of Things, Real-time, Data Analytics, IoT Framework, Data Heterogeneity, IoT Data Streaming
National Category
Media and Communication Technology
Identifiers
URN: urn:nbn:se:lnu:diva-66057OAI: oai:DiVA.org:lnu-66057DiVA, id: diva2:1118863
Subject / course
Media Technology
Educational program
Social Media and Web Technologies, Master Programme, 120 credits
Supervisors
Examiners
Available from: 2017-07-03 Created: 2017-07-02 Last updated: 2018-01-13Bibliographically approved

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fulltext(2119 kB)390 downloads
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Zamam, Mohamad
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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf