Big data applications on the Internet of Things: A systematic literature review

2021 ◽  
Author(s):  
Ulkar Ahmadova ◽  
Mustafa Mustafayev ◽  
Behnam Kiani Kalejahi ◽  
Saeed Saeedvand ◽  
Amir Masoud Rahmani
Keyword(s):  
Big Data ◽  
Internet Of Things ◽  
Literature Review ◽  
Systematic Literature Review ◽  
The Internet ◽  
Big Data Applications ◽  
The Internet Of Things

scholarly journals Assessing the Role of Big Data and the Internet of Things on the Transition to Circular Economy: Part I : An extension of the ReSOLVE framework proposal through a literature review

2020 ◽  
Vol 64 (1) ◽  
pp. 19-31 ◽  
Author(s):  
Gustavo Cattelan Nobre ◽  
Elaine Tavares
Keyword(s):  
Big Data ◽  
Internet Of Things ◽  
Literature Review ◽  
Circular Economy ◽  
Grey Literature ◽  
Modern Technology ◽  
The Internet ◽  
Extensive Literature ◽  
Statistical Tool ◽  
The Internet Of Things

The debate about circular economy (CE) is increasingly present in the strategic agenda of organisations around the world, being driven by government agencies and general population pressures, or by organisations’ own vision for a sustainable future. This is due in part to the increasing possibility of turning original theoretical CE proposals into real economically viable initiatives, now possible with modern technology applications such as big data and the internet of things (IoT). Information technology (IT) professionals have been called upon to incorporate technology projects into their strategic plans to support their organisations’ transition to CE, but a structured framework with the necessary IT capabilities still lacks. This study focuses on taking the first step towards this path, by extending the technology attributes present on the existing Ellen MacArthur Foundation (EMF) Regenerate, Share, Optimise, Loop, Virtualise and Exchange (ReSOLVE) framework. The research was conducted based on an extensive literature review through 226 articles retrieved from Scopus® and Web of ScienceTM databases, which were triangulated, validated and complemented with content analysis using the ‘R’ statistical tool, grey literature research and inputs from specialists. Part I describes the introduction and methods used in this study.

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