Authors:
João Victor Poletti
1
;
Lucas Mauricio Castro e Martins
2
;
Samuel Almeida
1
;
Maristela Holanda
1
and
Rafael Timóteo de Sousa Júnior
2
Affiliations:
1
Department of Computer Science, University of Brasília and Brazil
;
2
Department of Electrical Engineering, University of Brasília and Brazil
Keyword(s):
Internet of Things, Middleware, Data collector, Data Management, Heterogeneity, Challenges, Devices, Analysis.
Related
Ontology
Subjects/Areas/Topics:
Data Communication Networking
;
Enterprise Information Systems
;
Internet of Things
;
Sensor Networks
;
Software Agents and Internet Computing
;
Software and Architectures
;
Telecommunications
Abstract:
The Internet of Things (IoT) emerged as a consequence of the advanced development of increasingly interconnected intelligent devices. These devices integrate within our environment to achieve specific goals that can relate to the areas of object tracking, health care, security, transport, and recreation. However, the amount of devices connected to the Internet and their variety is a problem that needs attention. The purpose of this paper is to present analysis based on real data retrieved from devices inside an IoT universe. The paper proposes a strategy for data extraction as well as a method for handling the information by filtering it and applying an analysis in order to identify different types of measuring devices and techniques to validate the measurements retrieved from the objects. Two techniques from the data mining were used, linear regression and clustering, and another one was developed. The results give different alternatives for the distribution of data in hypothetical
devices that were inferred.
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