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Pervasive Radio Mapping of Industrial Environments Using a Virtual Reality Approach.

Nedelcu AV, Machedon-Pisu M, Duguleana M, Talaba D - ScientificWorldJournal (2015)

Bottom Line: This data is the input of radio mapping algorithms that generate electromagnetic propagation profiles.Such profiles are used for identifying obstacles within the environment and optimum propagation pathways.With the purpose of further optimizing the radio planning process, the authors propose a novel human-network interaction (HNI) paradigm that uses 3D virtual environments in order to display the radio maps in a natural, easy-to-perceive manner.

View Article: PubMed Central - PubMed

Affiliation: Department of Electronics and Computers, Transilvania University of Brasov, 500036 Brasov, Romania.

ABSTRACT
Wireless communications in industrial environments are seriously affected by reliability and performance issues, due to the multipath nature of obstacles within such environments. Special attention needs to be given to planning a wireless industrial network, so as to find the optimum spatial position for each of the nodes within the network, and especially for key nodes such as gateways or cluster heads. The aim of this paper is to present a pervasive radio mapping system which captures (senses) data regarding the radio spectrum, using low-cost wireless sensor nodes. This data is the input of radio mapping algorithms that generate electromagnetic propagation profiles. Such profiles are used for identifying obstacles within the environment and optimum propagation pathways. With the purpose of further optimizing the radio planning process, the authors propose a novel human-network interaction (HNI) paradigm that uses 3D virtual environments in order to display the radio maps in a natural, easy-to-perceive manner. The results of this approach illustrate its added value to the field of radio resource planning of industrial communication systems.

No MeSH data available.


Related in: MedlinePlus

(a) Overall obstacle detection rate; (b) machine tool detection rate; (c) small obstacle detection rate.
© Copyright Policy - open-access
Related In: Results  -  Collection


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fig12: (a) Overall obstacle detection rate; (b) machine tool detection rate; (c) small obstacle detection rate.

Mentions: Five sets of measurements were performed in industrial hall A. The same was done for industrial hall B. The average percentage of successfully detected obstacles is presented in Figure 12.


Pervasive Radio Mapping of Industrial Environments Using a Virtual Reality Approach.

Nedelcu AV, Machedon-Pisu M, Duguleana M, Talaba D - ScientificWorldJournal (2015)

(a) Overall obstacle detection rate; (b) machine tool detection rate; (c) small obstacle detection rate.
© Copyright Policy - open-access
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC4489011&req=5

fig12: (a) Overall obstacle detection rate; (b) machine tool detection rate; (c) small obstacle detection rate.
Mentions: Five sets of measurements were performed in industrial hall A. The same was done for industrial hall B. The average percentage of successfully detected obstacles is presented in Figure 12.

Bottom Line: This data is the input of radio mapping algorithms that generate electromagnetic propagation profiles.Such profiles are used for identifying obstacles within the environment and optimum propagation pathways.With the purpose of further optimizing the radio planning process, the authors propose a novel human-network interaction (HNI) paradigm that uses 3D virtual environments in order to display the radio maps in a natural, easy-to-perceive manner.

View Article: PubMed Central - PubMed

Affiliation: Department of Electronics and Computers, Transilvania University of Brasov, 500036 Brasov, Romania.

ABSTRACT
Wireless communications in industrial environments are seriously affected by reliability and performance issues, due to the multipath nature of obstacles within such environments. Special attention needs to be given to planning a wireless industrial network, so as to find the optimum spatial position for each of the nodes within the network, and especially for key nodes such as gateways or cluster heads. The aim of this paper is to present a pervasive radio mapping system which captures (senses) data regarding the radio spectrum, using low-cost wireless sensor nodes. This data is the input of radio mapping algorithms that generate electromagnetic propagation profiles. Such profiles are used for identifying obstacles within the environment and optimum propagation pathways. With the purpose of further optimizing the radio planning process, the authors propose a novel human-network interaction (HNI) paradigm that uses 3D virtual environments in order to display the radio maps in a natural, easy-to-perceive manner. The results of this approach illustrate its added value to the field of radio resource planning of industrial communication systems.

No MeSH data available.


Related in: MedlinePlus