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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

3D representation of the detected obstacles and their type, red for severe obstacles, and blue for slight obstacles.
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fig8: 3D representation of the detected obstacles and their type, red for severe obstacles, and blue for slight obstacles.

Mentions: The second representation is called “Obstacle Map,” and it represents the map of the discovered obstacles in the industrial building. The obstacles are divided into two types, according to the severity of their disturbance exerted upon the indoor radio spectrum. The more severe obstacles are color-coded red and the less severe ones are color-coded blue, while the areas that do not have obstacles are depicted as green. For 3D representations severe obstacles get a high Y-axis value, slight obstacles get half the Y-axis value that severe obstacles get, and the absence of obstacles is marked with a Y-axis value. This is portrayed in Figure 8 along with Interaction Menu representation of how the user can access the Obstacle Map.


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

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

3D representation of the detected obstacles and their type, red for severe obstacles, and blue for slight obstacles.
© Copyright Policy - open-access
Related In: Results  -  Collection

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

fig8: 3D representation of the detected obstacles and their type, red for severe obstacles, and blue for slight obstacles.
Mentions: The second representation is called “Obstacle Map,” and it represents the map of the discovered obstacles in the industrial building. The obstacles are divided into two types, according to the severity of their disturbance exerted upon the indoor radio spectrum. The more severe obstacles are color-coded red and the less severe ones are color-coded blue, while the areas that do not have obstacles are depicted as green. For 3D representations severe obstacles get a high Y-axis value, slight obstacles get half the Y-axis value that severe obstacles get, and the absence of obstacles is marked with a Y-axis value. This is portrayed in Figure 8 along with Interaction Menu representation of how the user can access the Obstacle Map.

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