Mitigation of the ground reflection effect in real-time locating systems based on wireless sensor networks by using artificial neural networks
Wireless sensor networks (WSNs) have become much more relevant in recent years, mainly because they can be used in a wide diversity of applications. Real-time locating systems (RTLSs) are one of the most promising applications based on WSNs and represent a currently growing market. Specifically, WSN...
| Autores Principales: | Pinzón Trejos, Cristian, Tapia, Dante, De Paz, Juan, Alonso, Ricardo, Pinzón, Cristian, Bajo, Javier, Corchado, Juan |
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| Formato: | Artículo |
| Idioma: | Inglés Inglés |
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2018
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| Acceso en línea: |
http://ridda2.utp.ac.pa/handle/123456789/4781 |
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RepoUTP4781 |
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dspace |
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RepoUTP47812021-07-06T15:35:04Z Mitigation of the ground reflection effect in real-time locating systems based on wireless sensor networks by using artificial neural networks Pinzón Trejos, Cristian Tapia, Dante De Paz, Juan Alonso, Ricardo Pinzón, Cristian Bajo, Javier Corchado, Juan Wireless sensor networks Real-time location systems Artificial neural networks Ground reflection effect Wireless sensor networks Real-time location systems Artificial neural networks Ground reflection effect Wireless sensor networks (WSNs) have become much more relevant in recent years, mainly because they can be used in a wide diversity of applications. Real-time locating systems (RTLSs) are one of the most promising applications based on WSNs and represent a currently growing market. Specifically, WSNs are an ideal alternative to develop RTLSs aimed at indoor environments where existing global navigation satellite systems, such as the global positioning system, do not work correctly due to the blockage of the satellite signals. However, accuracy in indoor RTLSs is still a problem requiring novel solutions. One of the main challenges is to deal with the problems that arise from the effects of the propagation of radiofrequency waves, such as attenuation, diffraction, reflection and scattering. These effects can lead to other undesired problems, such as multipath. When the ground is responsible for wave reflections, multipath can be modeled as the ground reflection effect. This paper presents an innovative mathematical model for improving the accuracy of RTLSs, focusing on the mitigation of the ground reflection effect by using multilayer perceptron artificial neural networks. Wireless sensor networks (WSNs) have become much more relevant in recent years, mainly because they can be used in a wide diversity of applications. Real-time locating systems (RTLSs) are one of the most promising applications based on WSNs and represent a currently growing market. Specifically, WSNs are an ideal alternative to develop RTLSs aimed at indoor environments where existing global navigation satellite systems, such as the global positioning system, do not work correctly due to the blockage of the satellite signals. However, accuracy in indoor RTLSs is still a problem requiring novel solutions. One of the main challenges is to deal with the problems that arise from the effects of the propagation of radiofrequency waves, such as attenuation, diffraction, reflection and scattering. These effects can lead to other undesired problems, such as multipath. When the ground is responsible for wave reflections, multipath can be modeled as the ground reflection effect. This paper presents an innovative mathematical model for improving the accuracy of RTLSs, focusing on the mitigation of the ground reflection effect by using multilayer perceptron artificial neural networks. 2018-06-05T19:02:02Z 2018-06-05T19:02:02Z 01/01/2013 01/01/2013 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion http://ridda2.utp.ac.pa/handle/123456789/4781 eng eng https://creativecommons.org/licenses/by-nc-sa/4.0/ info:eu-repo/semantics/openAccess application/pdf application/pdf |
| institution |
Universidad Tecnológica de Panamá |
| collection |
Repositorio UTP – Ridda2 |
| language |
Inglés Inglés |
| topic |
Wireless sensor networks Real-time location systems Artificial neural networks Ground reflection effect Wireless sensor networks Real-time location systems Artificial neural networks Ground reflection effect |
| spellingShingle |
Wireless sensor networks Real-time location systems Artificial neural networks Ground reflection effect Wireless sensor networks Real-time location systems Artificial neural networks Ground reflection effect Pinzón Trejos, Cristian Tapia, Dante De Paz, Juan Alonso, Ricardo Pinzón, Cristian Bajo, Javier Corchado, Juan Mitigation of the ground reflection effect in real-time locating systems based on wireless sensor networks by using artificial neural networks |
| description |
Wireless sensor networks (WSNs) have become much more relevant in recent years, mainly because they can be used in a wide diversity of applications. Real-time locating systems (RTLSs) are one of the most promising applications based on WSNs and represent a currently growing market. Specifically, WSNs are an ideal alternative to develop RTLSs aimed at indoor environments where existing global navigation satellite systems, such as the global positioning system, do not work correctly due to the blockage of the satellite signals. However, accuracy in indoor RTLSs is still a problem requiring novel solutions. One of the main challenges is to deal with the problems that arise from the effects of the propagation of radiofrequency waves, such as attenuation, diffraction, reflection and scattering. These effects can lead to other undesired problems, such as multipath. When the ground is responsible for wave reflections, multipath can be modeled as the ground reflection effect. This paper presents an innovative mathematical model for improving the accuracy of RTLSs, focusing on the mitigation of the ground reflection effect by using multilayer perceptron artificial neural networks. |
| format |
Artículo |
| author |
Pinzón Trejos, Cristian Tapia, Dante De Paz, Juan Alonso, Ricardo Pinzón, Cristian Bajo, Javier Corchado, Juan |
| author_sort |
Pinzón Trejos, Cristian |
| title |
Mitigation of the ground reflection effect in real-time locating systems based on wireless sensor networks by using artificial neural networks |
| title_short |
Mitigation of the ground reflection effect in real-time locating systems based on wireless sensor networks by using artificial neural networks |
| title_full |
Mitigation of the ground reflection effect in real-time locating systems based on wireless sensor networks by using artificial neural networks |
| title_fullStr |
Mitigation of the ground reflection effect in real-time locating systems based on wireless sensor networks by using artificial neural networks |
| title_full_unstemmed |
Mitigation of the ground reflection effect in real-time locating systems based on wireless sensor networks by using artificial neural networks |
| title_sort |
mitigation of the ground reflection effect in real-time locating systems based on wireless sensor networks by using artificial neural networks |
| publishDate |
2018 |
| url |
http://ridda2.utp.ac.pa/handle/123456789/4781 |
| _version_ |
1796209798526533632 |
| score |
12.041272 |