Your browser doesn't support javascript.
loading
A Rescue-Assistance Navigation Method by Using the Underground Location of WSN after Disasters.
Li, Shuo; Guo, Tiancheng; Mo, Ran; Zhao, Xiaoshuai; Zhou, Feng; Liu, Weirong; Peng, Jun.
Afiliación
  • Li S; School of Electrical and Information Engineering, Changsha University of Science & Technology, Changsha 410114, China.
  • Guo T; School of Electrical and Information Engineering, Changsha University of Science & Technology, Changsha 410114, China.
  • Mo R; School of Computer Science and Engineering, Central South University, Changsha 410083, China.
  • Zhao X; School of Computer Science and Engineering, Central South University, Changsha 410083, China.
  • Zhou F; School of Electrical and Information Engineering, Changsha University of Science & Technology, Changsha 410114, China.
  • Liu W; School of Computer Science and Engineering, Central South University, Changsha 410083, China.
  • Peng J; School of Computer Science and Engineering, Central South University, Changsha 410083, China.
Sensors (Basel) ; 20(8)2020 Apr 11.
Article en En | MEDLINE | ID: mdl-32290518
A challenging rescue task for the underground disaster is to guide survivors in getting away from the dangerous area quickly. To address the issue, an escape guidance path developing method is proposed based on anisotropic underground wireless sensor networks under the condition of sparse anchor nodes. Firstly, a hybrid channel model was constructed to reflect the relationship between distance and receiving signal strength, which incorporates the underground complex communication characteristics, including the analytical ray wave guide model, the Shadowing effect, the tunnel size, and the penetration effect of obstacles. Secondly, a trustable anchor node selection algorithm with node movement detection is proposed, which solves the problem of high-precision node location in anisotropic networks with sparse anchor nodes after the disaster. Consequently, according to the node location and the obstacles, the optimal guidance path is developed by using the modified minimum spanning tree algorithm. Finally, the simulations in the 3D scene are conducted to verify the performance of the proposed method on the localization accuracy, guidance path effectiveness, and scalability.
Asunto(s)
Palabras clave
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Trabajo de Rescate / Desastres / Tecnología Inalámbrica Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: Sensors (Basel) Año: 2020 Tipo del documento: Article País de afiliación: China Pais de publicación: Suiza
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Trabajo de Rescate / Desastres / Tecnología Inalámbrica Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: Sensors (Basel) Año: 2020 Tipo del documento: Article País de afiliación: China Pais de publicación: Suiza