Indoor localization and tracking based on received signal strength in wireless sensor networks
Following the success of Global Positioning System (GPS) in outdoor localization, the attention has shifted to indoor localization and its applications. Due to the very different wave propagation effects indoors, outdoor localization techniques are unable to obtain accurate results indoors. This...
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sg-ntu-dr.10356-551342023-07-07T18:00:30Z Indoor localization and tracking based on received signal strength in wireless sensor networks Ng, Jian Min. Er Meng Joo School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering Following the success of Global Positioning System (GPS) in outdoor localization, the attention has shifted to indoor localization and its applications. Due to the very different wave propagation effects indoors, outdoor localization techniques are unable to obtain accurate results indoors. This project explores the feasibility and limitations of several localization techniques based on received signal strength in an indoor environment with the use of Wireless Sensor Network (WSN). The three received signal strength based localization techniques implemented are trilateration, neural network and minimum root mean squared error (RMSE) estimation. The experiments are conducted in a static indoor environment with and without stationary obstacles. The experimental results show that minimum RMSE estimation produces the most accurate result for both scenarios among the three localization techniques with the loss of some precision. Bachelor of Engineering 2013-12-19T06:31:28Z 2013-12-19T06:31:28Z 2013 2013 Final Year Project (FYP) http://hdl.handle.net/10356/55134 en Nanyang Technological University 62 p. application/pdf |
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DRNTU::Engineering::Electrical and electronic engineering Ng, Jian Min. Indoor localization and tracking based on received signal strength in wireless sensor networks |
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Following the success of Global Positioning System (GPS) in outdoor localization, the attention has shifted to indoor localization and its applications. Due to the very different wave propagation effects indoors, outdoor localization techniques are unable to obtain accurate results indoors.
This project explores the feasibility and limitations of several localization techniques based on received signal strength in an indoor environment with the use of Wireless Sensor Network (WSN). The three received signal strength based localization techniques implemented are trilateration, neural network and minimum root mean squared error (RMSE) estimation. The experiments are conducted in a static indoor environment with and without stationary obstacles. The experimental results show that minimum RMSE estimation produces the most accurate result for both scenarios among the three localization techniques with the loss of some precision. |
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Er Meng Joo |
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Er Meng Joo Ng, Jian Min. |
format |
Final Year Project |
author |
Ng, Jian Min. |
author_sort |
Ng, Jian Min. |
title |
Indoor localization and tracking based on received signal strength in wireless sensor networks |
title_short |
Indoor localization and tracking based on received signal strength in wireless sensor networks |
title_full |
Indoor localization and tracking based on received signal strength in wireless sensor networks |
title_fullStr |
Indoor localization and tracking based on received signal strength in wireless sensor networks |
title_full_unstemmed |
Indoor localization and tracking based on received signal strength in wireless sensor networks |
title_sort |
indoor localization and tracking based on received signal strength in wireless sensor networks |
publishDate |
2013 |
url |
http://hdl.handle.net/10356/55134 |
_version_ |
1772827003777449984 |