Indoor positioning for autonomous hospital bed
This FYP project explores the possibility of using BLE for localisation of autonomous hospital beds (AHB). An indoor positioning system (IPS) was developed based on BLE Fingerprint method and experiments were conducted to find out the best suited configuration for the application. An optimal balance...
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2020
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sg-ntu-dr.10356-1402452023-03-04T20:00:31Z Indoor positioning for autonomous hospital bed Koh, Yu Xiang Li King Ho Holden School of Mechanical and Aerospace Engineering holdenli@ntu.edu.sg Engineering::Mechanical engineering::Mechatronics This FYP project explores the possibility of using BLE for localisation of autonomous hospital beds (AHB). An indoor positioning system (IPS) was developed based on BLE Fingerprint method and experiments were conducted to find out the best suited configuration for the application. An optimal balance between cost and accuracy is found after rounds of experiments and analysis. The optimal system setup has beacons spaced two meters apart and the Fingerprint Server uses Kalman Filter in conjunction with Fingerprint Scoring Type 3 (a comparison algorithm developed in this project) to match fingerprints and return an estimated location to medical staff. With the optimal system implemented, the system provides a stable reading with accuracy of 2.3m with 99.7% confidence. While the bed is moving at speed of 0.75m/s, there is poor localisation accuracy of 10m. However, medical staff can expect the localisation to have a stabilisation time of 5 seconds—time for location readings to reach ±1m of the actual location and attain the static accuracy of 2.3m with 99.7%. Bachelor of Engineering (Mechanical Engineering) 2020-05-27T08:33:44Z 2020-05-27T08:33:44Z 2020 Final Year Project (FYP) https://hdl.handle.net/10356/140245 en C075 application/pdf Nanyang Technological University |
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Engineering::Mechanical engineering::Mechatronics Koh, Yu Xiang Indoor positioning for autonomous hospital bed |
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This FYP project explores the possibility of using BLE for localisation of autonomous hospital beds (AHB). An indoor positioning system (IPS) was developed based on BLE Fingerprint method and experiments were conducted to find out the best suited configuration for the application. An optimal balance between cost and accuracy is found after rounds of experiments and analysis. The optimal system setup has beacons spaced two meters apart and the Fingerprint Server uses Kalman Filter in conjunction with Fingerprint Scoring Type 3 (a comparison algorithm developed in this project) to match fingerprints and return an estimated location to medical staff. With the optimal system implemented, the system provides a stable reading with accuracy of 2.3m with 99.7% confidence. While the bed is moving at speed of 0.75m/s, there is poor localisation accuracy of 10m. However, medical staff can expect the localisation to have a stabilisation time of 5 seconds—time for location readings to reach ±1m of the actual location and attain the static accuracy of 2.3m with 99.7%. |
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Li King Ho Holden |
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Li King Ho Holden Koh, Yu Xiang |
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Final Year Project |
author |
Koh, Yu Xiang |
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Koh, Yu Xiang |
title |
Indoor positioning for autonomous hospital bed |
title_short |
Indoor positioning for autonomous hospital bed |
title_full |
Indoor positioning for autonomous hospital bed |
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Indoor positioning for autonomous hospital bed |
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Indoor positioning for autonomous hospital bed |
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indoor positioning for autonomous hospital bed |
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Nanyang Technological University |
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2020 |
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https://hdl.handle.net/10356/140245 |
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