Bluetooth low energy (BLE) based asset tagging system
Asset Tracking is a valuable technology that most businesses want to leverage on, especially the well developed GPS-based outdoor asset tracking system. However, indoor localization is still not well developed as GPS is not accurate in indoor environment. One good option is to utilize BLE technol...
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| Format: | Final Year Project |
| Language: | English |
| Published: |
Nanyang Technological University
2022
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| Online Access: | https://hdl.handle.net/10356/157760 |
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| Institution: | Nanyang Technological University |
| Language: | English |
| Summary: | Asset Tracking is a valuable technology that most businesses want to leverage on,
especially the well developed GPS-based outdoor asset tracking system. However,
indoor localization is still not well developed as GPS is not accurate in indoor
environment. One good option is to utilize BLE technology for indoor
localization. However, by using the RSSI value itself is not accurate. Therefore,
this project will develop an asset tracking system to collect RSSI fingerprinting
data and increase localization accuracy by using various machine learning
algorithms. The experimental results show a significant improvement over a
previous BLE indoor localization study, but there is still opportunity for
improvement, such as adopting different machine learning techniques as a
comparison. |
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