Analysis of Indoor Localization Methods for Smart Home Automation Systems
Ettu, Nurudeen (2024)
2024
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2024121937624
https://urn.fi/URN:NBN:fi:amk-2024121937624
Tiivistelmä
The Internet of Things (IoT) development on smart home automation solutions has had an extraordinary effect, providing innovative ways to increase efficiency, convenience, and energy management. This thesis studies the capabilities and limitations of indoor localization technologies like Bluetooth Low Energy (BLE) and Ultra Wideband (UWB) for accurate indoor positioning systems in smart home environments. BLE offers ease of implementation and cost effectiveness while UWB offers accuracy and precise tracking abilities allowing these technologies to improve user experience while optimizing resource allocation. This study provided a thorough assessment of BLE and UWB.
This study aimed to analyze BLE and UWB use in IoT applications by analyzing their range with particular attention paid to IoT home operations. A comparison analysis between accuracy and scalability under environmental conditions. The methodologies used to work on this include hardware implementations like ESP32S3 microcontrollers for BLE applications and DWM3000 for UWB applications with advanced positioning algorithms implemented during real world tests.
The results of this study provided insights into the strengths and limitations of BLE and UWB technologies for use in IoT enabled smart homes, offering practical recommendations. Furthermore, this study highlighted the accuracy and errors between the technologies within a controlled environment. The use of UWB for accurate indoor localization would be more practical because of its meter precision with Time of Flight (ToF), and high resistance to interference.
This study aimed to analyze BLE and UWB use in IoT applications by analyzing their range with particular attention paid to IoT home operations. A comparison analysis between accuracy and scalability under environmental conditions. The methodologies used to work on this include hardware implementations like ESP32S3 microcontrollers for BLE applications and DWM3000 for UWB applications with advanced positioning algorithms implemented during real world tests.
The results of this study provided insights into the strengths and limitations of BLE and UWB technologies for use in IoT enabled smart homes, offering practical recommendations. Furthermore, this study highlighted the accuracy and errors between the technologies within a controlled environment. The use of UWB for accurate indoor localization would be more practical because of its meter precision with Time of Flight (ToF), and high resistance to interference.