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System Design for Automating Smart Internet of Things Devices Using Bluetooth Localization
As companies continue to expand, more people have to be managed within a workplace. Along with this comes energy consumption that is increasingly becoming difficult to manage. To solve these issues, this study aims to create a system for employee monitoring and energy optimization. The researchers p...
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creator | Uy, Grant Eldrick M. Choachuy, Alan Carlisle Y. Parocha, Raymark C. Pena, Robert Alfie S. Macabebe, Erees Queen B. |
description | As companies continue to expand, more people have to be managed within a workplace. Along with this comes energy consumption that is increasingly becoming difficult to manage. To solve these issues, this study aims to create a system for employee monitoring and energy optimization. The researchers propose a system that can gather information from occupants and automate smart devices depending on their location. This research primarily seeks to serve as a foundation in creating a flexible, energy-efficient, and scalable system that can be innovated easily. The resulting output is expected to control Internet of Things (IoT) devices based on occupancy data obtained from Bluetooth localization. A system using Bluetooth to retrieve occupancy data was integrated with OpenHAB as the platform to connect and automate IoT devices. The proposed architecture of the system includes Bluetooth localization, IoT automation, and the system interface. This implementation used Bluetooth Low Energy (BLE) beacons sending location data to an ESP32 mesh network, increasing the scalability. The Raspberry Pi server parsed and analyzed the data using Node-RED. The data was then fed to OpenHAB to connect to the IoT devices. After the system was developed, three measurements were used to assess the system, namely location difference, response time, and status accuracy. This study proved the potential and validity of the integration of a Bluetooth positioning system with IoT automation. |
doi_str_mv | 10.1109/IoTaIS56727.2022.9975874 |
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This implementation used Bluetooth Low Energy (BLE) beacons sending location data to an ESP32 mesh network, increasing the scalability. The Raspberry Pi server parsed and analyzed the data using Node-RED. The data was then fed to OpenHAB to connect to the IoT devices. After the system was developed, three measurements were used to assess the system, namely location difference, response time, and status accuracy. 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This implementation used Bluetooth Low Energy (BLE) beacons sending location data to an ESP32 mesh network, increasing the scalability. The Raspberry Pi server parsed and analyzed the data using Node-RED. The data was then fed to OpenHAB to connect to the IoT devices. After the system was developed, three measurements were used to assess the system, namely location difference, response time, and status accuracy. 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Along with this comes energy consumption that is increasingly becoming difficult to manage. To solve these issues, this study aims to create a system for employee monitoring and energy optimization. The researchers propose a system that can gather information from occupants and automate smart devices depending on their location. This research primarily seeks to serve as a foundation in creating a flexible, energy-efficient, and scalable system that can be innovated easily. The resulting output is expected to control Internet of Things (IoT) devices based on occupancy data obtained from Bluetooth localization. A system using Bluetooth to retrieve occupancy data was integrated with OpenHAB as the platform to connect and automate IoT devices. The proposed architecture of the system includes Bluetooth localization, IoT automation, and the system interface. This implementation used Bluetooth Low Energy (BLE) beacons sending location data to an ESP32 mesh network, increasing the scalability. The Raspberry Pi server parsed and analyzed the data using Node-RED. The data was then fed to OpenHAB to connect to the IoT devices. After the system was developed, three measurements were used to assess the system, namely location difference, response time, and status accuracy. This study proved the potential and validity of the integration of a Bluetooth positioning system with IoT automation.</abstract><pub>IEEE</pub><doi>10.1109/IoTaIS56727.2022.9975874</doi><tpages>7</tpages></addata></record> |
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subjects | Automation Bluetooth localization Internet of Things Location awareness mesh networks openHAB Scalability Servers Time factors Time measurement |
title | System Design for Automating Smart Internet of Things Devices Using Bluetooth Localization |
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