A INDOOR POSITION ROUTING (IPR) AND DATA MONITOR USING BLUETOOTH LOW ENERGY TECHNOLOGY (iBEACON-BLE): AN IMPLEMENTATION STUDY
Keywords:Bluetooth, BLE, iBeacon, Indoor, Mapping, Broadcasting, TX, RX.
Rapid advancements in mobile industry have emerged new technological ideas and applications for researchers by allowing smart devices over the last decade. In recent years, the need for Indoor Position Routing (IPR) and Location-Based Advertisements (LBA) systems are increasingly common, IPR and LBA systems have been becoming very popular. Nowadays, it has become possible to create software and hardware applications for IPR and LBA in indoor environments, thanks to developments of different technologies. The development of the system should be based on low-cost technology, it should be suitable for integration and indoors operation. New options and possibilities for indoor locations are presented by the iBeacon-Bluetooth Low Energy (BLE) radio protocol. iBeacon-BLE supports portable battery-powered system that can be smoothly distributed at low cost giving it distinct advantages over Wi-Fi. Therefore, in this study, a technological infrastructure is created to solve the navigation problem in closed locations using iBeacon-BLE technology, a data monitoring information system is proposed for smart devices of currently available technology for IPR, LBA with using iBeacon-BLE. The localization of the objects based on iBeacon-BLE and their combination are determined using the measured data with the developed application. To build an IPR system for indoor environments, the available hardware, software, and network technologies are presented. The concept of the indoor monitoring system and the technologies can be used to develop the IPR system are presented. This system is made up of iBeacon-BLE sensor nodes, a smart device and a mobile application that provides IPR and LBA services by measuring the distance between Transmitter (TX) and Receiver (RX). The proposed model uses the trilateration method, it allows the mobile application to determine the exact location of the object at the micro-level size. The proposed model uses sensory data to identify and trilateration the object’s position.
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