Performance Analysis of a Probabilistic Local Search Algorithm for Indoor Tracking

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Conference Proceeding

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American Society of Civil Engineers

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Many researchers in the construction domain have explored various sensing technologies to acquire location awareness of construction assets. With the use of certain technologies, such as GPS, UWB, and RFID, previous research achieved significant progress for outdoor applications. However, unlike outdoor tracking, indoor environments pose considerable challenges because of the existence of a multitude of interactions among workers, equipment, and materials. These challenges appear in the form of signal interference such as signal degradation, occlusions, obstructions and multipath effects. To overcome signal interference, this study aims to develop and evaluate a probabilistic local search (PLS) algorithm using Bluetooth Low Energy (BLE). This study conducted a site test together with computer simulation to assess the performance of the developed algorithm with respect to accuracy, reliability and robustness. Although the test was conducted in a simple path, noisy data that are generated from the computer simulation reflect the challenges of signal interference, which are expected from occlusions and other objects that potentially introduce signal interference. Based on the test results, the PLS algorithm showed a significant improvement in accuracy, compared with two conventional positioning methods, especially when signal interference exists in the test environment.