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JLGBMLoc—A Novel High-Precision Indoor Localization Method Based on LightGBM

Combining RSSI and Accelerometer Features for Room-Level Localization

Centre for Research and Technology Hellas, Information Technologies Institute, 6th Km Charilaou-Thermi, 57001 Thessaloniki, Greece
Author to whom correspondence should be addressed.
Academic Editor: David Plets
Sensors 2021, 21(8), 2723;
Received: 24 March 2021 / Revised: 7 April 2021 / Accepted: 9 April 2021 / Published: 13 April 2021
(This article belongs to the Section Intelligent Sensors)
The continuing advancements in technology have resulted in an explosion in the use of interconnected devices and sensors. Internet-of-Things (IoT) systems are used to provide remote solutions in different domains, like healthcare and security. A common service offered by IoT systems is the estimation of a person’s position in indoor spaces, which is quite often achieved with the exploitation of the Received Signal Strength Indication (RSSI). Localization tasks with the goal to locate the room are actually classification problems. Motivated by a current project, where there is the need to locate a missing child in crowded spaces, we intend to test the added value of using an accelerometer along with RSSI for room-level localization and assess the performance of ensemble learning methods. We present here the results of this preliminary approach of the early and late fusion of RSSI and accelerometer features in room-level localization. We further test the performance of the feature extraction from RSSI values. The classification algorithms and the fusion methods used to predict the room were evaluated using different protocols applied to a public dataset. The experimental results revealed better performance of the RSSI extracted features, while the accelerometer’s individual performance was poor and subsequently affected the fusion results. View Full-Text
Keywords: room-level localization; RSSI; inertial sensors; fusion room-level localization; RSSI; inertial sensors; fusion
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MDPI and ACS Style

Tsanousa, A.; Xefteris, V.-R.; Meditskos, G.; Vrochidis, S.; Kompatsiaris, I. Combining RSSI and Accelerometer Features for Room-Level Localization. Sensors 2021, 21, 2723.

AMA Style

Tsanousa A, Xefteris V-R, Meditskos G, Vrochidis S, Kompatsiaris I. Combining RSSI and Accelerometer Features for Room-Level Localization. Sensors. 2021; 21(8):2723.

Chicago/Turabian Style

Tsanousa, Athina, Vasileios-Rafail Xefteris, Georgios Meditskos, Stefanos Vrochidis, and Ioannis Kompatsiaris. 2021. "Combining RSSI and Accelerometer Features for Room-Level Localization" Sensors 21, no. 8: 2723.

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