Using Received Strength Signal Indication for Indoor Mobile Localization Based on Machine Learning Technique
The techniques of triangulation in Euclidean geometry can be considered the base of a wide range of positioning techniques for sensor networks; where they deduced the sensor locations by using its geometrical characteristics. This work presents a completely different method based on machine learning, where the data is obtained directly from the natural coordinate systems through the readings provided by Bluetooth Low Energy Devices. The known locations of beacon nodes in the network and the Received Strength Signal Indication (RSSI) can be exploited to detect the current position on mobile device based on the Bluetooth technology.
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Using Received Strength Signal Indication for Indoor Mobile Localization Based on Machine Learning Technique
Semantic Scholar · Computer Science · 2020
Abstract
The techniques of triangulation in Euclidean geometry can be considered the base of a wide range of positioning techniques for sensor networks; where they deduced the sensor locations by using its geometrical characteristics. This work presents a completely different method based on machine learning, where the data is obtained directly from the natural coordinate systems through the readings provided by Bluetooth Low Energy Devices. The known locations of beacon nodes in the network and the Received Strength Signal Indication (RSSI) can be exploited to detect the current position on mobile device based on the Bluetooth technology.
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