In the context of fingerprinting (FP) applications, this paper investigates the reduction of quantization levels in the Received Signal Strength Indicator (RSSI) till to its binary representation. One of the common drawbacks of FP is the large data size and consequently the large search space and computational load as a result of either vastness of the positioning area or the finer resolution in the FP grid map. This complexity can be limited reducing the RSSI quantization till to a simple binary indicator at the expense of an increased number of reference points or beacons. This approach turns out to be advantageous for the deployment of FP systems based on diffused beacons equipped with inexpensive technologies, such as Bluetooth Low Energy (BLE) or other technologies for the Internet of Things (IoT). An appropriate quantization and design of RSSI signatures will make possible the deployment of FP in larger areas maintaining the same computational load and/or the desired localization performance. The experimental results confirm promising computational savings without a relevant impact on the localization performance.

Binary fingerprinting-based indoor positioning systems

M. Mizmizi;L. Reggiani
2017-01-01

Abstract

In the context of fingerprinting (FP) applications, this paper investigates the reduction of quantization levels in the Received Signal Strength Indicator (RSSI) till to its binary representation. One of the common drawbacks of FP is the large data size and consequently the large search space and computational load as a result of either vastness of the positioning area or the finer resolution in the FP grid map. This complexity can be limited reducing the RSSI quantization till to a simple binary indicator at the expense of an increased number of reference points or beacons. This approach turns out to be advantageous for the deployment of FP systems based on diffused beacons equipped with inexpensive technologies, such as Bluetooth Low Energy (BLE) or other technologies for the Internet of Things (IoT). An appropriate quantization and design of RSSI signatures will make possible the deployment of FP in larger areas maintaining the same computational load and/or the desired localization performance. The experimental results confirm promising computational savings without a relevant impact on the localization performance.
Proceedings 2017 International Conference on Indoor Positioning and Indoor Navigation
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1063833
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