RSSI-based environment monitoring and accurate event detection
Brockmann, Falk
Produktnummer:
18c977af57dca241a8b0ef666473617a55
Autor: | Brockmann, Falk |
---|---|
Themengebiete: | BLE Human queue monitoring Passive presence detection People counting RSSI |
Veröffentlichungsdatum: | 13.03.2019 |
EAN: | 9783832548681 |
Sprache: | Englisch |
Seitenzahl: | 164 |
Produktart: | Kartoniert / Broschiert |
Verlag: | Logos Berlin |
Produktinformationen "RSSI-based environment monitoring and accurate event detection"
Past research on the analysis of the Received Signal Strength Indicator (RSSI) of a radio transmission indicates that radio signals can be used as passive sensing technology to detect the presence of persons. This way, a detection system can be built from inexpensive commercial of-the-shelf transceivers with no need for possibly expensive additional sensing hardware. Furthermore, radio signals can penetrate obstacles, like walls or furniture, which increases the detection range in cluttered indoor environments. However, the RSSI of a radio transmission itself has a naturally fluctuating behaviour due to the effects of multipath propagation. Because of these circumstances the detection accuracy is an important feature for any RF-based passive presence detection application. Here, we evaluate different means to improve the detection accuracy of passive presence detection based on the application scenarios velocity estimation and queueing systems. First, we evaluate and compare 15 techniques for estimating the velocity of a person. The analysis is based on each technique's detection accuracy when sensing a Line of Sight (LoS) crossing event between radio transceivers. Second, we analyse Bluetooth Low Energy as alternative radio technology for RSSI-based passive presence detection. Third, we create a prototype queueing system estimating the number of people waiting in line and the occupancy level of the waiting area based on the insights of the previous sections. The resulting system has a high portability, is easy to deploy and has a high detection accuracy.

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