Detecção da direcionalidade do movimento humano utilizando perturbações do sinal eletromagnético de interfaces IEEE 802.11
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2018-10-08
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Universidade Federal de Goiás
Resumo
The movement flow detection in indoor environments requires the aquisition and implantation of specialized devices. The perturbations that can affect the electromagnetic signals used by 802.11 interfaces make this type of device a low-cost and widely available movement sensor. Most indoor environments have a 802.11 interface, which makes the use of this type of devices a good option as it doesn't requires any new device. In this work, we propose the WiDMove, a proposal to detect the movement flows in an indoor environment using the channel quality measurements (known as Channel State Information - CSI) offered
by the IEEE 802.11n standard. Our proposal is based on signal processing and pattern recognition techniques, which allow us to extract and classify event signatures using the CSI. In lab tests with off-the-shelf 802.11 interfaces, we collected CSI samples that were affected by 8 different people. From this collected data we extracted the signature of the entry and exit events using some techniques such as Principal Component Analysis (PCA), Short-Time Fourier Transform (STFT) and Continuous Wavelet Transform (CWT). We trained two model types, the first based on a Support Vector Machine (SVM) classifier and the second based on a Multi Layer Perceptral (MLP) neural network. We validated this models with average accuracy experiments and with the cross-validation, including the K-Fold and Leave-One-Out
techniques. WiDMove presented that can reach an average accuracy above 93% and that we can train neural networks that can reach an accuracy above 97%.
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SILVA, Bruno Soares da. Detecção da direcionalidade do movimento humano utilizando perturbações do sinal eletromagnético de interfaces IEEE 802.11. 2018. 66 f. Dissertação (Mestrado em Ciência da Computação) - Universidade Federal de Goiás, Goiânia, 2018.