In smart living environments many sensors are employed to improve the quality of daily life, collecting a variety of heterogeneous signals, characterized by different features. In order to save storage space and power consumption, a valid support for ambient assisted living may be provided by hardware architectures, to acquire while compressing the signals of interest: the Analog-to-Information Converters (AIC). This paper presents a LabVIEW implementation of the AIC based on the Random Demodulation principle. In particular, the phase of compression is designed through several LabVIEW building blocks, while the phase of reconstruction is implemented through a MATLAB script. The performed simulations show that, while performing the sub-sampling, the AIC can reconstruct correctly signals of interest for living environments.

A support for signal compression in living environments: the Analog-to-Information Converter / Iadarola, G.; Spinsante, S.; De Vito, L.; Lamonaca, F.. - ELETTRONICO. - (2022), pp. 292-297. (Intervento presentato al convegno 2022 IEEE International Workshop on Metrology for Living Environment, MetroLivEn 2022 tenutosi a ita nel 2022) [10.1109/MetroLivEnv54405.2022.9826923].

A support for signal compression in living environments: the Analog-to-Information Converter

Iadarola G.;Spinsante S.;
2022-01-01

Abstract

In smart living environments many sensors are employed to improve the quality of daily life, collecting a variety of heterogeneous signals, characterized by different features. In order to save storage space and power consumption, a valid support for ambient assisted living may be provided by hardware architectures, to acquire while compressing the signals of interest: the Analog-to-Information Converters (AIC). This paper presents a LabVIEW implementation of the AIC based on the Random Demodulation principle. In particular, the phase of compression is designed through several LabVIEW building blocks, while the phase of reconstruction is implemented through a MATLAB script. The performed simulations show that, while performing the sub-sampling, the AIC can reconstruct correctly signals of interest for living environments.
2022
978-1-6654-0893-6
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11566/309797
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