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Abstract
This thesis provides new directions in the impedance spectroscopy, making it an interesting investigation technique for emerging smart sensors. Modern technologies increasingly require sensors capable of giving accurate measurements extracted among a lot of undesired surrounding information while maintaining low
power consumptions. In this scenario, the main focuses of this thesis are: 1) developing an accurate complex impedance system, 2) extracting the augmented information using multivariate statistical analysis and 3) implementing IS-based systems with low power consumptions. The first project shows the design of a miniaturized, low power and accurate vector analyser for multi-parameter measurements in real-time. It is a versatile platform well-suited to be interfaced with various impedance-based sensors. The vector analyser, based on an accurate application specific integrated circuit and a digital interface, has been statistically characterized in order to evaluate accuracy and resolution. The validation of the entire system was performing on two real-time biomedical applications. The second project concerns the combination of powerful statistical methods inside moisture content sensors. The multivariate statistical approaches boost the prediction capability of the sensors exploiting the impedance mismatch between a transmitting and reflecting excitation on a soil. Two probe systems have been manufactured and associated with linear and non-linear models for being tested on three soil types. The third project shows a low-power implementation of an impedance sensor based on a digital random excitation. The entire system is almost digital, made up by an ultra-low power platform with the aim to become a wearable device. In future developments, these new investigated directions can be simultaneously applied in the design of IS based sensors which extract the desired information with high accuracy and reduced power budget. The potential of such improved system can be employed in a lot of smart sensors, involving electrochemical, environmental, food, biological applications and wearable devices.
Abstract
This thesis provides new directions in the impedance spectroscopy, making it an interesting investigation technique for emerging smart sensors. Modern technologies increasingly require sensors capable of giving accurate measurements extracted among a lot of undesired surrounding information while maintaining low
power consumptions. In this scenario, the main focuses of this thesis are: 1) developing an accurate complex impedance system, 2) extracting the augmented information using multivariate statistical analysis and 3) implementing IS-based systems with low power consumptions. The first project shows the design of a miniaturized, low power and accurate vector analyser for multi-parameter measurements in real-time. It is a versatile platform well-suited to be interfaced with various impedance-based sensors. The vector analyser, based on an accurate application specific integrated circuit and a digital interface, has been statistically characterized in order to evaluate accuracy and resolution. The validation of the entire system was performing on two real-time biomedical applications. The second project concerns the combination of powerful statistical methods inside moisture content sensors. The multivariate statistical approaches boost the prediction capability of the sensors exploiting the impedance mismatch between a transmitting and reflecting excitation on a soil. Two probe systems have been manufactured and associated with linear and non-linear models for being tested on three soil types. The third project shows a low-power implementation of an impedance sensor based on a digital random excitation. The entire system is almost digital, made up by an ultra-low power platform with the aim to become a wearable device. In future developments, these new investigated directions can be simultaneously applied in the design of IS based sensors which extract the desired information with high accuracy and reduced power budget. The potential of such improved system can be employed in a lot of smart sensors, involving electrochemical, environmental, food, biological applications and wearable devices.
Tipologia del documento
Tesi di dottorato
Autore
Luciani, Giulia
Supervisore
Co-supervisore
Dottorato di ricerca
Ciclo
31
Coordinatore
Settore disciplinare
Settore concorsuale
Parole chiave
Impedance Spectroscopy, low power consumption, high accuracy, augmented information
URN:NBN
DOI
10.6092/unibo/amsdottorato/8867
Data di discussione
8 Aprile 2019
URI
Altri metadati
Tipologia del documento
Tesi di dottorato
Autore
Luciani, Giulia
Supervisore
Co-supervisore
Dottorato di ricerca
Ciclo
31
Coordinatore
Settore disciplinare
Settore concorsuale
Parole chiave
Impedance Spectroscopy, low power consumption, high accuracy, augmented information
URN:NBN
DOI
10.6092/unibo/amsdottorato/8867
Data di discussione
8 Aprile 2019
URI
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