Software-Defined Radar System for Landslides Monitoring

Costanzo, Sandra; Massa, G. Di; Costanzo, Antonio; Borgia, A.; Raffo, Antonio; Viggiani, Giuseppe; Versace, Pasquale

doi:10.1007/978-3-319-31307-8_34

Cited by 14 publications

(11 citation statements)

References 6 publications

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“…LEWIS (Costanzo et al, 2016) uses heterogeneous sensors, distributed in the risk areas, to monitor the several physical quantities related to landslides. The measured data, through a telecommunications network, flow into the data collecting and processing center (DCPC), where, using suitable mathematical models for the monitored site, the risk is evaluated and eventually the state of alert for mitigation action is released (Fig.…”

Section: Early Warning System Architecturementioning

confidence: 99%

“…The resiliency policy involves not only prevention activities but also, and more importantly, those activities needed to maintain functionality after disruption (Snyder and Burns, 2009) and to promptly alert people of incoming catastrophes in order to protect them and prepare for a possible damaging of the endangered CI. Among these activities, the implementation of integrated landslides early warning systems (i.e., LEWIS: Landslides Early Warning Integrated System: An Integrated System for Landslide Monitoring, Early Warning and Risk Mitigation along Life-lines; Versace et al, 2012;Costanzo et al, 2016) reveals its increasing importance.…”

Section: Introductionmentioning

confidence: 99%

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Big data managing in a landslide early warning system: experience from a ground-based interferometric radar application

Intrieri

Bardi

Fanti

et al. 2017

Nat. Hazards Earth Syst. Sci.

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Abstract. A big challenge in terms or landslide risk mitigation is represented by increasing the resiliency of society exposed to the risk. Among the possible strategies with which to reach this goal, there is the implementation of early warning systems. This paper describes a procedure to improve early warning activities in areas affected by high landslide risk, such as those classified as critical infrastructures for their central role in society.This research is part of the project "LEWIS (Landslides Early Warning Integrated System): An Integrated System for Landslide Monitoring, Early Warning and Risk Mitigation along Lifelines".LEWIS is composed of a susceptibility assessment methodology providing information for single points and areal monitoring systems, a data transmission network and a data collecting and processing center (DCPC), where readings from all monitoring systems and mathematical models converge and which sets the basis for warning and intervention activities.The aim of this paper is to show how logistic issues linked to advanced monitoring techniques, such as big data transfer and storing, can be dealt with compatibly with an early warning system. Therefore, we focus on the interaction between an areal monitoring tool (a ground-based interferometric radar) and the DCPC. By converting complex data into ASCII strings and through appropriate data cropping and average, and by implementing an algorithm for line-of-sight correction, we managed to reduce the data daily output without compromising the capability for performing.

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Section: Early Warning System Architecturementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Big data managing in a landslide early warning system: experience from a ground-based interferometric radar application

Intrieri

Bardi

Fanti

et al. 2017

Nat. Hazards Earth Syst. Sci.

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“…In recent years, several VLC prototypes and different modulation techniques have been proposed [5], [6] . In order to reduce hardware costs, an interesting approach is the software defined approach, widely used in other contexts [7], [8]. Since most of signal operations are performed via software (modulation, demodulation, filtering, etc.…”

Section: System Descriptionmentioning

confidence: 99%

A Learning Approach for Robust Carrier Recovery in Heavily Noisy Visible Light Communication

Costanzo

Loscrì

2019

2019 IEEE Wireless Communications and Networking Conference (WCNC)

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Visible Light Communication (VLC) exploits optical frequencies, diffused by usual LED lamps, for adding data communication features to illuminating systems. This paradigm has attracted a growing interest in both scientific and industrial community in the latter decade. Nevertheless, classical wireless communication mechanisms for physical and Medium Access Control (MAC) layers are hardly available for VLC, due to the massive external interference caused by sunlight. A correct signal carrier recover in high noise conditions represent a significant challenge. In this work, it is shown that the synchronization frame length affects the performance of the system in terms of Bit Error Ratio (BER). Since different external conditions require different minimum preamble lengths, we considered an Artificial Intelligence (AI) approach, based on multi-arm bandit formulation, for obtaining a low impact in both BER and goodput of the communication. A low-cost hardware VLC system, implementing a learning algorithm on a Frequency Shift Keying Modulation (FSK), has been designed and tested in different environmental conditions. Experimental results show that a proper choice of preamble length overcomes, in terms of BER and goodput, the classical approach based on fixed preambles.

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“…La tecnología de Radar Definido por Software (SDRadar) posee un hardware dedicado desarrollado en términos de módulos de software que permiten implementar aplicaciones de bajo costo con una flexibilidad y versatilidad fácilmente adaptable a cambios. Varias investigaciones han sido desarrolladas mediante el uso de tecnología SDRadar, con la explotación de todas sus características, debido a que se puede obtener información valiosa para desarrollar aplicaciones relacionadas a necesidades que posee la sociedad tal como analizar niveles de riesgo en zonas de desprendimiento de tierra, también conocidos como deslaves [2]- [4].…”

Section: Introductionunclassified

Sistema de medición del nivel de riesgo de zonas de desprendimiento con tecnología SDRadar en ambientes de laboratorio

Avilés

Veloz

Moreno

et al. 2019

Maskay

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Este trabajo propone un sistema de medición de riesgo en zonas de desprendimiento de tierra con tecnología SDRadar. El prototipo fue desarrollado en un ambiente de laboratorio en la ESPOCH de Ecuador, con la utilización de una USRP B210 que trabaja a 5 GHz, se ha incluido dos amplificadores ZJL6G+ en cascada con 20dB de ganancia total para mejorar la potencia total del sistema. En la etapa de mediciones, se usaron 3 muestras de distinto material con diferentes niveles de humedad para determinar el riesgo en diversas condiciones. Estos materiales fueron macadam, tierra y arena. En dependencia de sus niveles de humedad, los riesgos oscilan entre valores máximos y mínimos, dónde una alta humedad conlleva a un alto riesgo y viceversa. El macadam fue el mejor material para un área de derrumbe debido a que presenta un menor índice de permitividad, esto da como resultado el menor riesgo. Los resultados fueron procesados para obtener los valores de reflexión y permitividad de los materiales y fueron guardados en una base de datos para analizar y determinar los niveles de riesgo, mediante simulaciones de desprendimientos de tierras como función del nivel de humedad.

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Software-Defined Radar System for Landslides Monitoring

Cited by 14 publications

References 6 publications

Big data managing in a landslide early warning system: experience from a ground-based interferometric radar application

Big data managing in a landslide early warning system: experience from a ground-based interferometric radar application

A Learning Approach for Robust Carrier Recovery in Heavily Noisy Visible Light Communication

Sistema de medición del nivel de riesgo de zonas de desprendimiento con tecnología SDRadar en ambientes de laboratorio

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