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Seismic Sensor Network for High Density Deployments: Concept, Design, Deployment and Results

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Sensor Networks (SENSORNETS 2021, SENSORNETS 2020)


The devastating impact that seismic events can cause to societies demands that the underlying physical processes that cause them are better understood. Seismic networks have been increasingly deployed over the years allowing to measure ground motion with great accuracy and, in a few cases, reaching high-density deployments for high-resolution measurements. In this chapter it is described the work conducted to build a high-density seismic network comprised of low-cost network-enabled accelerometer sensors to monitor the Alentejo region. The design resulted in a modular platform that can operate with different sensors. Following a noise performance evaluation, the Analog ADXL355 accelerometer was selected for the deployment phase. Herein, sensor system measurements were compared with a professional seismometer, using two actual seismic events recorded in Portugal. These events allowed to demonstrate the sensors capabilities in detecting weak (2.5 ML) to moderate (3.4 ML) seismic events at short (8 km) and medium (140 km) distances respectively. Comparing obtained measurements with a professional seismometer, however, the sensor prototypes exhibited, as expected, a higher presence of sensor noise. Overall it is concluded that the sensor system has a potential application in seismology.

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    When the event occurred, Portuguese local time was the same as UTC time.

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    When the event occurred, Portuguese local time was the same as UTC time.


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The SSN-Alentejo project is funded by the Science Foundation of Portugal (FCT) under grant number ALT20-03-0145-FEDER-031260 with the support of the Instituto de Ciências da Terra of the University of Évora (ICTUÉ) under the projects UIDB/04683/2020 and UIDP/04683/2020.

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Correspondence to Marco Manso .

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Manso, M., Bezzeghoud, M., Borges, J., Caldeira, B. (2022). Seismic Sensor Network for High Density Deployments: Concept, Design, Deployment and Results. In: Ahrens, A., Prasad, R.V., Benavente-Peces, C., Ansari, N. (eds) Sensor Networks. SENSORNETS SENSORNETS 2021 2020. Communications in Computer and Information Science, vol 1674. Springer, Cham.

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