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  • 05.04. Instrumentation and techniques of general interest  (3)
  • rumore sismico ambientale
  • 2020-2024  (3)
  • 1
    Publication Date: 2023-02-28
    Description: This paper presents the study of NordicWalking providing objective evaluations based on real time acquisition of kinematic parameters during the sport practice. It is possible to carefully monitor the athletic gesture through the integration of conventional poles with inertial sensors, composed of a triaxial accelerometer, a triaxial gyroscope, a pressure sensor positioned on the handle, and a load cell, which constitute aWireless Sensor Networkwhose nodes are appropriately synchronized. The integration of such sensors, whichmust be unobstructive and not change the functionality of the poles, is dictated by the ultimate goal of providing a real time biofeedback in two possible scenarios. The first is intended for Nordic Walking’s instructors, who have the opportunity to verify the proper practice execution by their trainees through the availability of real time objective data, in addition to their personalexperience.The second is devoted to amateur playerswho can practicealone, after the training sessionwith the instructor, and can independently correct any imperfections in real time using a software tool running on their smartphone. Using the Dynamic TimeWarping algorithm, the proposed system identifies themost frequent errors in performing athletic gesture, allowing adjustment in real time of the sporting exercise, through the detection, quantification and correction of errors. The obtained results show that the developed system is able to provide an accurate analysis of the athletic gesture and the proposed algorithm allows a quantitative monitoring of the progress achieved by each subject over time.
    Description: Published
    Description: 2744 - 2757
    Description: 7TM.Sviluppo e Trasferimento Tecnologico
    Description: JCR Journal
    Keywords: Activity monitoring ; data analytics ; Internet Of Things ; smart sport equipments ; wireless sensor network ; 05.04. Instrumentation and techniques of general interest
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: article
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  • 2
    Publication Date: 2024-04-23
    Description: Nel mese di maggio 2022 è iniziato uno sciame sismico, di breve durata, che ha interessato una piccola area del Chianti fiorentino a circa 15 km a sud dalla città di Firenze. I due terremoti più energetici hanno avuto una magnitudo momento pari a 3.7; nonostante la magnitudo modesta, tali eventi sono stati avvertiti distintamente fino a distanze di diverse decine di chilometri, e hanno destato preoccupazione nella popolazione prossima all’area epicentrale. Inoltre, dato l’ingente patrimonio artistico presente nel capoluogo toscano, questo episodio ha sollevato interrogativi sulla sua vulnerabilità anche a scuotimenti del suolo di piccola entità. Al fine di migliorare le conoscenze sulla ubicazione e le dimensioni delle strutture sismogenetiche attive in prossimità di Firenze, l’Istituto Nazionale di Geofisica e Vulcanologia (INGV) è intervenuto nell’area interessata dallo sciame attraverso il Gruppo Operativo (GO) di emergenza SISMIKO. Il 4 maggio, giorno successivo all’inizio dello sciame, cinque stazioni sismiche mobili sono state installate a distanza ravvicinata dall’area epicentrale, e integrate nel sistema di monitoraggio permanente INGV. Questo lavoro descrive le procedure relative a: (i) l’installazione, la manutenzione e la disinstallazione della rete sismica mobile; (ii) la gestione e il controllo di qualità dei dati acquisiti. Infine, vengono presentate, in riferimento al contesto sismotettonico dell’area, le caratteristiche spaziali e l’evoluzione temporale dello sciame, che ha presentato una piccola ripresa nell’attività sismica ad agosto del 2022, con un terremoto di magnitudo locale 2.7 e successive repliche.
    Description: Published
    Description: 1-26
    Description: OST5 Verso un nuovo Monitoraggio
    Description: JCR Journal
    Keywords: Sciame sismico ; Reti sismiche di pronto intervento ; Chianti fiorentino ; Seismic swarm ; Rapid response seismic networks ; 04.06. Seismology ; 05.04. Instrumentation and techniques of general interest
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: article
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  • 3
    Publication Date: 2024-03-13
    Description: This article describes a dataset of acceleration signals acquired from a low-cost Wireless Sensor Network (WSN) during seismic events that occurred in Central Italy. The WSN consists of 5 low-cost sensor nodes, each embedding an ADXL355 tri-axial MEMS accelerometer with a fixed sampling frequency of 250 Hz. The data was acquired from February 2023 to the end of June 2023. During this period, several earthquake sequences affected the area where the sensor network was installed. Continuous data was acquired from the WSN and then trimmed around the origin time of seismic events that occurred near the installation site, close to the city of Pollenza (MC), Italy. A total of 67 events were selected, whose data is available at the Istituto Nazionale di Geofisica e Vulcanologia (INGV) Seismology data center. The traces acquired from the WSN were then manually annotated by analysts from INGV. Annotations include picking time for P and S phases, when distinguishable from the background noise, alongside an associated uncertainty level for the manual annotations. The resulting dataset consists of 328 3 × 25,001 arrays, each associated with its metadata. The metadata includes event data (hypocenter position, origin time, magnitude, magnitude type, etc.), trace-related data (mean, median, maximum, and minimum amplitudes, manual picks, and picks uncertainty), and sensor-specific data (sensor name, sensitivity, and orientation). Furthermore, a small dataset consisting of non-seismic traces is included, with the goal of providing records of noise-only traces, relative to both electronic and environmental/anthropic noise sources. The dataset holds potential for training and developing Machine Learning or signal processing algorithms for seismic data with low signal-to-noise ratios. Additionally, it is valuable for research about earthquakes, structural health monitoring, and MEMS accelerometer performance in civil and seismic engineering applications.
    Description: Published
    Description: 110174
    Description: OST5 Verso un nuovo Monitoraggio
    Description: JCR Journal
    Keywords: Earthquake early warning; Internet of things; MEMS accelerometers; Structural health monitoring; Wireless sensor network ; 05.04. Instrumentation and techniques of general interest ; 05.02. Data dissemination ; 04.06. Seismology
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: article
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