Smart Sensors, Internet of Things, Machine Learning: Coalition Forces on Seismic Monitoring
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Intelligent Sensors".
Deadline for manuscript submissions: 10 March 2025 | Viewed by 180
Special Issue Editor
Interests: physics of the earth’s interior; electromagnetic methods in geophysics; seismic electric, magnetic and electromagnetic phenomena; earthquake prediction research; sensors and transducers; measuring and data acquisition systems; measurements, telemetry and instrumentation; micro-controllers and computer technologies for measurements
Special Issue Information
Dear Colleagues,
Seismic monitoring is the cardinal and indispensable measurement data supplier to seismology. Providing the most complete and accurate earthquake information, multi-sensor, seismic networks contribute essentially to breakthroughs in studying Earth's interior and in understanding earthquake mechanisms and dynamics, tectonics, seismic hazards, volcanology and in many other disciplines of geophysics and recently planetary physics as well.
Permanent global and regional seismic networks, the backbone of passive seismology, reinvigorated by employing diverse high-end sensors, broadband, with high-resolution and dynamic amplitude, yet expensive. Challenges remain concerning covered Earth’s surface (unbalanced deployments on land and ocean-bottom) and interstation spacing (sparse coverage), as well to monitor rotational seismic motions.
Nevertheless, the first quarter of the current century, a new trend of real-time seismic monitoring emerges benefited by next-generation intelligent systems such as large nodal arrays, and revolutionary sensing methods, e.g., fiber-optics, distributed acoustic sensing (DAS). These daring innovations, nowadays applicable to temporary, local/urban deployments, are directed towards ultra-dense seismic networks featuring low-cost, low-power integrated sensors, at the loss of data-quality, the expense of enormous storage capacity, the demand for big-data processing and novel earthquake detection and seismic inversion methods. To this end, data mining, machine learning methods and neural networks applications are overwhelmingly involved to the software part of seismic monitoring, of course being compelled to and taking advantage of computational power and resources.
Based on and the technological achievements of the recent decades, including Internet of Things (IoT) and micro-electromechanical systems (MEMS), urban seismic networks and earthquake early warning systems (EEWS) are acquiring the pace to be a mature branch of seismic monitoring that will provide a practical tool to mitigate earthquake risk. Seismic monitoring is becoming hybrid encompassing early warning. Earthquake prediction research, the other major echelon for the fight against earthquake disasters, apart its unquestionable importance and unprecedented growth, needs to strengthen earthquake prediction technology and models for the identification and interpretation of earthquake precursory phenomena.
This special issue aims to enrich scientific literature with a bright collection of state-of-the-art reviews, pioneering examples, innovative approaches and case studies with topics that are affiliated to the above thematics, presenting prominent advances, discussing bottlenecks and challenges, highlighting current trends and future perspectives on seismic monitoring (hardware and software).
Dr. John P. Makris
Guest Editor
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Keywords
- seismic motions
- seismic monitoring
- seismic networks
- nodal arrays
- fiber-optic sensing
- smart sensors
- intelligent systems
- internet of things
- machine learning
- neural networks
- data processing
- earthquake analysis
- earthquake catalogs
- early warning
- earthquake precursors
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