IDSL: Enhancing Tsunami Early Warning Systems
by: Alessandrio Annunziato
IDSL System Overview
The IDSL (Internet Data Stream Logger) system is a vital component of Tsunami Early Warning Systems. It operates continuously, ensuring uninterrupted functionality. In case of errors, it can autonomously stop and restart, with data recovery capabilities when the connection is reestablished. Importantly, no data is written to the SD memory card, simplifying maintenance with easy part replacement.
Data Collection Methods
The IDSL system employs two data collection methods:
1. Classical Method: Under this approach, all stations are scanned centrally at regular intervals (e.g., 1 minute). However, the latency is determined by the scanning interval.
2. TAD_server Method: Stations transmit data to the server as soon as it becomes available, ensuring minimal latency. This method also serves as a backup mechanism, offering transmission redundancy. Notably, this method is utilized by various institutions, including IGN/PdE for Spanish stations and ISPRA for ten stations within the Italian Mareographic Network, utilizing the FAST (Fully Automated Sea-level Measurement System) method.
IDSL Power and Battery
The IDSL system's power consumption is meticulously managed. It comprises components such as Teltonika (3.5 W), Raspberry Pi (1 W), and the board (1 W), with a total consumption of 7 W (equivalent to 0.58 A at 12 V). It relies on a combination of internal and external batteries, providing a total capacity of 43.2 Ah, offering approximately 3 days of autonomy. In regions near the 40-degree latitude, solar panels generating 100 W are employed for battery replenishment.
IDSL Control
Remote control of the IDSL system is facilitated via logmein VPN in a remote desktop environment. The traffic consumption for remote control typically ranges between 5 and 8 GB per month.
Tsunami Detection Algorithm
Tsunami detection through sea level measurements is crucial for non-seismic events like volcanic eruptions and landslides. Operational systems have been established at locations such as Stromboli, Italy, and Krakatoa, Indonesia. In some cases, tsunamis can arrive before seismic sources are properly identified.
Various detection methods have been developed, including:
- NOAA DART buoys with low-frequency tide interpolation and alert mechanisms based on signal and tide estimation differences.
- F. Chierici et al.'s method, utilizing harmonics analysis and least square techniques for tide estimation.
- Bressan et al.'s TEDA method, based on instantaneous signal slope and window-based alerting.
- Y. Wang et al.'s adaptive decomposition method, separating tsunami signals from other sources through intrinsic mode functions.
Tsunami Alerting Model
The IDSL system incorporates a Tsunami Detection Model that proves effective in identifying ongoing events, especially non-earthquake-related incidents like volcanic eruptions, such as the Honga Tonga Volcano explosion. This model is adaptable to various devices, as long as online data analysis is conducted.
In conclusion, the IDSL system, with its Tsunami Detection Model, is a valuable asset for Tsunami Early Warning Systems, offering reliability and adaptability across different scenarios and devices. The system's robust design and data collection methods contribute to the timely detection of tsunamis and other critical events.
Data Acquisition for Tsunami Early Warning System
by Dr. Ing. Ardian Ulvan, S.T., M.Sc.
Project: KRAKATAU - Integrated Krakatau Observatory Networks (IKON)
Major Challenges
IKON faces two significant challenges:
1. Infrastructure Limitations: Infrastructure such as electricity and communication access is often unavailable in the Krakatau region.
2. Conservation Area Constraints: Krakatau is a conservation area, which means restricted access and limited activity.
CURRENT WORKS ON PUMMA U-TEWS: TECHNICAL ASPECTS
Data Collection & Information
The primary focus of IKON's efforts lies in data collection and information management. This involves addressing various challenges, including:
- Data Cleaning: Dealing with noise and ensuring data quality.
- Data Processing: Tasks like forecasting, interpolation, extrapolation, and more.
- Funding: Securing financial resources for the project's sustenance.
- Data Interpretation: Identifying and addressing data anomalies.
- Environmental Challenges: Coping with the unique environmental conditions of the area.
Ongoing Initiatives
IKON is actively engaged in several ongoing projects, including:
1. Low-Level Water Pressure Sensor (PUMMA– L U-TEWS): Developing sensors to collect data related to water pressure at low levels.
2. Barometric Pressure Sensor & Tsunami Contactor (PUMMA-P U-TEWS): Designing sensors for measuring barometric pressure and tsunami-related data.
3. Differential Optical Absorption Spectrometry (DOAS): Implementing advanced spectrometry techniques for environmental monitoring.
4. SUK-01: UAV for EWS Krakatau: Utilizing Unmanned Aerial Vehicles (UAVs) for enhancing early warning systems in the Krakatau region.
In conclusion, the IKON project focuses on overcoming infrastructure limitations and conservation area constraints to advance the Tsunami Early Warning System. Their work includes data collection, processing, and interpretation, with ongoing projects that aim to improve data quality and monitoring capabilities in this challenging environment.
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