This document presents an underwater acoustic sensor network for early warning generation of tsunamis. It discusses flaws in existing tsunami early warning systems, and proposes an integrated system using underwater sensor networks, satellites, and terrestrial communication networks. Key challenges addressed include power optimization, modulation schemes, and routing for underwater acoustic networks. Performance is measured by reliability and timeliness of warnings. Further improvements could include better simulations, decision support, and tsunami modeling.

1. UNDERWATER ACOUSTIC SENSOR
NETWORK
FOR EARLY WARNING GENERATION
by
Srija
Physics and Mathematics Dept.
Whitman College, WA, USA
srijas@whitman.edu.in
Co-authors:
 Prashant Kumar and Preetam Kumar, Electrical Engg. Dept.
Indian Institute of Technology Patna, India
 Poonam Priyadarshini, Electronics and Comm. Engg. Dept.
Birla Institute of Technology Patna, India
IEEE/MTS OCEANS’12 Hampton Roads, Virginia Oct. 14-19

2. BRIEF OUTLINE
 Problem Statement
 Flaw in Existing Systems
 Our Contribution
 Challenges in Implementation
 Performance Metrics
 Scope of further improvement
 Conclusion
 References

3. PROBLEM STATEMENT
 Tsunami is actually a series of ocean waves produced by earthquakes
or underwater landslides that can travel at speeds averaging 450 miles
per hour in the open ocean.
 A tsunami warning system (TWS) is used to detect tsunamis in
advance and issue warnings to prevent loss of life and damage.
 The evolution of TWS shows a significant development from seismic-
centered to multi-sensor system architectures.
 Two equally important components: a network of sensors to detect
tsunamis and a communications infrastructure to issue timely alarms
to permit evacuation of coastal areas.
 This presentation highlights the physical layer challenges in
establishing a reliable, low power consuming and long life
underwater wireless sensor network (UWSN) system for such
early warning generation.

4. EXISTING SYSTEMS
 A sensor network capable of detecting an oceanic earthquake and an impending
tsunami is feasible, but will be useless unless backed by improved
communications infrastructure in the countries in greatest peril.
 The devastating death toll and damage caused by the tsunami in 2004 has
prompted urgent calls for an early warning system.
 European Union funded project Distant Early Warning System (DEWS) has aims
at developing an advanced interoperable Tsunami early warning system for
strong early warning capacities for Indonesia.
 The project detects and analyzes seismic events in the Indian Ocean, the rapid
assessment of their potential to unleash a Tsunami, and warning at-risk
countries by means of a network of detectors made up of broadband
seismometers, land and ocean-surface based GPS instruments, tide gauges, and
ocean bottom pressure control devices. Using satellites, the data obtained by
these instruments is sent to a central station in Jakarta, Indonesia for
processing.

5. INCOIS
Tsunami Early Warning Centre is a part of Indian Nation Centre For Ocean
Information Services (INCOIS). It has a warehouse of ocean related
information gathered from institutions in India involved in Marine Data, Ocean
Observation and Atmospheric sciences.
 INCOIS translate it into deliverable products to a range of users - Fishing
community, State Fishery Department Officers, Planning Commission,
Shipping Industry, Navy, Coast Guards, Pollution Control Board, etc for timely
dissemination of advisories following a standard operating procedure.
 Seismic and sea-level data are continuously monitored in the warning centre
using a custom-built DSS software application that generates alarms/alerts in
the warning centre whenever a preset threshold is crossed. The software
solution built entirely using GIS techniques enables operations (i) display of
locations of seismic sensors, tide gauges, bottom pressure sensors, (ii) retrieve
real-time data, (iii) online plotting, (iv) overlay tsunami travel times by picking
up the right scenario from the database, (v) warning generation and
dissemination, (vi) system monitoring, administration, back up, data retrieval
and play back.

6. INCOIS

7. DART
 An early warning system for tsunamis is already in operation in the
Pacific Ocean and consists of a network of seismograph and tidal
gauges linked via satellite to monitoring centers based in Alaska, US,
and Hawaii.
 Deep Ocean Assessment and Reporting sensors use deep-sea pressure
detectors that measure changes in water depth as a tsunami wave
passes overhead.
 The sensors then transfer the information to a surface buoy, which
relays it to the monitoring stations by satellite.
 The DART system prevented a false alarm on Hawaii just a month after
its activation, following a tremor in Alaska.
 DART is also less vulnerable to earthquake damage than tide gauges but
experts insist that multiple detection systems are essential.

8. DART

9. GITEWS
 GITEWS-developed, GPS based component offers possibility for
detection of co-seismic land mass movements and tsunami
waves on the ocean, it covers station design, data transfer, near
real time data processing and warning center operator desk.
This German Indonesian project was started in 2004.
 The project detects and analyzes seismic events in the Indian
Ocean, the rapid assessment of their potential to unleash a
Tsunami, and warning at-risk countries by means of a network
of detectors made up of broadband seismometers, land and
ocean-surface based GPS instruments, tide gauges, and ocean
bottom pressure control devices.
 Using satellites, the data obtained by these instruments is sent
to a central station in Jakarta, Indonesia for processing.

10. GITEWS

11. FLAW IN THE EXISTING SYSTEMS
 90 % a tsunami is generated by an earthquake but also volcanic eruptions
and landslides may be the triggering events.
 The early warning part of Tsunami hazard management till date relies upon the
measurements of sea level and computer models to characterize the
Tsunami waves.
 Scientists rely on ocean based buoys and models to track and predict the path
of a Tsunami.
 Geospatial technology has immensely helped in the design of early warning
system for tsunami.
 Use of model simulations as well as water level data from tide gauges for
generation of tsunami bulletins has definite advantage in bringing down the
number of false alarms.
 The observation need to be made at the site and not at the sea level.

12. OUR CONTRIBUTION
 Sensor networks that measure seismic activity from remote
locations can provide Tsunami warnings to coastal areas, or
study the effects of submarine earthquakes (seaquakes).
 Underwater sensor networks have the potential to pave the
way for unexplored applications and to help observe and
predict the ocean.
 We combine the underwater acoustic sensor network with
satellite and terrestrial communication systems together
with the internet to generate early warning.
 This type of UWSN technology integrated with the internet
technology would make the data and warning accessible to
one and all.

13. UNDERWATER SENSOR NETWORK

14. UWSN BASED EARLY WARNING SYSTEM
 The present design considers a method of exploiting underwater acoustic
sensor network with nodes spread over the entire ocean bed under
coverage.
 It has space-based monitoring with satellite technology in addition to other
terrestrial communication technologies. There are three levels in the design.
 The 1st level deals with communication inside the harsh underwater
environment where only acoustic communication is possible. The sensor
nodes are organized in clusters and these nodes communicate over short
distances while the cluster heads convey the data collected to the surface
stations closest to them.
 In the 2nd level the surface station collects the information and forwards it to
the coastal data collection centre through line of sight (LOS) microwave
terrestrial transmission; there may be a master surface station which is more
capable in terms of power and communication.
 In the 3rd level the information is either directly sent to a universal data
collection centre through satellite by the surface station or the coastal data

15. UWSN BASED EARLY WARNING SYSTEM

16.  Power and energy optimizations are especially critical for UWANs
because:
1) acoustic communications will consume more energy than RF
channels, and
2) energy harvesting is much more difficult because major
harvesting sources such as solar and wind energy are not
available in the underwater environment.
 Since UWANs are battery operated, lowering the transmission power
may extend network life time but at the cost of increased bit error rate
(BER), as signal to noise ratio (SNR) might not be high enough to
ensure satisfactory information transmission.
 Motivated by these constrains UWANs design require low power
consuming, good BER system with least complexity.
CHALLENGES IN IMPLEMENTATION

17. CHALLENGES IN IMPLEMENTATION
 Doppler Spread-depends on the ocean environment (chemical-physical
properties of the water medium such as temperature) under consideration and
varies from ocean to ocean.
 These variations, together with the wave guide nature of the channel cause the
acoustic channel to be temporally and spatially variable.
 Routing Techniques-A common practice used in terrestrial sensor network
applications is to design routing algorithms that minimize the
communication power and consequently increase the sensor lifetime.
This requirement needs to be ported to underwater as well as space
applications.
 Modulation Schemes-Among the important design parameter are bit error
rate, peak to average power ratio, number of subcarriers, signal
bandwidth, block duration, guard interval, subcarrier spacing, pilot
carriers and null subcarriers.

18. PERFORMANCE METRICS
 The system will be judged by the reliability (correct and prompt warning) so
that public can be targeted warned and evacuation measures can be initiated.
State of art Ocean Instrumentation
 Instruments are installed on the coast, in the ocean or on the ocean floor
measuring the sea level fluctuations both on the ocean as well as on the coasts
 Analysis of different measurements at a very early stage with the help of
seismometers, GPS instruments, tide gauges and buoys as well as ocean
bottom pressure sensors. The recording and analysis of bathymetric data for
determining the topography of the ocean floor is an essential basis for
modeling.
Warning Centre
 Here the data of the particular sensor systems are received and analyzed.
 By means of a Decision Support System and based on simulations and pre-
tailored hazard and risk maps the information is to be delivered to
governmental institutions, local disaster management, action forces and media.

19. SCOPE OF FURTHER IMPROVEMENT
Better Simulations:
 As the WSN supplies data at few points only, computer simulations are needed,
in order to synthesize an overall picture of the situation. Taking help of model
for the ascertainment of arrival times and wave heights as well as information
on the inhabitants and infrastructure, fast risk estimations can be reached.
Better Warning Centre and Decision-making Support:
 A better Decision Support System (DSS) is always required.
Rigorous Tsunami Modeling: Modeling of Tsunami can be divided into three
stages: Generation, Propagation and Run-up (inundation).
 The use of numerical modeling to determine the potential run-ups and
inundation from a local or distant Tsunami is recognized as useful and
important tool, since data from past Tsunamis are usually insufficient to plan
future disaster mitigation and management plans. Models can be initialized
with potential worst case scenarios for the Tsunami sources or for the waves
just offshore to determine corresponding impact on near by coast.

20. CONCLUSION
 The development of the early warning generation system based on UWANs will
undoubtedly contribute to save a lot of human lives facing natural disasters.
 It can be concluded that reliable communication, low-power design and
efficient resource management will remain the major challenges for UWSN
based early warning generation system designs.
 Sensor webs for early warning will prove to be a powerful technology for
environmental and ecological research in addition to saving human life.
 However in deploying such a system it should be taken care that the aquatic
ecological balance is not disturbed.
 Education is another key element in the tsunami warning system. Coastal areas
must have designated tsunami inundation zones and marked evacuation routes
to assist residents and visitors to higher ground. Emergency management
officials should distribute tsunami education information, conduct
community meetings and workshops, and many more awareness
activities.

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22. Thank you!