Research on Emergency Warning System for natural disasters Based on
Multi-Sensor Information Fusion
Jiang Shen, Tong-zheng Zeng, Tao Li, Hong Zhao*
College of Management and Economics, Tianjin University, Tianjin, P. R. China
(*zhaohong0129@163.com)
Abstract - Accordance with these problems of the
frequent natural disasters and the serious losses caused by
natural disasters, the paper constructs a natural disaster
emergency warning model and decision-making support
system based on the research of multi-sensor technology and
information fusion technology, and the functions of modules
and system structures are also analyzed and studied. The
research of this paper provides strong support on technique
and system for the natural disaster decision-making
emergency and warning management.
Keywords - multi-sensor, information fusion, natural
disasters, early warning
I. INTRODUCTION
In recent years, the frequently occurring of natural
disasters highlights the environment vulnerability,
resulting in a lot of property losses and casualties, the
emergency management has been concerned by many
researchers and policy makers. The devastating
9.0-magnitude earthquake in Japan in March 2011 leads
to secondary disasters such as tsunamis, nuclear power
plant leaks, causing serious casualties and economic
losses; in 2010, Zhouqu, Gansu suffered a heavy rainfall
which caused flash flooding and debris flow; in2008,
China suffered snow disaster and Wenchuan earthquake
which demonstrated the inadequacies of integrated
emergency response system for natural disaster in China.
Attentions should be given to the natural disaster
detection and alarm systems after these events.
With the application of multi-sensor information
fusion technology of the emergency warning system for
natural disasters, system information can be mastered
more comprehensively and accurately, natural disasters
can be monitored and pre-warned timely and accurately,
the overall efficiency and effectiveness of existing
emergency response system can be improved, and then
the system is to bring greater social and economic
benefits and better capabilities of the information sharing.
This study can also promote the process of emergency
management research in China, improve the level of
natural disaster management and emergency response
capabilities and provide a scientific basis and technical
support of establishing the daily countermeasures and
contingency plans for the authorities, making mitigation
planning, deploying disaster prevention and relief work
and making city development planning.
II. RESEARCH STATUS AT HOME AND ABROAD
AND TECHNOLOGICAL TRENDS
A． Natural Disaster Research
Natural disasters are the event that the variability of
natural factors exceeds the bear or adaptability of human
society, thus affecting human life, property and the living
security. Essentially, natural disasters are the results that
the earth's natural environment alters role in human
society, including both the role of natural factors and the
role of human society, especially the role of human
society to withstand or adapt to the natural environment
changes, namely, natural disasters have natural and social
attributes[1]. Early researchers mainly associated natural
disasters with hazard factors, they started natural disasters
research with the growth characteristics and the formation
mechanism of natural disasters such as typhoons, storm
surges, heavy rain and floods and so on[2]. In accordance
with the types of natural disasters mentioned by National
Comprehensive Disaster Reduction "Eleventh Five-Year
Plan", natural disasters in China can be divided into 13
kinds: floods, droughts, typhoons, hail, lightning, heat
waves, dust storms, earthquakes, geological disasters,
storm surges, red tides, forest and grassland fires, and
plant diseases and insect pests.
B. The application of information fusion technology
Multi-source
heterogeneous
information’s
multi-dimension, networking, dynamic characteristics
requires information fusion technology to do
multielement normalized fusion. Information fusion
mainly includes two categories: fusion based on
epistemology and fusion based on information theory,
mathematical tools used in this field include probability
theory, reasoning network, fuzzy theory and neural
networks.
In terms of seamless integration of multi-information
and data association, Casasent[3], et al put forward
Probabilistic Data Association (PDA), Bloon[4], et al
proposed Neural Network Data Association (NNDA),
Shalom[4], et al constructed interacting multi-model
associated filter, Bozdag[5], et al put forward Joint
Probabilistic Data Association (JPDA). NNDA, PDA and
JPDA achieve the analysis of targets, sparse targets,
high-density environment. In terms of multi-sensor
information fusion theory, Waltz and Linas made
comprehensive discussion on research, framework and
application of the multi-sensor information fusion, Hall,
et al made research on mathematical techniques in the
multi-sensor data fusion, Bar-Shalom and Fortman[6]
proposed new ideas and methods of multi-sensor data
fusion in target tracking field. In the 1980s, Chinese
scholars began to apply multi-sensor information fusion
technology on national defense, military and other fields,
after 1990s, multi-sensor information fusion technology
began to be used in robotics and industrial process
monitoring system. Information fusion is studied less on
the control problems in the field of complex systems, in
addition to the reason for the complexity of the
multi-element and multi-dimensional information, the
integrated issues on information fusion, learning
mechanism as well as historical data mining are also very
complex.
III. INFORMATION FUSION TECHNIQUE
Multi-sensor information fusion technology is a key
technology of natural disasters monitoring and early
warning in the decision support system, it joins all levels
of various types of sensors located at each monitoring
point into an effective network to achieve interoperability
and comprehensive integration of information, of data
acquisition and real-time monitoring tasks, the
completion of each monitoring point. The role of
multi-sensor information fusion system is the integration
of multi-source information obtained by the various
sensors to obtain more information than a single
intelligence source and a better quality of information and
information credibility, and greatly improve system
access to information, the efficiency of the transfer,
collection, processing, distribution and information
applications [7].
The study selects applicable integration structure to
complete the information fusion. Information fusion
system architecture can be divided into three categories,
namely, data level fusion, feature level fusion and
decision level fusion [8].
Data level. It includes a lot of raw data collected by
the multi-sensor system and the necessary signal
pre-processing and analysis processes, such as signal
noise removal, filtering, cross-correlation analysis,
spectral analysis and so on.
Feature level. It makes effective decision to data
fusion results, it generally corresponds to the diagnostic
methods of the natural disasters.
Decision level. For the initial diagnosis of natural
disasters, it supports decision-making to variety of
countermeasures responding to disasters using decision
fusion algorithms.
On the functional characteristics, this three-layer
structure can respectively meet the requests of monitoring
alarm, disaster diagnosis and disaster countermeasures in
the natural disaster decision support systems.
Combining different sources of information or data
collected by sensors in accordance with established rules
can obtain more comprehensive and reliable awareness
and understanding of the exact state of the object. The
proposed rule methods include Classic reasoning method,
Bayesian, Dempster-Shafer evidence theory, cluster
analysis, expert system reasoning method and so on.
IV. NATURAL DISASTER EMERGENCY WARNING
SYSTEM MODEL BASED ON MULTI-SENSOR
INFORMATION FUSION
A. Information fusion model and method based on
multi-sensor
Because of information heterogeneity, uncertainty,
multi-dimensional features of the complex system, we
need to study the key integration and implementation
issues such as multi-sensor technology, information
fusion, adaptive control and so on; in decision-making
and reasoning core technology, we need to study a variety
of fusion strategies such as CBR (Case-Based Reasoning),
RBR (Rule-Based Reasoning), realizing performance
complement between CBR and RBR. The line of research
preliminarily considered is realizing information
collection, comparison and analysis by multi-sensor
perception and integration, normalizing multi-parameter,
and then on the basis of certain optimization criteria and
the integration algorithm, realizing decision analysis and
collaborative optimization using of CBR/ RBR
integration decision reasoning model by the multi-layer
fusion.
B. Natural disaster emergency warning model based on
multi-sensor information fusion
To obtain information to support the final
decision-making and control the disaster timely and
accurately, natural disasters information is detected by
multi-sensor in this model, then pretreated by filtering
and normalization processing, and finally processed by
multilayer fusion in the multi-layer information fusion
center [9].
filtering
processing
Information
Preprocessing
human-machine
interaction
Information Fusion
Center
adaptive
processing
normalization of
parameters
data association
Level 2:
Information
integration and
optimization
feature extraction
Level 3:
Information
decision-making
and alarming
external data
Information Fusion
Decision Support System
fault
alarming
danger
alarming
information
sharing
Natural Disaster Information Resources Database
Level 1:
information
acquisition and
preprocessing
Multi-sensor Detection
System
manual
intervention
hazard
information
query
disaster
warning
Fig.1 Natural disaster emergency warning model based on multi-sensor information fusion
Level 1: information acquisition and preprocessing.
The data, information and knowledge detected by
multi-sensor form a multi-layer, multi-dimensional,
heterogeneous and complex information space. Noise and
interference signals in the complex information should be
reduced before multi-sensors information processing. The
pretreatment methods include filtering [10] and
normalization. The multi-sensor information is filtrated
by building a filter model, the uncertainty fire information
data parameters and subspace features are normalized, so
that multivariate information can be uniformly recognized
and processed.
Level 2: Information integration and optimization
Though multiple natural disaster risk information has
gone through the first level pretreatment, the essence of
multiple heterogeneous information does not change. In
order to achieve the fusion of these decision making
knowledge which is uncertain, uncontrollable and
heterogeneous in the data structure space, information
fusion technology should be applied to build a
multi-sensor information fusion model. Multi-sensor
information fusion and optimization is done in the fusion
processing center. In this center, multi-source information
is processed in multiple levels according to certain rules
and fusion algorithms. On the one hand, the information
with the same purpose is connected [11], on the other hand,
with the feature extraction of the associated data, a
feature vector is obtained, and all feature vectors are
merged so that we gain a target state or characteristics of
target which are higher level than feature vectors. The
results of the information fusion provide the basis and
data
support
for
natural
disaster
warning
decision-making.
Level 3: Information decision-making and alarming
After multi-layer optimization of disaster information,
the catastrophability still needs to be monitored by a
decision support system to control disaster information,
this level defines threshold of disaster information using
multiple attribute decision making and multiple space
scale analysis method, and then processes the information
in the natural disaster warning system. This model puts
the information processed as input factors of natural
disaster warning decision system to definite threshold
value, and gets system fault alarms, danger level forecast,
and disaster alarming and response plan, etc. the system
outputs information by multimedia hardware and
software, and also provides inquiry through the
man-machine interface.
C.
Decision-making
information fusion
support
system
based
on
Building information fusion decision support system
via information fusion model is based on different
information structure models, constraint rules, probability
functions. The decision support system can be divided
into four parts: information fusion algorithm (core model),
human-machine interaction subsystems (components),
database subsystem (data components), model library
subsystem (model parts) [12].
(1) Information fusion algorithm
Information fusion algorithm is multi-level
progressive structure. It needs to select the appropriate
information fusion algorithm model according to the
information structure in the planning and design of the
actual decision-making support system. Information
fusion structure model generally includes centralized,
hybrid, and feedback.
(2) Human-machine interaction subsystem
Human-machine interaction part is a bridge between
natural disaster decision support system and system users,
it is responsible for passing the decision-making
information which is entered by users to the system for
processing, and also passes the results processed by the
system to users or requires users to enter information in
accordance with system requirements.
(3) Database Subsystem
The database Subsystem mainly plays the role of
storing data, maintaining data and ensuring data security
and effective. The system stores data types include
system user data, user decision-making demanding data,
historical monitoring data, disaster parameter data,
rule-based reasoning data and other data.
(4)Model library and model library management
system
The model library section includes data
pre-processing model, attributes reasoning model, disaster
identification model, disaster early warning model,
decision support program development model and so on.
Model library Management System section is mainly
responsible for creating, modifying and deleting the
models. And also is responsible for defining the new
model and making data exchange the databases.
V. CONCLUSION
Based on the analysis of the seriousness of natural
disasters and the plague mechanism, the paper integrates
hi-tech such as multi-sensor technology, information
fusion technology, adaptive technology and so on, and
builds decision-making model and its supporting system
for natural disaster emergency warning which provide
powerful technology and system support for natural
disasters detecting and warning. The system guarantees to
make more promptly and accurate decisions in the natural
disaster warning system, and it has significant meanings
for improving natural disaster emergency level and
reducing disaster losses.
ACKNOWLEDGMENT
This paper is supported by National Natural Science
Foundation of China (Grant No.71171143), Tianjin
Research Program of Application Foundation and
Advanced Technology (Grant No.10JCYBJC07300), Key
Project of Science and Technology supporting program in
Tianjin (Grant No.09ECKFGX00600), and FOXCONN
Group
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