**4. Disaster management aspects**

104 Emerging Informatics – Innovative Concepts and Applications

HDSS states the scheme, which has to be developed to cater to the requirements of pre, during and post disaster activities. During the events of the disaster, the approach enables user to send and retrieve information as required through the use of handheld devices such as mobile and PDAs. In addition, users can obtain urgent messages or alerts transmitted on their mobile phones in the

The solution is developed for the prevention and management of floods, which combines telematic technologies with advanced meteorological and hydrological forecasting encapsulated in a

The decision system is designed to assist mainly in the post-and pre disaster situation. As a post-disaster measure it can identify a vulnerable population and assist in the evacuation of the

The DSS approach is described as dynamic integrated model for disaster management decision support. The model is created on the

basis of a given disaster scenario and described the main components of the framework and usefulness of the proposed integrated model. The intelligent technique is used to select the

group of subroutines to create the integrated model.

Gupta (2011) described various stages involved in the preparation of GIS based DSS for disaster management in India. The solution includes the development of an integrated geodatabase that consists of various thematic maps, demographic data, socio-economic data and infrastructural facilities at remote level (Gupta, 2011). Gupta's approach uses a menu driven system that is used by administrators who may not have in-depth knowledge of working in GIS. Adityam and Sarkar (1998) also describe a GIS-based DSS for Indian cities affected by cyclones. However, the approach is focused on disaster preparedness and

The term "cloud computing" has become popular due to its contribution to shared computing applications. Fitzgerald and Dennis (2010) described cloud based design as a "*circuit-switched service architecture*" that is easier to implement for organisations because *"they move the burden of network design and management inside the cloud"* (p. 297). As such, cloud computing provision has been used as a modern architecture of shared computing services. When Amazon.com provided web-based utility services, many service providers

The DSS is developed for disaster communications through decision processes in the phases of preparation, prevention, and

planning of a protection system from natural and other catastrophes, as well as interventions during an emergency situation. The model captures the necessary location-specific data.

*support solutions Descriptions* 

form of SMS.

decision support system.

population at risk.

planning through the use of GIS technologies.

Table 1. Different purpose and technologies used for disaster management DSS

*Purpose of decision* 

Assilzadeha and Mansora (2011) Hazard Decision Support System

TELEFLEUR (Cioca and Cioca, 2010) TELEmatics-assisted handling of FLood Emergencies

GIS Based DSS (Buzolic, Mladineo &

Knezic, 2009)

Integrated DSS (Asghar, Alahakoon and Churilov, 2006)

development

2009)

Post and pre disaster DSS (Mirfenderesk,

(HDSS)

In disaster situations involves a number of entities such as disaster management authorities, teams and individuals from more than one location that are geographically distributed. The entities can be for example medical teams, rescue services, police, civil protection, fire, health and safety professionals, and ambulance services that will be required to communicate, cooperate and collaborate – in real time – in order to take appropriate decisions and actions (Bessin et al. 2011, Graves, 2004; Often et al., 2004). This implies that decision making for such combined action taking is rather multifarious due to diverse information processing from different sources. Carle et al. (2004) suggest that *"there are frequent quotes regarding the lack and inconsistent views of information shared in emergency operations"* (Bessin et al. 2011 p. 77). Carle et al. (2004) also reported that information exchange during an emergency situation is very important and can be very diverse and complex and at analysing information is very important, yet none of the current technologies support such needs.

Disaster managers play important roles in disaster situations. Asimakopoulou and Bessis (2010) and Bessis et al. (2010) note that disaster managers are required to identify the site of people and evaluate their present and projected impacts, because there is no real benefit in sending rescue team to a place if there is no one actually present. This implies that disaster managers need analysed information to make such a quick decision in an appropriate way. Because, it is important to urgently send the rescue team to a place where there is a great risk of someone or many injured. It is straightforward to construct many plausible scenarios where knowledge can be collected from various emerging technologies to the benefit of the disaster managers and the society. In other words, access to shared information regarding the number, whereabouts and health of people in an area struck by a disaster will significantly enhance the ability of disaster managers to respond timely to the reality of the situation. The aforementioned challenges are so vast and multifaceted that it is clearly insufficient to address all of them here.

A framework for analysing disaster management activities is outlined by Wallace & De Balogh, (1985). The proposed framework uses pre and post event based activities for identifying scope of DSS development. The approach can be useful to guide the implementation of DSS technologies for specific purpose.

As mentioned previously, a service oriented architecture based solution in the public security sector called SoKNOS (SoKNOS, 2011) has been developed, in which different technological and user oriented objectives will be investigated such as machine-readable semantics, user-friendly workplace, highly-reliable system behavior and integral data processing. Another objective is machine readable semantics to provide relevant services to user contexts using appropriate machine readable coding in developed technology. Further objective is the user-friendly workplace, which concerns fulfilling decision makers' desires through technological features. This aspect relates to how the technology will accommodate current user's problem scenario and information flow appropriate to particular situation. To

An Emerging Decision Support Systems Technology for Disastrous Actions Management 107

Recent research in business intelligence (BI) suggest that the approach can be supportive for any decision support solutions including its underlying architectures, tools, databases, applications, and methodologies (Raisinghani 2004). Negash (2004) provides a definition of

*"combine data gathering, data storage, and knowledge management with analytical tools to present* 

Turban et al. (2008) describes BI's main purposes as enabling interactive and easy access to data, its manipulation and transformation to provide business managers the required decision support. This implies that the approach can add value to decision makers in a disaster management situation where they need to process and transform diverse data. As such, the BI approach is now widely adopted in the world of application design for decision making aid (Watson and Wixom 2007). Drawing from this, this study outlines a BI based conceptual solution in which diverse data are retrieved and manipulated through an analytics filter at the initial stage. Figure 1 illustrates the proposed solution model. The first layer ranges from data sources to knowledge repository; the second from knowledge repository to data fostering; and the third extends from data fostering unit to user group access. At the first layer, the aim is to create meaningful data for storing in the knowledge

*complex internal and competitive information to planners and decision makers"* 

Fig. 1. Conceptual solution model of the proposed decision support systems

After storing the data in the knowledge repository, using an ontology model defined in protégé II (Gennari et al. 2003), the data fostering unit (second layer) use BI rules which will be generated from contextual knowledge to transform the meaningful information to different decision makers at the third layer. It is suggested that BI heavily relies on advanced data collection, extraction, and analysis technologies (Watson and Wixom 2007). In the proposed process, business analytics ensures advanced data collections from a range of data sources with context specific detail knowledge. To extract the data, BI rules ensure appropriate contextual information generation of the stored data to improve decision making. In the data fostering unit, (third layer) the user group can select options relevant to their context, for example by defining parameters for the BI rules. During the events of the disaster, the user is able to send and retrieve information through the use of handheld

**5. Proposed DSS framework** 

BI as follows:

repository.


Table 2. Activities under disaster management scenario (adapted from Wallace & De Balogh, 1985)

achieve the objective of developing reliable system behaviour, the technology should demonstrate robust behaviour that helps achieve reliability through its innovative mechanisms. The integral data processing requires the technical development that combines internal and external data readable to decision makers. These objectives are useful in motivating further technology development for disaster management; however, this project is still in its conceptual stage. From this perspective this study adopts the principle "*technology should demonstrate robust behaviour that helps achieve reliability*" to outline a business intelligence technique based DSS model in this chapter that guides a conceptual solution design.
