# Data Fusion Analysis and Synthesis Framework for Improving Disaster Situation Awareness
## 7 Algorithms for Synthesizing the Optimal Data Fusion Configuration
### Optimal-Fit
: _Consider the following data sources where the optimal data fusion option must be determined:_

* _The cost limit is 15_ \(K\) _in unit of currency._
* _The time limit is 3.6_ \(K\) _in seconds._

The effectiveness values of the available data sources are estimated as follows:

1. GPS trackers (\(e=0.433\));
2. Mobile phone apps (\(e=0.433\));
3. Base station (\(e=0.367\));
4. Registration database (\(e=0.333\));
5. UAV-camera (\(e=0.233\)). In this example, we only consider the effectiveness values. In the first iteration step, the data sources with highest effectiveness values are (GPS trackers, mobile phone apps, and base stations). In the second iteration, the best three data sources must be found for each data source that has been selected in the previous step. The result of the second iteration is given below:

* GPS Trackers \(\rightarrow\) Mobile Phones, Base Stations, Registration Database;
* Mobile Phone apps \(\rightarrow\) GPS Trackers, Base Stations, Registration Database;
* Base Stations \(\rightarrow\) GPS Trackers, Mobile Phones, Registration Database. Here, the sign \(\rightarrow\) denotes to appended sub-nodes. Assume that the algorithm is now terminated. The final step is to determine the best path from the nine paths. There are two paths with the same value: (\(e=0.679\)). The data sources in each path are: {GPS Trackers, Mobile Phone apps} and {Mobile Phone apps, GPS Trackers}. ## 8 Generalization of the Analysis and Synthesis Approach to UAS-Based Data Fusion

In Section 2.4, it was stated that the concept of AAM and its implementation as UAS can bring new opportunities for improving situation awareness in disaster/earthquake management. A UAV, together with many other system components such as ground-based stations and data sources of many kinds, provides much better coverage. They can form all together so-called systems of systems, in which swarm of UAVs or even swarm UASs can dynamically exchange data and information, and cooperate with each other for a common set of goals. In addition to generic ones, UASs can also be designed for specific missions such as disaster management. They may also share the heavy load such as radars and precision optical devices. Such a geography-based system consisting of static and dynamic parts can offer effective decision making. In addition, life data can be provided to emergency control centers. UASs, in short, offer the perspective of creating a more dynamic and self-adapting and responsive system architecture for the purpose of dealing with the unforeseen disaster conditions. In the following, we therefore elaborate on the possibilities of extending our analysis and design framework for supporting UASs. AAM-based data fusion systems can be introduced to the analysis and synthesis framework in the following way:

1. UAV must be introduced as an element of a geographical model. If necessary, a new class must be introduced in CityGML. 2. A set of queries must be defined for UAVs so that data sources can be attached for fusion. In this case, an instance of a UAV can function as a data source and and as a fusion node (element of a geographical area). 3. In addition to cost and timing values, a new quality attribute _weight_ must be introduced. 4. The analysis and synthesis algorithms must take care of this new attribute as well. 5. UAVs may cooperate together during their mission by sharing some of their tasks. 6. To analyse and synthesize models with cooperating UAVss, the computation of the efficiency values must take care of a group of elements. In addition, time-dependent properties of UAVs must be taken into account. The analysis and synthesis algorithms must be defined accordingly, possibly by using network-based evaluation models. The steps described in this section illustrate how the framework can be adapted to cope with substantial change demands. These are our future plans for research.