# Data Fusion Analysis and Synthesis Framework for Improving Disaster Situation Awareness
## 7 Algorithms for Synthesizing the Optimal Data Fusion Configuration
### Optimal-Fit
In this article, we adopt a heuristic rule based on the following: First, data sources are ranked according to their effectiveness values. Second, the search space is formed by starting from the alternatives with the highest effectiveness values. Gradually, other alternatives are considered according to their ranking order. The process continues until the whole search space is constructed or the cost and/or timing constraints are violated. It is also possible to limit the size of the search space while constructing it. The heuristic rule reduces the state space considerably. This algorithm may not find the optimal fusion if many data sources with fewer effectiveness values give in total a better result than a few but more effective data sources. However, in practice due to physical restrictions, it may be impractical to attach too many data sources at a given geographical area even if their total effectiveness value is high. The adopted heuristic rule is therefore considered preferable for most cases. The algorithms presented in this article adopts a single objective optimization strategy, meaning that the quality attribute effectiveness is the main objective of the search for the optimal solution. The other attributes, cost and timing values, are the restricting constraints. One can also adopt multi-objective-based optimization algorithms, such as Pareto optimization [61], to consider all relevant quality factors. From the perspective of this article, the effectiveness of earthquake damage detection is the main objective and the other two attributes are only taken into account as limiting constraints. ## 10 Future Work

The article presents part of our ongoing activities on disaster management. We are currently extending the proposed approach in various ways. First, we are setting up a laboratory to measure the actual parameters of commercially available data sources. By this way, the data values will be determined more precisely for a given set of products. In our current approach, data fusion is realized at certain predetermined physical locations. This approach will be extended to UAS-based data Fsion. In this way, it will be possible to analyze and synthesize the models with a cooperating swarm of UAVs. Finally, the analysis and synthesis algorithms will be investigated for this dynamically changing topology of data-fusion systems. ## 11 Results and Conclusions

After the occurrence of a disaster such as an earthquake, emergency control centers need to accurately and promptly determine the effect of the disaster so that aid operations can be carried out effectively. To this aim, a data fusion system consisting of multiple data sources must be designed and installed before a disaster occurs. Unfortunately, designing a cost-effective system for this purpose is a challenging task. Firstly, the kinds of possible data sources can be too large. Secondly, each data source may have its relative advantages and shortcomings. Moreover, in case of data fusion, mutual effects of data sources on each other must be considered. Finally, data sources may need to be installed in a large geographical area. We will now elaborate on this article from the perspective of the contributions/novelties by referring to the research questions formulated in Section 3. A novel model-based analysis and synthesis framework is introduced to address the research questions 'What is a suitable architectural style of the desired model-based framework?' and 'How can this architecture be extended to deal with the (future) UAS?'. In Section 8, we have outlined an approach for extending the proposed framework so that it can be utilized in designing UASs. Through an extensive domain analysis work and by organizing the identified domain concepts under a feature diagram, a new domain model is proposed to address the research question 'How to define a domain model of the data sources suitable for detecting the effects of earthquakes?'.