# Development of an Ontology-Based Solution to Reduce the Spread of Viruses
## 4 Analyze and Discussion  
In the healthcare sector, AI approaches have been widely used due to the urgent challenges posed by the spread of viruses, particularly in the area of awareness and precaution [33]. Among the artificial intelligence approaches that have emerged with great effectiveness is an ontology that we have relied on to develop the solution. Table 7 summarizes the scenarios previously described:  
\begin{table}
\begin{tabular}{c c c c} \hline \hline  
Figure 6: Results of the third scenario.  
From the results obtained, the following can be concluded:  
* This solution is a very effective preventive method;
* This solution can help the competent authorities to know the location and extent of the epidemic;
* This solution features the ability to quickly share updated information by encouraging behaviors such as hand washing and social distancing;
* The proposed solution advises people who suffer from these symptoms to seek medical attention and follow the preventive instructions, and thus the individual has an important role in achieving acceptable results, through his cooperation and carefully following the instructions and recommendations, as well as reporting when a viral disease is suspected;
* Unlike other solutions, this solution can identify a diseased condition in the individual, by containing the symptoms that affect the person in the knowledge base of the ontology;
* If a new (unknown) virus appears, there are two possibilities. The first is that it shares some of its symptoms with the viruses defined in the database. In this case, it can be dealt with. In the opposite case, it may pose a danger, but once it is identified, its identifiers can be entered into the database.  
Structurally, we know that the environment for this study (humans and viruses) is a dispersed (the system elements are geographically distributed) [34], dynamic (the system elements are changing), and open (the system interacts with other systems) system [35]. These last characteristics are among the main reasons for choosing the ontology approach. Using this approach, many advantages can be gained compared to the previous solutions, including:  
* When a new virus appears, the knowledge base can be easily updated with information about this virus without a defect in the solution;
* Unused information can be deleted from the knowledge base without going through the steps of developing the solution;
* In this solution, the ontology approach uses medical information from multiple sources that may use different vocabularies. To operate it, an ontology defines common terms in natural language and characterizes them in a computer-understandable logical language (semantic aspect). Thus ontology can support the automatic creation of generic data models that can aggregate data from different sources. This feature is not available in other artificial-intelligence approaches;
* Unlike other artificial-intelligence approaches, works based on this ontology are open to future developments, and their knowledge base can be easily exported and used by other works and researchers.  
Finally, it should be recalled that almost all research questions (hypotheses) related to the development of a smart solution to address and prevent the risk of virus spread have been answered. In addition, comparing it to other works [36; 37; 38; 39], we conclude that this solution has strong additions, whether in response (through results) or adaptation (ontology-based solution) to all developments. Accordingly, many recommendations regarding investment in this solution can be made by researchers specialized in the field of medicine. The establishment of a scientific project at the level of research centers is a qualitative initiative to develop more efficient solutions and thus protect humanity from the threat of viruses. It is also important to generalize these solutions at the global level and provide them to poor countries for free.