# System Architecture Design of IoT-Based Smart Cities
## 4 Domain Analysis  
The first step of our research method involves domain analysis of IoT-based smart city engineering. Domain analysis is generally defined as an approach to understanding the problem space and context of a particular field or industry. It involves gathering and analyzing information about user needs, business processes, and technical constraints in a specific domain to help inform the design and development of software solutions. In essence, it consists of domain scoping and domain modeling.  
Domain scoping is the first step of domain analysis and involves defining the boundaries of the problem space and identifying what specific aspects of the domain are relevant to the software development project at hand. It is used to determine the scope and goals of the domain analysis and to ensure that the investigation is focused on the domain's most important and relevant aspects. The scope of our research is the domain of smart cities developed using IoT. As such, both domains and, in particular, the combination of both domains is explored.  
Domain modeling is the next step of domain analysis and involves creating conceptual representations of real-world entities, processes, and relationships within the defined scope of the problem space. It is used to gain a deeper understanding of the domain and to identify potential solutions for the system development project. Feature modeling is a technique used as part of domain modeling in software engineering to represent a software system's product requirements and variability. It is a graphical representation that captures the common and variant features and the relationships between features. Feature modeling plays a crucial role in capturing the product requirements and variability of the system. In feature modeling, features are defined as distinct and recognizable characteristics or capabilities of a system. They can be used to represent functional and non-functional requirements, as well as the variability of the system. The adopted relations in feature modeling define the relationships between features, such as mandatory, optional, and alternative relationships. The following are the most common relations:  
* Mandatory: A feature must be included in the final product;
* Optional: A feature may be included in the final product, but it is not required;
* Alternative: Only one of the features in this group can be included in the final product;
* Or: At least one feature in this group must be included in the final product;
* Exclusive Or: Only one of the features in this group can be included in the final product, but the others are not allowed.  
By using these relations, feature modeling can capture the hierarchical structure of features and the interdependencies between features, which can help ensure that the final solution meets stakeholders' requirements and is flexible and scalable. The resulting feature model for IoT-based smart city systems is shown in Figure 3. A detailed explanation of the specific features and the interconnection is provided in our earlier work [16; 17].  
Figure 3: Feature Model for IoT-based Smart Cities.