# Enhancing Sustainable IoT Systems Through a Goal-Oriented Requirements Analysis Framework
## 4 Goal-Oriented Requirements Analysis Approach for IoT Software Systems
### Application Example: IoT System for Monitoring Air Quality
#### 4.2.5 QVT for Model-to-Model Transformations
To our knowledge, only one proposal, as presented in [43], has attempted to integrate, focusing primarily on generating a specification document for the requirements, all these RE phases. To further enhance the sustainability of IoT systems, the proposed framework integrates GORA with MDD, providing a structured approach to linking user goals with the corresponding system actions required to achieve them. This is achieved by utilizing (i) task elements from the i* modeling language to analyze the impact of each device action and (ii) goals and sub-goals (quality attributes) to ensure a user-centric orientation in the requirements analysis. As a result, the system dynamically selects and executes device actions based on the current environmental state and the intended goals, enabling context-aware decision making. Designed for non-technical end users, the framework leverages the i* modeling language, which offers straightforward semantics and intuitive reasoning mechanisms, ensuring ease of adoption with a short learning curve. This approach pro \begin{table}
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**Approach** & **Tool Support** & **Sustainability Support** & **Automation Level** & **Code Generation** & **Limitations** \\ ine GORA (proposed) & Edipsse, iY, UML, Accelo & Energy, resource use, productivity & Full (goals \(\rightarrow\) code) & Automated & Scalability for large systems yet to be validated \\ ine SysML + RELAX [24] & SysML Tools & Adaptivity focus only & Manual modeling & No & No automatic transformation or deployment \\ ine FORM-L + Modelica [26] & FORM-L IDE & Verified energy/resource constraints & Partial (semi-automatic) & No & High modeling complexity, steep learning curve \\ ine e-CORE [27] & Custom DSL & Not addressed flow & Full DSL-to-code flow & No & No sustainability layer, limited interoperability \\ ine Domain-specific UML + Profiles [29] & UML Tools & Not addressed template-based & No & No traceability, no energy-awareness \\ \hline \end{tabular}
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Table 2: Comparison of GORA with existing IoT RE and MDD approaches. vides a comprehensive overview of the IoT system while maintaining a strong user focus. End users can define and express their desired states in the smart environment through various interaction modes, including web-based applications, voice commands, or mobile applications, all of which are incorporated into the modeling process. Furthermore, the framework is inherently adaptable, allowing users to customize their goals through the user interface without requiring technical expertise or direct manipulation of the system logic. Performance improvements achieved through the automated implementation based on GORA are directly supported by the structure and behavior of the generated Python code. In terms of energy consumption, the code is designed to be efficient and event-driven, avoiding redundant polling and minimizing CPU and memory activity, which justifies the observed reduction of 18.9%. System latency is improved by embedding MQTT timestamps and cross-referencing them in real time, enabling faster and more accurate actuation decisions, which is reflected in the 23.0% reduction in response time. The modularity and clean structure of the generated code reduce memory usage by 8.6% as they avoid unnecessary variables and libraries. Developer effort, measured in lines of code (LOC), is significantly reduced by 54.4% because the Acceleo transformation automates boilerplate and repetitive logic, resulting in more concise implementations. Finally, the error rate per 10 runs drops from 4 to 0 due to the correctness guarantees imposed by the QVT transformation rules and the template-based code generation, which eliminates the syntax and logic flaws typically introduced in manual development. These metrics collectively validate the effectiveness of the GORA framework in improving both system performance and development efficiency.