# Enhancing Sustainable IoT Systems Through a Goal-Oriented Requirements Analysis Framework
###### Abstract
Lastly, the environmental impact of IoT systems highlights the need to embed sustainability-focused design principles to promote long-term viability and resource-efficient development. Addressing these challenges requires a structured and comprehensive RE framework that optimizes requirements specifications while ensuring the implementation of an efficient and sustainable IoT system. This research presents a systematic approach to requirements analysis in IoT software systems, addressing key challenges in RE. The proposed methodology aims to bridge three fundamental gaps in current IoT development practices: (1) the lack of comprehensive requirements analysis methodologies tailored for IoT environments, (2) insufficient tool support for requirement definition, and (3) the absence of a unified framework that integrates both hardware and software components. By addressing these gaps, this study contributes to the development of sustainable, efficient, and systematic IoT solutions that incorporate both technical and environmental considerations. Moreover, the proposed approach integrates sustainability concerns, such as energy efficiency and computational optimization, throughout the development lifecycle, from requirement specification to system implementation. This ensures that IoT systems are not only optimally designed, but also aligned with long-term sustainability objectives. The need for this research is reinforced by well-documented correlations between rigorous RE practices and the successful deployment of IoT systems. Empirical evidence in the software engineering literature consistently demonstrates that inadequate RE practices contribute to project failures, particularly in complex distributed environments, such as IoT [15]. The consequences of poor requirements specification include (i) excessive rework cycles during development, (ii) inefficient resource allocation, and (iii) systems that ultimately fail to meet stakeholder needs, which is an especially critical issue given the IoT's direct interaction with the physical world. The proposed goal-oriented requirements analysis (GORA) is a structured, sustainability-driven methodology that is tailored for the development of IoT software. GORA provides a systematic approach to identifying, analyzing, and managing IoT-specific requirements, with a focus on optimizing resource use and minimizing development waste. By incorporating goal decomposition, requirement traceability, and sustainability constraints, GORA facilitates the design of energy-efficient, computationally optimized, and adaptable IoT systems, contributing to the overall sustainability of the solution. The proposed methodology for developing sustainable IoT systems integrates goal-oriented requirements engineering (GORE) and model-driven development (MDD) through a three-stage transformation process. The first stage involves defining the i* requirement analysis (RA) model, capturing the objectives and dependencies of the system. In the second stage, model-to-model (M2M) transformation rules are applied using Query/View/Transformation (QVT) to convert the i* RA model into a UML class diagram, ensuring a structured and well-defined representation of system components. Finally, in the third stage, a model-to-text (M2T) transformation is executed using Acceleo to generate Python source code from the UML class diagram, which streamlines the implementation of the IoT system. To ground this work in a real-world context, consider a homeowner aiming to improve indoor air quality using an IoT system. The system must collect data from multiple air quality sensors, visualize readings, and trigger actions, such as enabling air purifiers. This scenario exemplifies the complex interplay between stakeholder goals, system requirements, and sustainability constraints, which is introduced in detail in Section 4.2. This user journey encapsulates the typical input (goal definitions, environmental context, etc.)