# Enhancing Sustainable IoT Systems Through a Goal-Oriented Requirements Analysis Framework
###### Abstract  
The rapid expansion of the Internet of Things (IoT) has introduced significant challenges in requirements engineering (RE) due to the complexity of heterogeneous devices and dynamic user needs. Traditional RE methodologies often result in inefficient resource utilization and poor system performance. This research presents the goal-oriented requirements analysis (GORA) methodology, which optimizes requirement specification, resource allocation, and sustainability in IoT development. GORA addresses both functional and non-functional requirements, such as energy efficiency and security, while minimizing computational overhead and reducing resource wastage. The methodology integrates goal-oriented requirements analysis language i* and model-driven development (MDD) through a three-stage transformation process involving the i* RA model, UML class diagrams, and Python source code generation. A case study demonstrates how GORA improves system reliability, performance, and sustainability. Furthermore, an empirical evaluation was conducted in a simulated IoT environment, measuring key metrics such as energy consumption, latency, and code-generation error rate. A comparative analysis with existing RE and MDD approaches is also presented to highlight GORA's advantages in feature coverage, sustainability support, and automation level. This work underscores the need for structured IoT RE frameworks and positions GORA as a foundation for future research in sustainable IoT development. ao 2025 20  
pose significant challenges, particularly in the requirements engineering (RE) phase. The inherent complexity of IoT systems, characterized by heterogeneous devices, real-time constraints, dynamic user needs, and resource limitations, requires a systematic, goal-driven approach to requirements analysis and system design. The rapid evolution of IoT technologies has led to a proliferation of technical solutions, yet user support remains deficient. Unlike traditional software, IoT systems serve a diverse user base with varying needs, necessitating meticulous RE to address both functional (FR) and non-functional requirements (NFRs). RE, a subdiscipline of software engineering (SE), focuses on defining the objectives, functionalities, and constraints of the system [12]. As highlighted in [13], RE involves the analysis, specification, and validation of stakeholder needs to produce a comprehensive requirements document. Effective RE requires collaboration with customers to ensure that the final product satisfies their expectations. However, poor RE implementation often results in systems that do not meet user needs or remain unused. The motivation for this research stems from the increasing demand for sustainable and efficient IoT systems that can operate under resource constraints while maintaining high performance. Traditional SE methodologies are often proven inadequate for the IoT development of IoT due to their inability to capture the intricate interactions between hardware, software, and user expectations [14]. Unlike conventional software systems, IoT solutions interact directly with the physical world through sensors and actuators, necessitating precise definitions of FRs and NFRs, such as energy efficiency, security, latency, and scalability. The absence of a well-defined RE framework tailored for IoT has led to inefficient development processes, excessive resource consumption, and frequent failures to meet end user expectations. Furthermore, existing RE methodologies struggle to address the multidimensional nature of the Internet of Things, resulting in poor requirement definition and high maintenance costs. A critical challenge is the need to reconcile diverse user expectations with system functionality through a goal-driven approach that ensures alignment between stakeholder needs and technical implementation. Furthermore, IoT nodes face inherent resource limitations, including constraints in processing power, memory, and battery life, which traditional SE approaches do not adequately address.