## 2 Background
### ISO/IEC 25010:2011 Standard  
ISO/IEC 25010:2011 [23], part of the \"Software Engineering--Software Product Quality Requirements and Evaluation (SQUARE)\" series, is a comprehensive standard designed to specify and evaluate software product quality. It provides a structured framework for assessing software quality across diverse domains, covering essential quality dimensions such as performance, reliability, and security. This holistic approach enables consistent evaluations, clear justifications for decisions, and informed decision-making. The principles and quality characteristics outlined in ISO/IEC 25010:2011 can be effectively applied to evaluate both edge hardware products and AI models for edge applications. In this study, this standard is used in the methodology provided in Section 4 to evaluate edge hardware and AI model candidates. The use of ISO/IEC 25010:2011 for this study is motivated by both technical and business considerations. From a technical perspective, the standard offers a comprehensive set of quality characteristics that are highly relevant to Edge AI applications. Moreover, since ISO 25010 provides a well-established framework for quality assessment, some studies in the literature have also utilized it for the quality assessment of edge systems [34; 35; 36]: For instance, [PERSON] et al. [34] referenced ISO/IEC 25010 for mobile edge computing. [PERSON] et al. [35] focused on IoT systems layers and investigated quality dimensions, utilizing ISO 25010 characteristics. As shown in Figure 1, the ISO/IEC 25010 standard identifies 8 key quality characteristics and 31 sub-characteristics. The definitions and the relevance of each characteristic for evaluating edge hardware and AI models follow [37]:  
* Functional Suitability: The standard defines it as the \"degree to which a product or system provides functions that meet stated and implied needs when used under specified conditions\". This characteristic ensures that the edge applications perform their intended functions within the constrained environments of edge computing, such as limited processing power, memory, and energy resources. * Reliability: The standard defines it as the \"degree to which a system, product or component performs specified functions under specified conditions for a specified period\". It is a critical factor for edge systems, as they often operate in real-time and in dynamic environments, such as vehicles, drones, or remote monitoring systems. These systems are expected to function consistently under specified conditions over an extended period without failure. * Usability: The standard defines it as the \"degree to which a product or system can be used by specified users to achieve specified goals with effectiveness, efficiency, and satisfaction in a specified context of use\". The usability characteristic ensures that the system can be effectively and efficiently used by the intended stakeholders. For example, for end-users, systems like smart home devices should be intuitive, responsive, and easy to interact with. Performance Efficiency: The standard defines it as the \"degree of the performance relative to the number of resources used under stated conditions\". Performance efficiency is one of the most critical characteristics for Edge AI applications. Edge devices often have limited resources in terms of processing power, memory, and battery life. Ensuring that the system delivers expected performance under these limited resources is essential for effective deployment in edge environments. * Portability: The standard defines it as the \"degree of effectiveness and efficiency with which a system, product or component can be transferred from one hardware, software or other operational or usage environment to another\". This characteristic ensures that AI models and hardware can be easily deployed across various devices, allowing for flexible and scalable Edge AI solutions.