Edge AI Systems Verification and Validation

The integration of edge artificial intelligence (AI) into different complex systems presents unique challenges, particularly concerning their reliability, robustness, safety, and transparency. Edge AI systems must function as intended and meet regulatory and technical standards. Traditional verification and validation (V&V) methodologies, which are well-suited for conventional software (SW) and hardware (HW) systems, do not fully address the unique characteristics of edge AI-based systems that include hardware, software, elements of the edge AI technology stack and data.

The chapter delves into the challenges and methodologies for edge AI verification and validation to identify the unique elements required to develop verifiable edge AI systems based on a structured verification and validation framework integrated with model- and data-driven engineering principles, assurance cases, and domain-specific requirements. It highlights the terminology and concepts for edge AI as a technology that integrates HW, SW, and edge AI technology and data while presenting the challenges of the convergence of these technologies in developing verification and validation solutions.