Por Lip Yee – författare

This book is a compilation of high-quality scientific papers presented at International Conference on Artificial Intelligence, Electronic Instruments and Information Systems (AIEIIS 2025). This book addresses the integration challenge: AI is rapidly evolving, but practical deployment requires seamless interaction with physical devices, embedded systems, and secure information infrastructures. This book emphasizes end to end solutions, showing how advanced algorithms can be embedded into real world sensing, measurement, and control platforms. Contributors highlight how AI methods adapt under hardware constraints, achieve energy efficiency, handle uncertainty, and meet requirements of robustness, explainability, and regulatory compliance. This book is structured to balance theoretical advances with case studies and system prototypes. Part I covers foundations and methods for intelligent sensing, representation, and optimization. Part II presents platforms and architectures, including edge AI, distributed systems, and digital twin frameworks. Part III focuses on security, privacy, and reliability, reflecting the pressing demand for trustworthy AI in sensitive domains. Part IV illustrates application domains such as healthcare instrumentation, intelligent transportation, robotics, industrial inspection, environmental monitoring, and urban computing.

This book is a compilation of high-quality scientific papers presented at International Conference on Artificial Intelligence, Electronic Instruments and Information Systems (AIEIIS 2025). This book addresses the integration challenge: AI is rapidly evolving, but practical deployment requires seamless interaction with physical devices, embedded systems, and secure information infrastructures. This book emphasizes end to end solutions, showing how advanced algorithms can be embedded into real world sensing, measurement, and control platforms. Contributors highlight how AI methods adapt under hardware constraints, achieve energy efficiency, handle uncertainty, and meet requirements of robustness, explainability, and regulatory compliance. This book is structured to balance theoretical advances with case studies and system prototypes. Part I covers foundations and methods for intelligent sensing, representation, and optimization. Part II presents platforms and architectures, including edge AI, distributed systems, and digital twin frameworks. Part III focuses on security, privacy, and reliability, reflecting the pressing demand for trustworthy AI in sensitive domains. Part IV illustrates application domains such as healthcare instrumentation, intelligent transportation, robotics, industrial inspection, environmental monitoring, and urban computing.

This book is a compilation of high-quality scientific papers presented at International Conference on Artificial Intelligence, Electronic Instruments and Information Systems (AIEIIS 2025). This book addresses the integration challenge: AI is rapidly evolving, but practical deployment requires seamless interaction with physical devices, embedded systems, and secure information infrastructures. The proceedings emphasize end‑to‑end solutions, showing how advanced algorithms can be embedded into real‑world sensing, measurement, and control platforms. Contributors highlight how AI methods adapt under hardware constraints, achieve energy efficiency, handle uncertainty, and meet requirements of robustness, explainability, and regulatory compliance. The volume is structured to balance theoretical advances with case studies and system prototypes. Part I covers foundations and methods for intelligent sensing, representation, and optimization. Part II presents platforms and architectures, including edge AI, distributed systems, and digital twin frameworks. Part III focuses on security, privacy, and reliability, reflecting the pressing demand for trustworthy AI in sensitive domains. Part IV illustrates application domains such as healthcare instrumentation, intelligent transportation, robotics, industrial inspection, environmental monitoring, and urban computing.

This book is a compilation of high-quality scientific papers presented at International Conference on Artificial Intelligence, Electronic Instruments and Information Systems (AIEIIS 2025). This book addresses the integration challenge: AI is rapidly evolving, but practical deployment requires seamless interaction with physical devices, embedded systems, and secure information infrastructures. The proceedings emphasize end to end solutions, showing how advanced algorithms can be embedded into real world sensing, measurement, and control platforms. Contributors highlight how AI methods adapt under hardware constraints, achieve energy efficiency, handle uncertainty, and meet requirements of robustness, explainability, and regulatory compliance. The volume is structured to balance theoretical advances with case studies and system prototypes. Part I covers foundations and methods for intelligent sensing, representation, and optimization. Part II presents platforms and architectures, including edge AI, distributed systems, and digital twin frameworks. Part III focuses on security, privacy, and reliability, reflecting the pressing demand for trustworthy AI in sensitive domains. Part IV illustrates application domains such as healthcare instrumentation, intelligent transportation, robotics, industrial inspection, environmental monitoring, and urban computing.