Artificial Intelligence for Near-Infrared Spectroscopy and Electrical Impedance Spectroscopy

This book examines the integration of artificial intelligence (AI), near-infrared spectroscopy (NIR), and electrical impedance spectroscopy (EIS) to develop intelligent, embedded spectrometers for real-world diagnostics. It provides insights into both hardware and firmware, guiding readers on how to design and implement these advanced spectrometers. The focus is on calibration, validation, and deployment strategies, particularly for creating affordable, portable spectrometers suitable for Internet of Things (IoT) applications, thereby democratizing access to advanced diagnostic tools. The book addresses challenges related to data interpretation, basic hardware design, and real-world implementation. It also introduces machine learning models that automate the interpretation of complex high-dimensional spectral data, enhancing both accuracy and scalability. Covering foundational theory and practical applications, the text illustrates how AI can improve spectral analysis in various fields, including food quality assessment, skin and fluid characterization, and antibiotic detection in milk. Artificial Intelligence for Near-Infrared Spectroscopy and Electrical Impedance Spectroscopy: Concepts and Applications is designed for researchers, engineers, students, and innovators. It serves as a practical and visionary guide to the future of smart sensing technologies.