Technological Advancements and Artificial Intelligence Innovations

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Technological Advancements and Artificial Intelligence Innovations explores how cutting-edge AI technologies are transforming key sectors including health analytics, energy, biochemistry, subsurface engineering, and geoscience.

This volume is a research work that explores the latest developments and applications of technology and AI in various domains. It provides a comprehensive and up-to-date overview of the current state and prospects of technological and AI innovations in fields such as health, physics, mineral engineering, petroleum and energy. It comprises 12 chapters, each written by an expert in the respective field.

The book offers a balanced and objective perspective on the benefits, challenges and ethical implications of technology and AI, as well as insights into the future trends and opportunities in these fields. This balanced approach elevates the book into a unique and indispensable resource. Readers will not only be exposed to the frontiers of knowledge and innovation but will also find themselves equipped with tools to critically evaluate the impact of these advancements on society and the world at large. It offers a comprehensive, multidimensional, and future-oriented perspective that is indispensable for navigating the ever-evolving landscape of technology and AI. It is a definitive guide for both neophytes and seasoned experts, equipping them with knowledge and foresight to actively engage and contribute to the ongoing technological revolution. This book is not merely a passive repository of information; it is an active catalyst for intellectual growth and informed decision-making in an age where the integration of technology and AI is omnipresent and inevitable.

Obsah

Preface. 1. Introduction. 2. A Review of the Prospect of Utilizing AI Techniques in Digital Outcrop Model Geological Mapping. 3. Agentic Workflows and Multi‑Agent Systems: Platforms and Protocols in 2025. 4. Artificial-Neural-Network-Based Correlation for Predicting Oil Formation Volume Factor Using White-Box Technique. 5. CitricNet: Citrus Quality Grading Using Computer Vision. 6. Comparative Analysis of Machine Learning Techniques for Estimating CO2 Absorption in Ionic Liquids and the Implications on CO2 Capture. 7. Explainable Deep Learning and Multi-Scale Temporal Analysis for COVID-19 Outbreak Prediction in Nigeria. 8. An Automated Kick Detection System Based on Optimized Data Analytics. 9. Nanopore Sensing for Single-Entity Analysis: Challenges, Enhancements, and Future with AI and Computational Methods. 10. Identification and Evaluation of Shallow Water Flow-Prone Facies Using Advanced Seismic Interpretation and Machine Learning: A Case Study from the Malay Basin, Malaysia. Index.