Ebenezer Esenogho – författare

AI Innovations in Marine Resources and Pollution Management explores how cutting-edge artificial intelligence technologies are revolutionizing the monitoring, understanding, and protection of our oceans. This comprehensive guide addresses the pressing challenges of marine pollution and resource conservation by showcasing AI-driven solutions-from advanced predictive models and real-time detection to sophisticated mapping and sensor fusion technologies. It highlights innovative applications such as microplastics classification, oil spill detection with smart drones, and geospatial intelligence for ecosystem monitoring, providing practical insights for researchers, policymakers, and environmental practitioners.By harnessing the transformative power of AI, this book aims to improve pollution tracking, enhance response strategies, and promote sustainable management of marine environments-an essential resource for students and researchers dedicated to protecting our oceans and fostering a sustainable future.Provides in-depth insights into innovative solutions such as sensor fusion, geospatial intelligence, and drone-based detection systems to enhance marine environmental protectionCovers a wide range of AI-driven technologies and applications for monitoring, predicting, and managing marine pollution and resourcesIncludes case studies from around the world that illustrate the successful implementation of AI tools in tracking microplastics, oil spills, and emerging pollutants, thus informing on sustainable marine management practices

This book explores the transformative intersection of artificial intelligence (AI) and microbiology, introducing the concept of microbial artificial intelligence (MAI). Designed to bridge the gap between microbiology and AI, it provides a comprehensive overview of fundamental AI concepts, practical applications, limitations, ethical considerations, and future opportunities in this emerging field.Featuring contributions from a global team of experts, the book is structured into two distinct sections for a deeper exploration of MAI. The first section introduces the fundamentals of MAI, offering microbiologists a clear understanding of AI principles and their relevance to microbiology. The second section highlights real-world applications of MAI across diverse industries, including healthcare, genomics, metagenomics, drug discovery, antimicrobial resistance, biofuel production, food quality and safety, astrobiology, and forensic science. This section addresses critical issues such as bias in MAI, ethical challenges, and the impact of data collection and interpretation on research outcomes, while proposing strategies to mitigate these challenges.This essential resource is ideal for students and researchers eager to explore the potential of MAI and understand AI's growing influence on microbiology. It also serves as valuable supplementary reading for AI professionals seeking insights into broader applications of AI across scientific disciplines.

This book explores the transformative intersection of artificial intelligence (AI) and microbiology, introducing the concept of microbial artificial intelligence (MAI). Designed to bridge the gap between microbiology and AI, it provides a comprehensive overview of fundamental AI concepts, practical applications, limitations, ethical considerations, and future opportunities in this emerging field.Featuring contributions from a global team of experts, the book is structured into two distinct sections for a deeper exploration of MAI. The first section introduces the fundamentals of MAI, offering microbiologists a clear understanding of AI principles and their relevance to microbiology. The second section highlights real-world applications of MAI across diverse industries, including healthcare, genomics, metagenomics, drug discovery, antimicrobial resistance, biofuel production, food quality and safety, astrobiology, and forensic science. This section addresses critical issues such as bias in MAI, ethical challenges, and the impact of data collection and interpretation on research outcomes, while proposing strategies to mitigate these challenges.This essential resource is ideal for students and researchers eager to explore the potential of MAI and understand AI's growing influence on microbiology. It also serves as valuable supplementary reading for AI professionals seeking insights into broader applications of AI across scientific disciplines.