Syed Ali Hassan – författare

Artificial Intelligence and Food Science examines a range of applications from pre- and post-harvest management to food packaging and the dairy industry, providing a thorough overview of how AI is revolutionizing these industries. The initial chapters introduce the fundamentals of AI and its recent advancements, covering key areas such as Constraint Satisfaction Problems, Adversarial Search, and Statistical Learning Theory. The book then moves on to explore AI applications in pre- and post-harvest management and highlights techniques such as machine vision and spectral imaging for non-destructive analysis of agricultural products.The role of AI in the fat and oil processing industry, specifically the use of bioinformatics predictive methods based on artificial neural network (ANN) is discussed in detail. Subsequent chapters probe the use of AI in the processing of fruits, vegetables, dairy, and meat, and detail how technologies like neural networks and Industry 4.0 innovations can drive improvements in product quality. Later chapters explore AI applications in the baking and confectionery industries, with a focus on automation and 3D printing technologies that are setting new standards for production and product design.Functions as an accessible book on artificial intelligence and smart techniques employed in the food industryDescribes how AI applications enhance efficiency and reliability in various food sector processesProvides in-depth information on the current challenges faced by the food industry in implementing AI and offers possible solutionsEnables food researchers and industrialists to make informed decisions about adopting AI and smart techniques over conventional methodsOffers PowerPoint slides and a test bank for instructors and students

Underwater communication systems have been gaining significant interest over the past two decades in addressing various applications, ranging from the depths of the ocean to its surface. To implement applications such as oil monitoring, earthquake and tsunami detection, marine animal study and military surveillance, underwater communications are crucial in establishing reliable connections between sensor nodes.Advances in Underwater Communication and Networking covers 6G-based underwater acoustic communications that integrate modern technologies such as software-defined networking (SDN), network function virtualization (NFV), non-orthogonal multiple access (NOMA), reconfigurable intelligent surfaces (RIS), unmanned aerial vehicles (UAVs), autonomous underwater vehicles (AUVs), and AI.The book investigates NOMA as a solution to enhance spectral efficiency and user fairness in order to tackle acoustic band issues. This is followed by a detailed exploration of various machine learning and deep learning techniques for exploring underwater acoustic environments, optimizing acoustic signal transmission, and using hybrid intelligent models to power acoustic communications. The later chapters explore those few underwater applications that cover AI-based seismic monitoring, detection of tsunamis and earthquakes using AI-based models, and AI-based sonar image classification and analysis. In the final two chapters, the focus is on testing sound propagation in water and using various sonar systems to acquire underwater images and investigate real-life applications such as mine-detection, seabed mapping, and AUV navigation. Finally, a modelling scenario is developed and verified using the UPPAAL model checker for sonar-based subsystems.Advances in Underwater Communication and Networking discusses a variety of recent concepts that will open new avenues for researchers in this field to explore underwater environments using 6G concepts and technologies.

This book provides and assesses the techniques required for the realization of practical wireless-powered backscatter systems for large-scale and intelligent IoT networks.