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Artificial intelligence --- Engineering applications. --- Engineering --- Data processing

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Unmanned aerial systems (UAS) have evolved rapidly in recent years thanks to advances in microelectromechanical components, navigation, perception, and artificial intelligence, allowing for a fast development of autonomy. This book presents general approaches to develop, test, and evaluate critical functions such as navigation, obstacle avoidance and perception, and the capacity to improve performance in real and simulated scenarios. It provides the practical knowledge to install, analyze and evaluate UAS solutions working in real systems; illustrates how to use and configure complete platforms and software tools; and reviews the main enabling technologies applied to develop UAS, possibilities and evaluation methodology. You will get the tools you need to evaluate navigation and obstacle avoidance functions, object detection, and planning and landing alternatives in simulated conditions. The book also provides helpful guidance on the integration of additional sensors (video, weather, meteorological) and communication networks to build IoT solutions. This is an important book for practitioners and researchers interested in integrating advanced techniques in the fields of AI, sensor fusion and mission management, and anyone interest in applying and testing advanced algorithms in UAS platforms.

Vehicles, Remotely piloted. --- Robotics. --- Drone aircraft. --- Artificial intelligence --- Engineering applications.

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Electric power systems --- Artificial intelligence --- Data processing. --- Engineering applications. --- Engineering --- Data processing

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This volume comprises the second part of the proceedings of the 10th International Conference on Finite Volumes for Complex Applications, FVCA, held in Strasbourg, France, during October 30 to November 3, 2023. The Finite Volume method, and several of its variants, is a spatial discretization technique for partial differential equations based on the fundamental physical principle of conservation. Recent decades have brought significant success in the theoretical understanding of the method. Many finite volume methods are also built to preserve some properties of the continuous equations, including maximum principles, dissipativity, monotone decay of the free energy, asymptotic stability, or stationary solutions. Due to these properties, finite volume methods belong to the wider class of compatible discretization methods, which preserve qualitative properties of continuous problems at the discrete level. This structural approach to the discretization of partial differential equations becomes particularly important for multiphysics and multiscale applications. In recent years, the efficient implementation of these methods in numerical software packages, more specifically to be used in supercomputers, has drawn some attention. The first volume contains all invited papers, as well as the contributed papers focusing on finite volume schemes for elliptic and parabolic problems. They include structure-preserving schemes, convergence proofs, and error estimates for problems governed by elliptic and parabolic partial differential equations. This volume is focused on finite volume methods for hyperbolic and related problems, such as methods compatible with the low Mach number limit or able to exactly preserve steady solutions, the development and analysis of high order methods, or the discretization of kinetic equations.

Mathematics. --- Engineering mathematics. --- Engineering --- Mathematical and Computational Engineering Applications. --- Data processing. --- Finite volume method.

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The variety of future powertrain concepts has drastically increased the development cost for automotive manufactures. Profitable investment requires a significantly leaner and efficient powertrain development process. Traditional methods of test and model based development need to be assisted by big data and data analytics. For this purpose, a valuable tool is available at the right time - artificial intelligence (AI). But what does AI really mean in a narrower sense? What concepts lie behind it? And how are the methods and algorithms transferable to powertrain applications? For the first time, this book aims to bridge the gap between automotive engineering and computer science, by illuminating the complexity of current AI concepts and demystifying it for powertrain applications. By elaborating on work processes, it shows how AI could be implemented and how completely novel methods can help us reshape the future of mobility. Target groups: Engineers in the field of powertrain development Engineers & computer scientists in the field of artificial intelligence Development departments of the automotive industry Suppliers, service providers of the automotive industry, IT industry (AI experts, start-ups etc.) Universities and research institutions All interested readers with technical background knowledge The author: Dr. Aras Mirfendreski has developed into an engine-expert throughout the German and international scientific landscape (studied at RWTH Aachen University, doctorate at Audi AG). Through his experience as a powertrain developer at Stuttgart FKFS for various OEMs as well as his activities as a senior program manager at Toyota, his developments always thrive on the transfer of state-of-the-art methods into corporate structures. Today, he serves as Vice President Engine R&D at Aquarius Engines and is also an AI expert, keynote speaker and consultant on artificial intelligence topics.

Transport engineering --- motorrijtuigen --- ingenieurswetenschappen --- Artificial intelligence --- Automobiles --- Engineering applications. --- Design and construction --- Law and legislation.