This book examines the latest developments in the area of soft computing with engineering applications. It explores topics such as fuzzy sets, intuitionistic fuzzy sets, unmanned aerial vehicles, soft sets, neutrosophic sets, fractional calculus, Big Data analytics, and the mathematical foundations of convolutional neural networks (CNNs). Soft Computing: Engineering Applications offers readers a comprehensive and in-depth understanding of various cutting-edge technologies that are transforming industries worldwide. The book explores soft computing techniques in a very systematic manner. It elucidates the concepts, theories, and applications of fuzzy sets, enabling readers to grasp the fundamentals and explore their applications in various fields. It provides new insight into unmanned aerial vehicle applications to fuzzy soft set based decision-making. It then discusses new fixed point results in orthogonal neutrosophic generalized metric spaces and explores statistical convergence of triple sequences in a credibility space. The authors then provide readers with a solid grasp of the mathematical underpinnings of CNNs, enabling them to design, train, and optimize neural networks for image recognition, object detection, and other computer vision tasks. The authors also present new studies in fractional calculus and explore advanced visualization algorithms and techniques for Big Data analytics. Soft Computing will be useful for beginners and advanced researchers in engineering and applied sciences and healthcare professionals working in soft computing applications.