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This book enables the readers to design, optimize, and control complex systems with greater precision and efficiency. It further provides practical insights and presents case studies for readers interested in exploring the intersections between Artificial Intelligence (AI) and industry. This book discusses important topics such as algorithmic design, mathematical modeling, natural language processing (NLP), Machine Learning, and Computer Vision. In the rapidly evolving landscape of computer vision and Artificial Intelligence, the demand for robust and efficient multiple object tracking (MOT) systems has surged across various domains, including surveillance, autonomous vehicles, and human-computer interaction. Addressing this demand, our project introduces a cutting-edge real?time MOT framework that amalgamates the strengths of YOLOv7, DeepSORT, and TensorFlow. Object detection and tracking are fundamental challenges in Computer Vision, particularly in scenarios with dynamic environments, occlusion, and varying object scales. YOLOv7, renowned for its accuracy and speed in object detection, forms the first layer of our framework. By providing a comprehensive understanding of the scene in real time, YOLOv7 lays the foundation for subsequent tracking processes. To address the intricacies of object tracking over time, our system employs DeepSORT, a state-of-the-art tracking algorithm that seamlessly associates and tracks objects across consecutive frames. DeepSORT harnesses deep learning techniques to maintain tracking identities in the face of challenges such as occlusion and object interactions. This book Explores practical applications of Artificial Intelligence in engineering, including optimization, predictive modeling, decisions making, and control systems Provides reals world exampless of the applications of Artificial Intelligence in engineering, drawing from a range of industries, including aerospace, automotive, and manufacturing Discusses technologies such as Machine Learning and computer vision for aircraft design optimization, fault diagnosis, and autonomous navigation Explains natural language processing for analyzing and optimizing building systems, while robotics can be used for construction automation Presents Artificial Intelligence technologies for optimization of manufacturing processes, predictive maintenance, and quality control Preface List of contributors 1 Navigating the ethical landscape of artificial intelligence: challenges, frameworks, and responsible deployment 2 Opportunities of intelligent machine learning techniques for sustainable development 3 Disease prediction based on drug reviews using TF‑IDF in natural language processing 4 Investigating the potential of ChatGPT in substituting or assisting teachers in the digital era 5 Defence of DDoS attacks using targets in motion 6 Unlocking sign language interpretation: leveraging transfer learning in deep learning models 7 AI engineering for the best sustainable practices towards social applications 8 Healthcare robots enabled with IOT and artificial intelligence in healthcare applications 9 AI strategies for the realm of sustainable management and practices 10 Unveiling life’s horizon: predictive insights with automated machine learning 11 Sustainable energy optimization in smart buildings: a deep learning LSTM approach for intelligent management and environmental impact reduction 12 ConvXception: Covid‑19 detection using ConvXception model M. PURUSHOTHAM REDDY, E. GOUTHAM, T. NITHIN, AND GOLLA ANGEL 13 Automated road safety: Yolov3‑based non‑helmet rider detection with optical character recognition 14 Customer churn prediction for retention analysis 15 Exploring the intersection of sustainable economies and the Metaverse for a prosperous future 16 UNet‑based MRI image analysis for enhanced brain tumor spotting: a cutting‑edge approach in medical imaging 17 Multiple object tracking using deep learning and machine learning techniques 18 KGRecSys: Knowledge graph‑based recommendation systems: a comprehensive overview 19 Brain‑inspired cognitive architectures for artificial intelligence: unlocking the potential of human‑like intelligence 20 Harnessing deep learning algorithms for enhanced stock price predictability