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This book highlights the analytics and optimization issues in industry, to propose new approaches, and to present applications of innovative approaches in real facilities. In the past few decades there has been an exponential rise in the application of artificial intelligence for solving complex and intricate problems arising in industrial domain. The versatility of these techniques have made them a favorite among scientists and researchers working in diverse areas. The book is edited to serve a broad readership, including computer scientists, medical professionals, and mathematicians interested in studying computational intelligence and their applications. It will also be helpful for researchers, graduate and undergraduate students with an interest in the fields of Artificial Intelligence and Industrial problems. This book will be a useful resource for researchers, academicians as well as professionals interested in the highly interdisciplinary field of Artificial Intelligence.

Artificial Intelligence in Industrial Applications: Approaches to Solve the Intrinsic Industrial Optimization Problems

Chapter 1: Machine Learning Techniques for Grocery Sales Forecasting by Analyzing Historical Data.- Chapter 2: Identifying impact of sanitation and environmental safety in hospitality sector to identify the spread of COVID -19 using Polynomial Function Simulation.- Chapter 3: Upskilling and Curating the potentials of IoT enabled Smart Cities: Use Cases and Implementation Strategies.- Chapter 4: An Efficient Deep Learning Framework for People Detection in Overhead Images.