Preface

The section discusses different applications and advancements of robotics.

This chapter discusses different types, principles and applications of nanorobots that are used in different emerging areas. It also discusses the principles of different explored and programmed bots for repairing specific targets.

This chapter discusses robot path planning systems in a dynamic environment. The Deep Q-learning technique is used in this chapter by using a neural network. It helps to avoid different obstacles in the environment, which are dynamically created by the user.

This chapter only focuses on innovative design analysis of customized solar frames but not the working of the solar frames or air purifiers. This innovative design is going to change the concept of cycling in the future.

The section discusses different renewable energy applications for power management based on a sustainable future.

This chapter discusses a hybrid optimization technique for profit-based unit commitment. It solves the uncertainty issues for energy source management in wintertime and summertime. It helps reduce several noises that are related to gases that are harmful to fossil fuels and cause diseases and sicknesses.

This chapter illustrates the impact of Industry 4.0 based on the manufacturing system. The chapter contains several challenges and opportunities based on data production and integrating new technology in the sector of manufacturing.

The section discusses the systematic analysis of financial technology based on new and innovative applications.

In this chapter, the authors narrow down the overview of smart financial businesses and their complex challenges. It helps to manage the entire smart FinTech Ecosystem using the fusion of artificial intelligence and data science. It helps to enable smart FinTech and discusses some research problems among global academic and researcher communities.

This chapter provides insight into blockchain methodology applied in IoT healthcare security. It helps to provide the potential for the medical care environment. It also discusses how customary clinical frameworks and organizations have been occupied with the medical services area throughout the previous years.

This chapter provides a design development for pharmaceutical applications through the fusion of IoT and blockchain. In this chapter, it is suggested to avoid counterfeit drugs, delivering the pharmaceutical products to customers at the right time, and environmental parameters such as temperature and humidity are also monitored throughout the supply chain to avoid spoilage of pharmaceutical products.

The section discusses a different multidisciplinary approach based on new technologies and techniques that help in the automation system.

This chapter presents a holistic view of attrition and retention of employees on psychological aspects during this cut-throat competitive environment in India. Biology has a little role in management, though one cannot ignore biology in psychology. In broader terms, attrition is somehow related to psychology, and psychology and physiology are two sides of a coin.

This chapter provides a system for predicting the changes in the ecosystem. The changes in the ecosystem affect the living creatures who depend upon the ecosystem. One of the subsets of machine learning that play a vital role in saving the lives of living creatures is deep learning, which is used in this work for prediction purposes.

This chapter thoroughly examines solid-state drive subjects, ranging from the physical features of a flash memory cell to the design pattern. The subjects pertaining to the flash translation layer are described within the context of interconnected system-level operations.

This chapter discusses profit-based unit commitment using the global and local search methods. It suggests the combination of chaotic maps with Harris Hawks Optimizer and chaotic Sine Cosine Algorithm advancement strategy and assesses the execution of the proposed improved technique considering Plug-in Electric Vehicles.

This chapter discusses the classification of deep learning techniques for object detection. It uses an audit on a machine learning approach for classification. The applications of the protest location have been summarized, along with the diverse approaches to the location of the objects using template-based, portion-based, and region-based methods.