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This title is printed to order. This book may have been self-published. If so, we cannot guarantee the quality of the content. In the main most books will have gone through the editing process however some may not. We therefore suggest that you be aware of this before ordering this book. If in doubt check either the author or publisher’s details as we are unable to accept any returns unless they are faulty. Please contact us if you have any questions.
Generating data for the manufacturing of augmented, connected, and smart cities is a great opportunity to explore key concepts, challenges, and solutions. The use of relational databases and data prediction models using Machine Learning (ML), Deep Learning (DL), and Neural Networks (NN) techniques is crucial for collecting, organizing and exploitation of data in the context of smart cities.By integrating these elements, you shed light on how relational databases provide an effective framework for storing urban data and how advanced ML, DL and RN techniques can predict, analyze, and derive actionable insights from those data.The integration of Artificial Intelligence (AI) and Robotics plays a crucial role in the evolution towards smart and connected cities.A detailed case studies and practical applications of smart city concepts are presented in a second volume, providing real-world examples and insights into the implementation of smart city technologies.
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This title is printed to order. This book may have been self-published. If so, we cannot guarantee the quality of the content. In the main most books will have gone through the editing process however some may not. We therefore suggest that you be aware of this before ordering this book. If in doubt check either the author or publisher’s details as we are unable to accept any returns unless they are faulty. Please contact us if you have any questions.
Generating data for the manufacturing of augmented, connected, and smart cities is a great opportunity to explore key concepts, challenges, and solutions. The use of relational databases and data prediction models using Machine Learning (ML), Deep Learning (DL), and Neural Networks (NN) techniques is crucial for collecting, organizing and exploitation of data in the context of smart cities.By integrating these elements, you shed light on how relational databases provide an effective framework for storing urban data and how advanced ML, DL and RN techniques can predict, analyze, and derive actionable insights from those data.The integration of Artificial Intelligence (AI) and Robotics plays a crucial role in the evolution towards smart and connected cities.A detailed case studies and practical applications of smart city concepts are presented in a second volume, providing real-world examples and insights into the implementation of smart city technologies.