Data-Driven Urban Development
From BIM to the Augmented and Smart City
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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 acti...
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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