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This book looks at the success and continuing potential of photovoltaic (PV) technology in combating climate change by harnessing solar energy through building-integrated (BIPV) and building-applied photovoltaics (BAPV). With PV global capacity soaring from 940 GW in 2021 to 1100 GW in 2022 and projected to reach 1456 GW by the end of 2023, the world is witnessing an unprecedented shift towards renewable energy solutions. Today, no single country exists without some form of PV installation, driven by reduced costs and abundant free sunshine. The book’s chapters delve into the advancements in PV technology, exploring its integration as an essential building material by examining 14 countries and regions – Brazil, The Netherlands, Austria, Poland, Argentina, Iran, Germany, Malaysia, Oman, Bahrain, India, Australia, the United Kingdom, and Egypt – and providing a comprehensive overview of their successful adoption of PV for electricity generation. Whether you’re an architect, builder, engineer, or climate advocate, this vital resource offers insights, international case studies, and a path to a greener future. Explores how building-integrated (BIPV) and building-applied photovoltaics (BAPV) can mitigate environmental impact; Includes international case studies; Offers invaluable insights into the successful implementation of PV technology.

Building-integrated photovoltaic systems. --- Building-integrated photovoltaic systems --- Cost effectiveness. --- Photovoltaic power generation. --- Renewable energy sources. --- Sustainable architecture. --- Energy policy. --- Energy and state. --- Solar energy. --- Photovoltaics. --- Renewable Energy. --- Sustainable Architecture/Green Buildings. --- Energy Policy, Economics and Management. --- Solar Thermal Energy.

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With the growing advances in technology and transformation to digital services, the world is becoming more connected and more complex. Huge heterogeneous data are generated at rapid speed from various types of sensors. Augmented with artificial intelligence and machine learning and internet of things, latent relations, and new insights can be captured helping in optimizing plans and resource utilization, improving infrastructure, and enhancing quality of services. A “spatial data management system” is a way to take care of data that has something to do with space. This could include data such as maps, satellite images, and GPS data. A temporal data management system is a system designed to manage data that has a temporal component. This could include data such as weather data, financial data, and social media data. Some advanced techniques used in spatial and temporal data management systems include geospatial indexing for efficient querying and retrieval of location-based data, time-series analysis for understanding and predicting temporal patterns in datasets like weather or financial trends, machine learning algorithms for uncovering hidden patterns and correlations in large and complex datasets, and integration with Internet of Things (IoT) technologies for real-time data collection and analysis. These techniques, augmented with artificial intelligence, enable the extraction of latent relations and insights, thereby optimizing plans, improving infrastructure, and enhancing the quality of services. This book provides essential technical knowledge, best practices, and case studies on the state-of-the-art techniques of artificial intelligence and machine learning for spatiotemporal data analysis and modeling. The book is composed of several chapters written by experts in their fields and focusing on several applications including recommendation systems, big data analytics, supply chains and e-commerce, energy consumption and demand forecasting, and traffic and environmental monitoring. It can be used as academic reference at graduate level or by professionals in science and engineering related fields such as data science and engineering, big data analytics and mining, artificial intelligence, machine learning and deep learning, cloud computing, and internet of things. .

Data mining. --- Quantitative research. --- Big data. --- Engineering --- Data Mining and Knowledge Discovery. --- Data Analysis and Big Data. --- Big Data. --- Data Engineering. --- Data processing. --- Geomatics.

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In "Sports Analytics: Data-Driven Sports and Decision Intelligence," embark on a journey through the exhilarating world of sports enhanced by the power of data-driven insights. From the nail-biting moments on the field to the strategic decisions behind the scenes, this comprehensive guide unveils the secrets that propel teams to victory and champions to greatness.It explores the cutting-edge techniques and methodologies that revolutionize the way we understand and analyze sports performance. From player evaluations to game strategies, injury prevention to fan engagement, this book equips you with the tools to gain a competitive edge in any sport. Whether you're a coach, player, analyst, or simply a passionate fan, this book will change the way you see the game. This book details how to use analytics and machine learning to highlight key performance indicators (KPIs) of sports for analysis. The authors show how to apply various statistical techniques, machine learning and data mining algorithms for on-field and off-field analysis. They go on to show how analytical algorithms are used in the sports ecosystem to derive solutions for the team and leadership, helping team managers and coaches to monitor games and player information through dashboards. The book then shows how to deploy machine learning algorithms for validating and improving teams and players performance. The book is relevant to professionals and academics working in machine learning and data analysis related to sports. Shows how to apply machine learning and data mining algorithms for on-field and off-field analysis; Details how to use machine learning to highlight key performance indicators of sports for performance analysis; Relevant to professionals and academics working in machine learning and data analysis related to sports.

Telecommunication. --- Machine learning. --- Artificial intelligence. --- Communications Engineering, Networks. --- Machine Learning. --- Artificial Intelligence. --- Sports --- Data processing. --- Statistical methods.

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This book describes the basic principles and techniques of cold plasma to synthesize nanomaterials, emphasizing the fundamentals. Nanotechnology has matured enough to make inroads into the industry. “Quantum size effects” is the basis of the exotic properties of nanomaterials. The shapes and the size distribution dictate the properties of the nano-matter. The demands of the synthesis technique are to produce nano-matter with uniform size, repeatable shapes, uniform size distribution, stability of the nanostructures (reaching thermodynamic equilibrium), reproducibility of the particle sizes, and reliability of the process. These demands can be met when the synthesis technique has precise control over the process parameters. Cold plasma techniques possess all the requirements of the needs of nanomaterial synthesis. The cold plasma, an evolving field, has been established to be the most powerful tool not only for micro-electronics (both in the deposition and etching) but in many areas like health care, medicine, agriculture, food processing, etc. The book’s primary emphasis is to explain the basic principles and concepts of cold plasma in nanomaterial synthesis. The target audience is undergraduate and graduate students learning nanomaterial synthesis and plasma technology. It is hoped that this book also is a good source of reference for practicing scientists and engineers involved in synthesizing nanomaterials and nanostructures in the industry.

Plasma (Ionized gases). --- Condensed matter. --- Quantum dots. --- Basic Plasma Phenomena and Gas Discharges. --- Two-dimensional Materials. --- Condensed Matter Physics. --- Quantum Dots. --- Plasma (Ionized gases)