Urban and Regional Data Management


Book Description

Spatial technologies like GIS, CAD, and spatial DBMS have proved their applicability and usability in almost every sector of urban development. Urban Planning Systems, Public Participation Systems, and others have been continuously developed and improved contributing to better decision making, communicating ideas between different actors as well as




Urban Analytics


Book Description

The economic and political situation of cities has shifted in recent years in light of rapid growth amidst infrastructure decline, the suburbanization of poverty and inner city revitalization. At the same time, the way that data are used to understand urban systems has changed dramatically. Urban Analytics offers a field-defining look at the challenges and opportunities of using new and emerging data to study contemporary and future cities through methods including GIS, Remote Sensing, Big Data and Geodemographics. Written in an accessible style and packed with illustrations and interviews from key urban analysts, this is a groundbreaking new textbook for students of urban planning, urban design, geography, and the information sciences.




Digital Twins for Smart Cities and Villages


Book Description

Digital Twins for Smart Cities and Villages provides a holistic view of digital twin technology and how it can be deployed to develop smart cities and smart villages. Smart manufacturing, smart healthcare, smart education, smart agriculture, smart rural solutions, and related methodologies using digital twins are discussed, including challenges in deployment, their solutions and future roadmaps. This knowledge, enriched by a variety of case studies presented in the book, may empower readers with new capabilities for new research as well as new tasks and strategies for practical implementation and real-world problem solving.The book is thoughtfully structured, starting from the background of digital twin concepts and basic know-how to serve the needs of those new to the subject. It continues with implementation to facilitate and improve management in several urban contexts, infrastructures, and more. Global case study assessments further provide a deep characterization of the state-of-the-art in digital twin in urban and rural contexts. - Uniquely focuses on applications for smart cities and villages, including smart services for health, education, mobility, and agriculture - Provides use cases and practical deployment of research involved in the emerging uses of digital twins - Discusses all pertinent issues, challenges, and possible solutions instrumental in implementing digital twins smart solutions in this context - Edited and authored by a global team of experts in their given fields




Smart Cities


Book Description




Geospatial Application Development Using Python Programming


Book Description

Academics and researchers currently grapple with a pressing issue; the demand for precise and insightful geographical information has surged across various fields, encompassing urban planning, environmental monitoring, agriculture, and disaster management. This surge has revealed a substantial knowledge gap, underscoring the need for effective applications that can bridge the gap between cutting-edge technologies and practical usage. Geospatial Application Development Using Python Programming emerges as the definitive solution to this challenge. This comprehensive book equips academics, researchers, and professionals with the essential tools and insights required to leverage the capabilities of Python programming in the realm of spatial analysis. It goes beyond merely connecting these two realms; it actively fosters their collaboration. By advancing knowledge in spatial sciences and highlighting Python's pivotal role in data analysis and application development, this book plays a crucial part in addressing the challenge of effectively harnessing geographical data.




Advances in Human Factors, Sustainable Urban Planning and Infrastructure


Book Description

This book deals with human factors research directed towards realizing and assessing sustainability in the built environment. It reports on advanced engineering methods for sustainable infrastructure design, as well as on assessments of the efficient methods and the social, environmental, and economic impact of various designs and projects. The book covers a range of topics, including the use of recycled materials in architecture, ergonomics in buildings and public design, sustainable design for smart cities, design for the aging population, industrial design, human scale in architecture, and many more. Based on the AHFE 2017 International Conference on Human Factors, Sustainable Urban Planning and Infrastructure, held on July 17–21, 2017, in Los Angeles, California, USA, this book, by showing different perspectives on sustainability and ergonomics, represents a useful source of information for designers in general, urban engineers, architects, infrastructure professionals, practitioners, public infrastructure owners, policy makers, government engineers and planners, as well as operations managers, and academics active in applied research.




TRANSFORMING INDUSTRIES WITH AI: EXPLORING THE UPSIDES AND DOWNSIDES OF EMERGING TECHNOLOGY


Book Description

In the current day and age of technology, buzzwords such as artificial intelligence (AI), the internet of things (IoT), and cloud computing are often used. AI is the technology that tries to make computers or other machines equal to the human brain, making them capable of learning and problem-solving in the same way that humans do. Applications based on AI may be readily connected with other developing technologies such as the Internet of Things (IoT), the cloud, Big Data, and Blockchain. The Internet of Things refers to a network of interconnected, internet-enabled items or things that are able to gather and share data with one another. In recognition of the idea of the Internet of items, a significant number of tangible items are now being connected with the internet at an exceptionally rapid pace. By the year 2025, there will be more than 30 billion Internet of Things connections, with approximately four Internet of Things devices per person on average, according to reports and current trends. Cloud computing provides a means through which the huge amounts of data created by these Internet of Things applications may be sent to their respective endpoints. The use of cloud computing is widely acknowledged to be a facility for the processing and storage of data. Just-in-time processing and lightning fast response times are necessities for any and all real-time applications that make use of the Internet of Things. Researchers, academics, and industrialists in the fields of health care, agriculture, telecommunications, online and mobile commerce, and transportation have shown a significant amount of interest in AI and IoT-based data. In today's world, AI-based methodologies increase the role that IoT plays in business monitoring, health-care monitoring, illness prediction, bioinformatics, research and development, stock market prediction, social network analysis, weather analysis, agriculture, transportation, and resource optimization. The implementation of these applications needs a certain amount of processing capability as well as data storage, both of which are often given by cloud-based services. The data that has been saved is processed in a high-precision and just-in-time way with the help of AI algorithms. The cloud is a strong instrument that can send data not only via the standard channels of the internet but also through a dedicated direct connection. The Internet of Things becomes the source of creating enormous amounts of data, and the cloud becomes an essential component for data storage. As a result, the Internet of Things and clouds have become deeply intertwined in order to provide commercial business services. 1 | P a ge This configuration is sometimes referred to as cloud-based IoT. As a result of their success in providing cloud-based Internet of Things (IoT) services, companies like Amazon Web Services (AWS), Google, and Microsoft have become industry leaders. This makes the task much more rewarding. In addition, the cloud-based Internet of items is utilized to link a broad variety of intelligent items for usage in different applications. Artificial intelligence (AI), the internet of things (IoT), and cloud computing all play significant roles in a variety of domains in the present and will continue to do so in the future. The goal of AI is to analyze and collect the data produced through cloud-based Internet of Things devices by gathering data from a variety of businesses. Integrating AI, IoT, and the cloud has resulted in a transformation of both the entire storage capacity and the digital world, and as a result, it has become a subject of intense interest among academics and academicians. The purpose of this chapter is to place an emphasis on the function that AI plays in data storage that is based on the cloud and IoT. The remaining parts of the chapter are broken down into the following sections: storing of data on the cloud is the primary emphasis. examines the function that IoT plays in cloud environments. In addition, the part that AI plays in the Internet of Things (IoT) and cloud data storage is discussed in. Section 6 brings the chapter to a close by discussing the applications of AI, IoT, and clouds in a variety of industries.




Urban Energy Systems for Low-Carbon Cities


Book Description

With an increase of global energy demand arising in urban settlements, the key challenges for the urban energy transition include analysis of energy efficiency options and the potential of renewable energy systems within the existing building stock, making cities a key actor in the transition success. In Urban Energy Systems for Low Carbon Cities, indicators to evaluate urban energy performance are introduced and the status quo of monitoring and efficiency valuation schemes are discussed. The book discusses advances on the state-of-the-art of research in a number of key areas: - Energy demand and consumption mapping and monitoring - Optimization of design and operation of urban supply and distribution systems - Integration of renewable energy and urban energy network models - Demand side management strategies to better match renewable supply and demand and increase flexibilities With innovative modelling methods this book gives a real bottom-up modelling approach used for the simulation of energy consumption, energy conversion systems and distribution networks using engineering methods. - Provides support and guidance on the energy transition issues relating to energy demand, consumption mapping and monitoring - Includes examples from case study cities, including Vienna, Geneva, New York and Stuttgart - Analyzes the potential of energy management strategies in urban areas




Big Data Analytics Techniques for Market Intelligence


Book Description

The ever-expanding realm of Big Data poses a formidable challenge for academic scholars and professionals due to the sheer magnitude and diversity of data types, along with the continuous influx of information from various sources. Extracting valuable insights from this vast and complex dataset is crucial for organizations to uncover market intelligence and make informed decisions. However, without the proper guidance and understanding of Big Data analytics techniques and methodologies, scholars may struggle to navigate this landscape and maximize the potential benefits of their research. In response to this pressing need, Professor Dina Darwish presents Big Data Analytics Techniques for Market Intelligence, a groundbreaking book that addresses the specific challenges faced by scholars and professionals in the field. Through a comprehensive exploration of various techniques and methodologies, this book offers a solution to the hurdles encountered in extracting meaningful information from Big Data. Covering the entire lifecycle of Big Data analytics, including preprocessing, analysis, visualization, and utilization of results, the book equips readers with the knowledge and tools necessary to unlock the power of Big Data and generate valuable market intelligence. With real-world case studies and a focus on practical guidance, scholars and professionals can effectively leverage Big Data analytics to drive strategic decision-making and stay at the forefront of this rapidly evolving field.




Soft Computing and Optimization Techniques for Sustainable Agriculture


Book Description

This book covers the emerging applications of different computational and optimization techniques in order to achieve a sustainable agriculture. A sustainable agricultural management requires tools in providing integrated, area-specifi c, and interpreted prediction or forecasting and guidance in every aspect in agriculture.