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This book explores the transformative potential of AI-driven spatial computing, focusing on its impact on business and technology. It examines key technologies like virtual reality (VR), augmented reality (AR), and artificial intelligence (AI), highlighting their convergence and the resulting opportunities for innovation. The authors discuss the evolution of spatial computing from science fiction to business reality, offering insights into its applications and benefits in various sectors. They emphasize the importance of leadership and strategic foresight in navigating this new era, while also addressing ethical considerations and risks. The book aims to guide business leaders and technologists in leveraging spatial computing to enhance user experiences and drive organizational success.

Artificial intelligence. --- Spatial systems.

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Geospatial data --- Geographic information systems --- Spatial systems.

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"Traditional methods for handling spatial data are encumbered by the assumption of separate origins for horizontal and vertical measurements, but modern measurement systems operate in a 3-D spatial environment. The 3-D Global Spatial Data Model: Principles and Applications, Second Edition maintains a new model for handling digital spatial data, the global spatial data model or GSDM. The GSDM preserves the integrity of three-dimensional spatial data while also providing additional benefits such as simpler equations, worldwide standardization, and the ability to track spatial data accuracy with greater specificity and convenience. This second edition expands to new topics that satisfy a growing need in the GIS, professional surveyor, machine control, and Big Data communities while continuing to embrace the earth center fixed coordinate system as the fundamental point of origin of one, two, and three-dimensional data sets. Ideal for both beginner and advanced levels, this book also provides guidance and insight on how to link to the data collected and stored in legacy systems."--Provided by publisher.

Spatial data infrastructures --- Spatial systems. --- Three-dimensional imaging. --- Mathematics.

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Geography --- Geography. --- Spatial systems. --- Géographie --- Systèmes spatiaux --- Spatial systems --- Geografie --- Geografische Informatie Systemen --- Modelleren. --- Géographie --- Systèmes spatiaux --- Systems, Spatial --- System analysis --- Cosmography --- Earth sciences --- World history

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From environmental management to land planning and geo-marketing, the number of application domains that may greatly benefit from using data enriched with spatio-temporal features is expanding very rapidly. Unfortunately, development of new spatio-temporal applications is hampered by the lack of conceptual design methods suited to cope with the additional complexity of spatio-temporal data. This complexity is obviously due to the particular semantics of space and time, but also to the need for multiple representations of the same reality to address the diversity of requirements from highly heterogeneous user communities. Conceptual design methods are also needed to facilitate the exchange and reuse of existing data sets, a must in geographical data management due to the high collection costs of the data. Yet, current practice in areas like geographical information systems or moving objects databases does not include conceptual design methods very well, if at all. This book shows that a conceptual design approach for spatio-temporal databases is both feasible and easy to apprehend. While providing a firm basis through extensive discussion of traditional data modeling concepts, the major focus of the book is on modeling spatial and temporal information. Parent, Spaccapietra and Zimányi provide a detailed and comprehensive description of an approach that fills the gap between application conceptual requirements and system capabilities, covering both data modeling and data manipulation features. The ideas presented summarize several years of research on the characteristics and description of space, time, and perception. In addition to the authors' own data modeling approach, MADS (Modeling of Application Data with Spatio-temporal features), the book also surveys alternative data models and approaches (from industry and academia) that target support of spatio-temporal modeling. The reader will acquire intimate knowledge of both the traditional and innovative features

Database design --- Temporal databases --- Spatial systems --- Database management --- Mathematical models --- Database design. --- Database management. --- Temporal databases. --- Mathematical models. --- Information systems --- Spatial systems - Mathematical models