Advances in the knowledge of the tangible components (position, size, shape) and intangible components (identity, habits) of an historic building or site involves fundamental and complex tasks in any project related to the conservation of cultural heritage (CH). In recent years, new geotechnologies have proven their usefulness and added value to the field of cultural heritage (CH) in the tasks of recording, modeling, conserving, and visualizing. In addition, current developments in building information modeling (HBIM), allow integration and simulation of different sources of information, generating a digital twin of any complex CH construction. As a result, experts in the area have increased the number of available sensors and methodologies. However, the quick evolution of geospatial technologies makes it necessary to revise their use, integration, and application in CH. This process is difficult to adopt, due to the new options which are opened for the study, analysis, management, and valorization of CH. Therefore, the aim of the present Special Issue is to cover the latest relevant topics, trends, and best practices in geospatial technologies and processing methodologies for CH sites and scenarios as well as to introduce the new tendencies. This book originates from the Special Issue “Data Acquisition and Processing in Cultural Heritage”, focusing primarily on data and sensor integration for CH; documentation/restoration in CH; heritage 3D documentation and modeling of complex CH sites; drone inspections in CH; software development in CH; and augmented reality in CH. It is hoped that this book will provide the advice and guidance required for any CH professional, making the best possible use of these sensors and methods in CH.

Introduction to Data Acquisition & Control; Analog and Digital Signals; Signal Conditioning; The Personal Computer for Real Time Work; Plug-in Data Acquisition Boards; Serial Data Communications; Distributed & Standalone Loggers/Controllers; IEEE 488 Standard; Ethernet & LAN Systems; The Universal Serial Bus (USB); Specific Techniques; The PCMCIA Card; Appendix A: Glossary; Appendix B: IBM PC Bus Specifications; Appendix C: Review of the Intel 8255 PPI Chip; Appendix D: Review of the Intel 8254 Timer-Counter Chip; Appendix E: Thermocouple Tables; Appendix F: Numbers Systems; Appendix G: GPIB (IEEE-488) Mnemonics & their Definition; Appendix H: Practical Laboratories & Demonstrations; Appendix I: Command Structure & Programming.

Data Acquisition Techniques Using Personal Computers contains all the information required by a technical professional (engineer, scientist, technician) to implement a PC-based acquisition system. Including both basic tutorial information as well as some advanced topics, this work is suitable as a reference book for engineers or as a supplemental text for engineering students. It gives the reader enough understanding of the topics to implement a data acquisition system based on commercial products. A reader can alternatively learn how to custom build hardware or write his or her own software. Featuring diverse information, this book will be useful to both the technical professional and the hobbyist.

This book presents the theory and methodology of geographical data acquisition, providing comprehensive coverage ranging from the definition of geo-referencing systems and transformation between these systems to the acquisition of geographical data using different methods. The material provides readers with a good understanding of the nature of spatial data, the accuracy of spatial data, and the theory behind various data acquisition methodologies.

In this book readers will find technological discussions on the existing and emerging technologies across the different stages of the big data value chain. They will learn about legal aspects of big data, the social impact, and about education needs and requirements. And they will discover the business perspective and how big data technology can be exploited to deliver value within different sectors of the economy. The book is structured in four parts: Part I “The Big Data Opportunity” explores the value potential of big data with a particular focus on the European context. It also describes the legal, business and social dimensions that need to be addressed, and briefly introduces the European Commission’s BIG project. Part II “The Big Data Value Chain” details the complete big data lifecycle from a technical point of view, ranging from data acquisition, analysis, curation and storage, to data usage and exploitation. Next, Part III “Usage and Exploitation of Big Data” illustrates the value creation possibilities of big data applications in various sectors, including industry, healthcare, finance, energy, media and public services. Finally, Part IV “A Roadmap for Big Data Research” identifies and prioritizes the cross-sectorial requirements for big data research, and outlines the most urgent and challenging technological, economic, political and societal issues for big data in Europe. This compendium summarizes more than two years of work performed by a leading group of major European research centers and industries in the context of the BIG project. It brings together research findings, forecasts and estimates related to this challenging technological context that is becoming the major axis of the new digitally transformed business environment.

The practical, succinct LabVIEW data acquisition tutorial for every professional. No matter how much LabVIEW experience you have, this compact tutorial gives you core skills for producing virtually any data acquisition (DAQ) application-input and output. Designed for every engineer and scientist, LabVIEW for Data Acquisition begins with quick-start primers on both LabVIEW and DAQ, and builds your skills with extensive code examples and visual explanations drawn from Bruce Mihura's extensive experience teaching LabVIEW to professionals. Includes extensive coverage of DAQ-specific programming techniques Real-world techniques for maximizing accuracy and efficiency The 10 most common LabVIEW DAQ development problems-with specific solutions Addresses simulation, debugging, real-time issues, and network/distributed systems Preventing unauthorized changes to your LabVIEW code An overview of transducers for a wide variety of signals Non-NI alternatives for hardware and software LabVIEW for Data Acquisition includes an extensive collection of real-world LabVIEW applications, lists of LabVIEW tips and tricks, coverage of non-NI software and hardware alternatives, and much more. Whatever data acquisition application you need to create, this is the book to start and finish with. RELATED WEBSITE The accompanying website includes an evaluation version of LabVIEW and key LabVIEW code covered in the book.

Racecar data acquisition used to be limited to well-funded teams in high-profile championships. Today, the cost of electronics has decreased dramatically, making them available to everyone. But the cost of any data acquisition system is a waste of money if the recorded data is not interpreted correctly. This book, updated from the best-selling 2008 edition, contains techniques for analyzing data recorded by any vehicle's data acquisition system. It details how to measure the performance of the vehicle and driver, what can be learned from it, and how this information can be used to advantage next time the vehicle hits the track. Such information is invaluable to racing engineers and managers, race teams, and racing data analysts in all motorsports. Whether measuring the performance of a Formula One racecar or that of a road-legal street car on the local drag strip, the dynamics of vehicles and their drivers remain the same. Identical analysis techniques apply. Some race series have restricted data logging to decrease the team’s running budgets. In these cases it is extremely important that a maximum of information is extracted and interpreted from the hardware at hand. A team that uses data more efficiently will have an edge over the competition. However, the ever-decreasing cost of electronics makes advanced sensors and logging capabilities more accessible for everybody. With this comes the risk of information overload. Techniques are needed to help draw the right conclusions quickly from very large data sets. In addition to updates throughout, this new edition contains three new chapters: one on techniques for analyzing tire performance, one that provides an introduction to metric-driven analysis, a technique that is used throughout the book, and another that explains what kind of information the data contains about the track.