In this book, the authors focus on efficient ways to program instrumentation and automation systems using LabVIEW (TM), a system design platform and development environment commonly used for data acquisition, instrument control, and industrial automation on a variety of operating systems. Starting with the concepts of data flow and concurrent programming, the authors go on to address the development of state machines, event programming and consumer producer systems. Chapters cover the following topics: Introduction to LabVIEW (TM), debugging tools, structures, SubVIs, structures - LabVIEW (TM) features, organizing front panel and block diagram, using software resources, using hardware resources, implementing test machines with a basic architecture, controlling the user interface, error handling, responding to the user interactions, the ATM review project, communication between loops at different rates, preventing race conditions, advanced use of software resources, and real-time programming. This book helps undergraduate and graduate students learn how to identify the most suitable design patterns depending on the application, and how to implement them in conjunction with data acquisition and instrumentation control systems. It is also a helpful resource for engineers and scientists who want to implement binary files to record data, control the user interface and implement efficient ways of programming.

Sensor technologies play a large part in modern life, as they are present in things like security systems, digital cameras, smartphones, and motion sensors. While these devices are always evolving, research is being done to further develop this technology to help detect and analyze threats, perform in-depth inspections, and perform tracking services. Optoelectronics in Machine Vision-Based Theories and Applications provides innovative insights on theories and applications of optoelectronics in machine vision-based systems. It also covers topics such as applications of unmanned aerial vehicle, autonomous and mobile robots, medical scanning, industrial applications, agriculture, and structural health monitoring. This publication is a vital reference source for engineers, technology developers, academicians, researchers, and advanced-level students seeking emerging research on sensor technologies and machine vision.

As technology continues to develop, certain innovations are beginning to cover a wide range of applications, specifically mobile robotic systems. The boundaries between the various automation methods and their implementations are not strictly defined, with overlaps occurring. Specificity is required regarding the research and development of android systems and how they pertain to modern science. Control and Signal Processing Applications for Mobile and Aerial Robotic Systems is a pivotal reference source that provides vital research on the current state of control and signal processing of portable robotic designs. While highlighting topics such as digital systems, control theory, and mathematical methods, this publication explores original inquiry contributions and the instrumentation of mechanical systems in the industrial and scientific fields. This book is ideally designed for technicians, engineers, industry specialists, researchers, academicians, and students seeking current research on today's execution of mobile robotic schemes.

This book constitutes the refereed proceedings of the 17th Ibero-American Conference on Artificial Intelligence, IBERAMIA 2022, held in Cartagena de Indias, Colombia, in November 2022. The 33 full and 4 short papers presented were carefully reviewed and selected from 67 submissions. The papers are organized in the following topical sections: applications of AI; ethics and smart city; green and sustainable AI; machine learning; natural language processing; robotics and computer vision; simulation and forecasting.

A practical guide to getting the most out of Excel, using it for data preparation, applying machine learning models (including cloud services) and understanding the outcome of the data analysis. Key Features Use Microsoft's product Excel to build advanced forecasting models using varied examples Cover range of machine learning tasks such as data mining, data analytics, smart visualization, and more Derive data-driven techniques using Excel plugins and APIs without much code required Book DescriptionWe have made huge progress in teaching computers to perform difficult tasks, especially those that are repetitive and time-consuming for humans. Excel users, of all levels, can feel left behind by this innovation wave. The truth is that a large amount of the work needed to develop and use a machine learning model can be done in Excel. The book starts by giving a general introduction to machine learning, making every concept clear and understandable. Then, it shows every step of a machine learning project, from data collection, reading from different data sources, developing models, and visualizing the results using Excel features and offerings. In every chapter, there are several examples and hands-on exercises that will show the reader how to combine Excel functions, add-ins, and connections to databases and to cloud services to reach the desired goal: building a full data analysis flow. Different machine learning models are shown, tailored to the type of data to be analyzed. At the end of the book, the reader is presented with some advanced use cases using Automated Machine Learning, and artificial neural network, which simplifies the analysis task and represents the future of machine learning. What you will learn Use Excel to preview and cleanse datasets Understand correlations between variables and optimize the input to machine learning models Use and evaluate different machine learning models from Excel Understand the use of different visualizations Learn the basic concepts and calculations to understand how artificial neural networks work Learn how to connect Excel to the Microsoft Azure cloud Get beyond proof of concepts and build fully functional data analysis flows Who this book is forThis book is for data analysis, machine learning enthusiasts, project managers, and someone who doesn't want to code much for performing core tasks of machine learning. Each example will help you perform end-to-end smart analytics. Working knowledge of Excel is required.

As technology continues to develop, certain innovations are beginning to cover a wide range of applications, specifically mobile robotic systems. The boundaries between the various automation methods and their implementations are not strictly defined, with overlaps occurring. Specificity is required regarding the research and development of android systems and how they pertain to modern science. Control and Signal Processing Applications for Mobile and Aerial Robotic Systems is a pivotal reference source that provides vital research on the current state of control and signal processing of portable robotic designs. While highlighting topics such as digital systems, control theory, and mathematical methods, this publication explores original inquiry contributions and the instrumentation of mechanical systems in the industrial and scientific fields. This book is ideally designed for technicians, engineers, industry specialists, researchers, academicians, and students seeking current research on today's execution of mobile robotic schemes.

Sensor technologies play a large part in modern life, as they are present in things like security systems, digital cameras, smartphones, and motion sensors. While these devices are always evolving, research is being done to further develop this technology to help detect and analyze threats, perform in-depth inspections, and perform tracking services. Optoelectronics in Machine Vision-Based Theories and Applications provides innovative insights on theories and applications of optoelectronics in machine vision-based systems. It also covers topics such as applications of unmanned aerial vehicle, autonomous and mobile robots, medical scanning, industrial applications, agriculture, and structural health monitoring. This publication is a vital reference source for engineers, technology developers, academicians, researchers, and advanced-level students seeking emerging research on sensor technologies and machine vision.