Download or read book IoT Streams for Data Driven Predictive Maintenance and IoT Edge and Mobile for Embedded Machine Learning written by Joao Gama and published by Springer Nature. This book was released on 2021-01-09 with total page 317 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes selected papers from the Second International Workshop on IoT Streams for Data-Driven Predictive Maintenance, IoT Streams 2020, and First International Workshop on IoT, Edge, and Mobile for Embedded Machine Learning, ITEM 2020, co-located with ECML/PKDD 2020 and held in September 2020. Due to the COVID-19 pandemic the workshops were held online. The 21 full papers and 3 short papers presented in this volume were thoroughly reviewed and selected from 35 submissions and are organized according to the workshops and their topics: IoT Streams 2020: Stream Learning; Feature Learning; ITEM 2020: Unsupervised Machine Learning; Hardware; Methods; Quantization.

Download or read book Predictive Analytics with Microsoft Azure Machine Learning written by Valentine Fontama and published by Apress. This book was released on 2014-11-25 with total page 178 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Science and Machine Learning are in high demand, as customers are increasingly looking for ways to glean insights from all their data. More customers now realize that Business Intelligence is not enough as the volume, speed and complexity of data now defy traditional analytics tools. While Business Intelligence addresses descriptive and diagnostic analysis, Data Science unlocks new opportunities through predictive and prescriptive analysis. The purpose of this book is to provide a gentle and instructionally organized introduction to the field of data science and machine learning, with a focus on building and deploying predictive models. The book also provides a thorough overview of the Microsoft Azure Machine Learning service using task oriented descriptions and concrete end-to-end examples, sufficient to ensure the reader can immediately begin using this important new service. It describes all aspects of the service from data ingress to applying machine learning and evaluating the resulting model, to deploying the resulting model as a machine learning web service. Finally, this book attempts to have minimal dependencies, so that you can fairly easily pick and choose chapters to read. When dependencies do exist, they are listed at the start and end of the chapter. The simplicity of this new service from Microsoft will help to take Data Science and Machine Learning to a much broader audience than existing products in this space. Learn how you can quickly build and deploy sophisticated predictive models as machine learning web services with the new Azure Machine Learning service from Microsoft.

Download or read book An Introduction to Predictive Maintenance written by R. Keith Mobley and published by Elsevier. This book was released on 2002-10-24 with total page 451 pages. Available in PDF, EPUB and Kindle. Book excerpt: This second edition of An Introduction to Predictive Maintenance helps plant, process, maintenance and reliability managers and engineers to develop and implement a comprehensive maintenance management program, providing proven strategies for regularly monitoring critical process equipment and systems, predicting machine failures, and scheduling maintenance accordingly. Since the publication of the first edition in 1990, there have been many changes in both technology and methodology, including financial implications, the role of a maintenance organization, predictive maintenance techniques, various analyses, and maintenance of the program itself. This revision includes a complete update of the applicable chapters from the first edition as well as six additional chapters outlining the most recent information available. Having already been implemented and maintained successfully in hundreds of manufacturing and process plants worldwide, the practices detailed in this second edition of An Introduction to Predictive Maintenance will save plants and corporations, as well as U.S. industry as a whole, billions of dollars by minimizing unexpected equipment failures and its resultant high maintenance cost while increasing productivity. - A comprehensive introduction to a system of monitoring critical industrial equipment - Optimize the availability of process machinery and greatly reduce the cost of maintenance - Provides the means to improve product quality, productivity and profitability of manufacturing and production plants

Download or read book Fundamentals of Machine Learning for Predictive Data Analytics second edition written by John D. Kelleher and published by MIT Press. This book was released on 2020-10-20 with total page 853 pages. Available in PDF, EPUB and Kindle. Book excerpt: The second edition of a comprehensive introduction to machine learning approaches used in predictive data analytics, covering both theory and practice. Machine learning is often used to build predictive models by extracting patterns from large datasets. These models are used in predictive data analytics applications including price prediction, risk assessment, predicting customer behavior, and document classification. This introductory textbook offers a detailed and focused treatment of the most important machine learning approaches used in predictive data analytics, covering both theoretical concepts and practical applications. Technical and mathematical material is augmented with explanatory worked examples, and case studies illustrate the application of these models in the broader business context. This second edition covers recent developments in machine learning, especially in a new chapter on deep learning, and two new chapters that go beyond predictive analytics to cover unsupervised learning and reinforcement learning.

Download or read book Predictive Maintenance in Dynamic Systems written by Edwin Lughofer and published by Springer. This book was released on 2019-02-28 with total page 564 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a complete picture of several decision support tools for predictive maintenance. These include embedding early anomaly/fault detection, diagnosis and reasoning, remaining useful life prediction (fault prognostics), quality prediction and self-reaction, as well as optimization, control and self-healing techniques. It shows recent applications of these techniques within various types of industrial (production/utilities/equipment/plants/smart devices, etc.) systems addressing several challenges in Industry 4.0 and different tasks dealing with Big Data Streams, Internet of Things, specific infrastructures and tools, high system dynamics and non-stationary environments . Applications discussed include production and manufacturing systems, renewable energy production and management, maritime systems, power plants and turbines, conditioning systems, compressor valves, induction motors, flight simulators, railway infrastructures, mobile robots, cyber security and Internet of Things. The contributors go beyond state of the art by placing a specific focus on dynamic systems, where it is of utmost importance to update system and maintenance models on the fly to maintain their predictive power.

Download or read book Machine Learning for Cyber Physical Systems written by Jürgen Beyerer and published by Springer. This book was released on 2018-12-17 with total page 144 pages. Available in PDF, EPUB and Kindle. Book excerpt: This Open Access proceedings presents new approaches to Machine Learning for Cyber Physical Systems, experiences and visions. It contains some selected papers from the international Conference ML4CPS – Machine Learning for Cyber Physical Systems, which was held in Karlsruhe, October 23-24, 2018. Cyber Physical Systems are characterized by their ability to adapt and to learn: They analyze their environment and, based on observations, they learn patterns, correlations and predictive models. Typical applications are condition monitoring, predictive maintenance, image processing and diagnosis. Machine Learning is the key technology for these developments.

Download or read book 2019 IEEE 5th World Forum on Internet of Things WF IoT written by IEEE Staff and published by . This book was released on 2019-04-15 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The 2019 IEEE 5th World Forum on Internet of Things (WF IoT 2019) is the premier conference for the IEEE IoT Initiative and consists of the most outstanding participants from the research community, the public sector, and industry The theme of the Conference is IoT and the Digital Revolution in recognition of strides and leadership that the host location of Limerick and Ireland has made in the deployment of smart technologies, operating principles, and policies The theme also underscores the importance of IoT technologies in bringing about the digital revolution and making it a reality The papers, presentations, and events at the conference are focused on contributions to nurture, cultivate, enhance and accelerate the adoption of IoT technologies and applications for the benefit of society In the past year the Internet of Things has experienced significant growth in the number of deployments, in the resource investment from both industry and governments, and in attention from t

Download or read book Knowledge Management in Organizations written by Lorna Uden and published by Springer. This book was released on 2018-07-30 with total page 732 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains the refereed proceedings of the 13th International Conference on Knowledge Management in Organizations, KMO 2018, held in Žilina, Slovakia, in August 2018. The theme of the conference was "Emerging Research for Knowledge Management in Organizations." The 59 papers accepted for KMO 2018 were selected from 141 submissions and are organized in topical sections on: Knowledge management models and analysis; knowledge sharing; knowledge transfer and learning; knowledge and service innovation; knowledge creation; knowledge and organization; information systems and information science; knowledge and technology management; data mining and intelligent science; business and customer relationship management; big data and IoT; and new trends in IT.

Download or read book Advances in Production Management Systems Smart Manufacturing for Industry 4 0 written by Ilkyeong Moon and published by Springer. This book was released on 2018-08-24 with total page 518 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two-volume set IFIP AICT 535 and 536 constitutes the refereed proceedings of the International IFIP WG 5.7 Conference on Advances in Production Management Systems, APMS 2018, held in Seoul, South Korea, in August 2018. The 129 revised full papers presented were carefully reviewed and selected from 149 submissions. They are organized in the following topical sections: lean and green manufacturing; operations management in engineer-to-order manufacturing; product-service systems, customer-driven innovation and value co-creation; collaborative networks; smart production for mass customization; global supply chain management; knowledge based production planning and control; knowledge based engineering; intelligent diagnostics and maintenance solutions for smart manufacturing; service engineering based on smart manufacturing capabilities; smart city interoperability and cross-platform implementation; manufacturing performance management in smart factories; industry 4.0 - digital twin; industry 4.0 - smart factory; and industry 4.0 - collaborative cyber-physical production and human systems.

Download or read book Advanced Manufacturing and Automation VII written by Kesheng Wang and published by Springer. This book was released on 2018-02-10 with total page 627 pages. Available in PDF, EPUB and Kindle. Book excerpt: The proceedings brings together a selection of papers from the 7th International Workshop of Advanced Manufacturing and Automation (IWAMA 2017), held in Changshu Institute of Technology, Changshu, China on September 11–12, 2017. Most of the topics are focusing on novel techniques for manufacturing and automation in Industry 4.0. These contributions are vital for maintaining and improving economic development and quality of life. The proceeding will assist academic researchers and industrial engineers to implement the concepts and theories of Industry 4.0 in industrial practice, in order to effectively respond to the challenges posed by the 4th industrial revolution and smart factories.

Download or read book Machine Learning and Data Science in the Oil and Gas Industry written by Patrick Bangert and published by Gulf Professional Publishing. This book was released on 2021-03-04 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine Learning and Data Science in the Oil and Gas Industry explains how machine learning can be specifically tailored to oil and gas use cases. Petroleum engineers will learn when to use machine learning, how it is already used in oil and gas operations, and how to manage the data stream moving forward. Practical in its approach, the book explains all aspects of a data science or machine learning project, including the managerial parts of it that are so often the cause for failure. Several real-life case studies round out the book with topics such as predictive maintenance, soft sensing, and forecasting. Viewed as a guide book, this manual will lead a practitioner through the journey of a data science project in the oil and gas industry circumventing the pitfalls and articulating the business value. - Chart an overview of the techniques and tools of machine learning including all the non-technological aspects necessary to be successful - Gain practical understanding of machine learning used in oil and gas operations through contributed case studies - Learn change management skills that will help gain confidence in pursuing the technology - Understand the workflow of a full-scale project and where machine learning benefits (and where it does not)

Download or read book Advances in Machine Learning Applications in Software Engineering written by Zhang, Du and published by IGI Global. This book was released on 2006-10-31 with total page 498 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book provides analysis, characterization and refinement of software engineering data in terms of machine learning methods. It depicts applications of several machine learning approaches in software systems development and deployment, and the use of machine learning methods to establish predictive models for software quality while offering readers suggestions by proposing future work in this emerging research field"--Provided by publisher.

Download or read book Congress on Intelligent Systems written by Harish Sharma and published by Springer. This book was released on 2021-05-28 with total page 815 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a collection of selected papers presented at the First Congress on Intelligent Systems (CIS 2020), held in New Delhi, India during September 5 – 6, 2020. It includes novel and innovative work from experts, practitioners, scientists and decision-makers from academia and industry. It covers topics such as Internet of Things, information security, embedded systems, real-time systems, cloud computing, big data analysis, quantum computing, automation systems, bio-inspired intelligence, cognitive systems, cyber physical systems, data analytics, data/web mining, data science, intelligence for security, intelligent decision making systems, intelligent information processing, intelligent transportation, artificial intelligence for machine vision, imaging sensors technology, image segmentation, convolutional neural network, image/video classification, soft computing for machine vision, pattern recognition, human computer interaction, robotic devices and systems, autonomous vehicles, intelligent control systems, human motor control, game playing, evolutionary algorithms, swarm optimization, neural network, deep learning, supervised learning, unsupervised learning, fuzzy logic, rough sets, computational optimization, and neuro fuzzy systems.

Download or read book Industry 4 1 written by Fan-Tien Cheng and published by John Wiley & Sons. This book was released on 2021-10-26 with total page 562 pages. Available in PDF, EPUB and Kindle. Book excerpt: Industry 4.1 Intelligent Manufacturing with Zero Defects Discover the future of manufacturing with this comprehensive introduction to Industry 4.0 technologies from a celebrated expert in the field Industry 4.1: Intelligent Manufacturing with Zero Defects delivers an in-depth exploration of the functions of intelligent manufacturing and its applications and implementations through the Intelligent Factory Automation (iFA) System Platform. The book’s distinguished editor offers readers a broad range of resources that educate and enlighten on topics as diverse as the Internet of Things, edge computing, cloud computing, and cyber-physical systems. You’ll learn about three different advanced prediction technologies: Automatic Virtual Metrology (AVM), Intelligent Yield Management (IYM), and Intelligent Predictive Maintenance (IPM). Different use cases in a variety of manufacturing industries are covered, including both high-tech and traditional areas. In addition to providing a broad view of intelligent manufacturing and covering fundamental technologies like sensors, communication standards, and container technologies, the book offers access to experimental data through the IEEE DataPort. Finally, it shows readers how to build an intelligent manufacturing platform called an Advanced Manufacturing Cloud of Things (AMCoT). Readers will also learn from: An introduction to the evolution of automation and development strategy of intelligent manufacturing A comprehensive discussion of foundational concepts in sensors, communication standards, and container technologies An exploration of the applications of the Internet of Things, edge computing, and cloud computing The Intelligent Factory Automation (iFA) System Platform and its applications and implementations A variety of use cases of intelligent manufacturing, from industries like flat-panel, semiconductor, solar cell, automotive, aerospace, chemical, and blow molding machine Perfect for researchers, engineers, scientists, professionals, and students who are interested in the ongoing evolution of Industry 4.0 and beyond, Industry 4.1: Intelligent Manufacturing with Zero Defects will also win a place in the library of laypersons interested in intelligent manufacturing applications and concepts. Completely unique, this book shows readers how Industry 4.0 technologies can be applied to achieve the goal of Zero Defects for all product

Download or read book Machine Learning with SAP written by Laboni Bhowmik and published by SAP PRESS. This book was released on 2020 with total page 550 pages. Available in PDF, EPUB and Kindle. Book excerpt: Work smarter with machine learning! Begin with core machine learning concepts--types of learning, algorithms, data preparation, and more. Then use SAP Data Intelligence, SAP HANA, and other technologies to create your own machine learning applications. Master the SAP HANA Predictive Analysis Library (PAL) and machine learning functional and business services to train and deploy models. Finally, see machine learning in action in industries from manufacturing to banking. a. Foundation Build your understanding of probability concepts and algorithms that drive machine learning. See how linear regression, classification, and cluster analysis algorithms work, before plugging them into your very own machine learning app! b. Development Follow step-by-step instructions to gather and prepare data, create machine learning models, train and fine-tune models, and deploy your final app, all using SAP HANA and SAP Data Intelligence. c. Platforms Use built-in SAP HANA libraries to create applications that consume machine learning algorithms or integrate with the R language for additional statistical capabilities. Work with the SAP Leonardo functional services to customize and embed pre-trained models into applications or bring your own model with the help of Google TensorFlow. 1) Development 2) Retraining 3) Implementation 4) SAP Data Intelligence 5) SAP HANA predictive analysis library 6) SAP HANA extended machine learning library 7) SAP HANA automated predictive library 8) Google TensorFlow 9) Embedded machine learning 10) SAP Conversational AI 11) SAP Analytics Cloud Smart Predict

Download or read book Predictive Maintenance for HVAC Systems Leveraging Machine Learning for Optimal Performance written by Charles Nehme and published by Charles Nehme. This book was released on with total page 80 pages. Available in PDF, EPUB and Kindle. Book excerpt: The world of heating, ventilation, and air conditioning (HVAC) systems has long been vital to ensuring comfort in residential, commercial, and industrial environments. However, as these systems grow in complexity and scale, so too does the challenge of maintaining them efficiently. Traditionally, HVAC systems have relied on reactive or time-based maintenance strategies that often result in unnecessary downtime, increased operational costs, and inefficient energy use. In an age where sustainability and cost-effectiveness are paramount, businesses and organizations are seeking smarter solutions. This is where machine learning (ML) enters the scene. Machine learning has revolutionized industries across the globe, from healthcare to finance. Its ability to analyze vast amounts of data and predict outcomes with precision offers HVAC systems the potential to leap from reactive maintenance strategies to predictive ones. Imagine a world where HVAC systems can detect a malfunction before it occurs, optimize their own performance, and ensure energy efficiency with minimal human intervention. This is the promise of predictive maintenance powered by machine learning. The goal of this book is to bridge the gap between two seemingly distinct worlds—HVAC maintenance and machine learning. By providing an in-depth exploration of how predictive models can be applied to HVAC systems, this book is designed for engineers, data scientists, HVAC professionals, and facility managers alike. Whether you're an experienced machine learning practitioner looking to understand the specific needs of HVAC systems, or an HVAC professional eager to learn how AI can revolutionize maintenance strategies, this book provides a roadmap for implementing predictive maintenance in real-world environments. In writing this book, I’ve drawn from a wide array of sources: industry best practices, academic research, and hands-on case studies of machine learning models applied in HVAC settings. You will learn not only the technical foundations of machine learning but also how to gather, clean, and preprocess HVAC data for predictive modeling, select appropriate algorithms, and deploy models in live systems. The book aims to demystify the technical aspects of predictive maintenance and show how it can be implemented at scale. With practical examples, industry use cases, and step-by-step guides, you’ll gain a deep understanding of the processes involved in transforming your HVAC maintenance strategy from reactive to predictive. As we venture into the era of smart buildings, energy efficiency, and self-optimizing systems, the integration of machine learning with HVAC systems will no longer be a luxury—it will be a necessity. By the end of this book, you’ll be equipped with the knowledge and tools to lead the charge in this transformation. Thank you for joining me on this journey into the future of HVAC maintenance. I hope this book empowers you to harness the potential of machine learning and usher in a new era of efficiency, reliability, and sustainability in HVAC systems.

Download or read book 2021 Third International Conference on Transportation and Smart Technologies TST written by IEEE Staff and published by . This book was released on 2021-05-27 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: TST 21 conference is a forum where researchers will discuss around scientific papers on computer science and their applications, especially in the transportation domain