Download or read book Activity Recognition and Prediction for Smart IoT Environments written by Michele Ianni and published by Springer Nature. This book was released on with total page 188 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book IoT Sensor Based Activity Recognition written by Md Atiqur Rahman Ahad and published by Springer Nature. This book was released on 2020-07-30 with total page 214 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offer clear descriptions of the basic structure for the recognition and classification of human activities using different types of sensor module and smart devices in e.g. healthcare, education, monitoring the elderly, daily human behavior, and fitness monitoring. In addition, the complexities, challenges, and design issues involved in data collection, processing, and other fundamental stages along with datasets, methods, etc., are discussed in detail. The book offers a valuable resource for readers in the fields of pattern recognition, human–computer interaction, and the Internet of Things.
Download or read book Activity Recognition in Pervasive Intelligent Environments written by Liming Chen and published by Springer Science & Business Media. This book was released on 2011-05-04 with total page 339 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book consists of a number of chapters addressing different aspects of activity recognition, roughly in three main categories of topics. The first topic will be focused on activity modeling, representation and reasoning using mathematical models, knowledge representation formalisms and AI techniques. The second topic will concentrate on activity recognition methods and algorithms. Apart from traditional methods based on data mining and machine learning, we are particularly interested in novel approaches, such as the ontology-based approach, that facilitate data integration, sharing and automatic/automated processing. In the third topic we intend to cover novel architectures and frameworks for activity recognition, which are scalable and applicable to large scale distributed dynamic environments. In addition, this topic will also include the underpinning technological infrastructure, i.e. tools and APIs, that supports function/capability sharing and reuse, and rapid development and deployment of technological solutions. The fourth category of topic will be dedicated to representative applications of activity recognition in intelligent environments, which address the life cycle of activity recognition and their use for novel functions of the end-user systems with comprehensive implementation, prototyping and evaluation. This will include a wide range of application scenarios, such as smart homes, intelligent conference venues and cars.
Download or read book Towards Integrative Machine Learning and Knowledge Extraction written by Andreas Holzinger and published by Springer. This book was released on 2017-10-27 with total page 220 pages. Available in PDF, EPUB and Kindle. Book excerpt: The BIRS Workshop “Advances in Interactive Knowledge Discovery and Data Mining in Complex and Big Data Sets” (15w2181), held in July 2015 in Banff, Canada, was dedicated to stimulating a cross-domain integrative machine-learning approach and appraisal of “hot topics” toward tackling the grand challenge of reaching a level of useful and useable computational intelligence with a focus on real-world problems, such as in the health domain. This encompasses learning from prior data, extracting and discovering knowledge, generalizing the results, fighting the curse of dimensionality, and ultimately disentangling the underlying explanatory factors in complex data, i.e., to make sense of data within the context of the application domain. The workshop aimed to contribute advancements in promising novel areas such as at the intersection of machine learning and topological data analysis. History has shown that most often the overlapping areas at intersections of seemingly disparate fields are key for the stimulation of new insights and further advances. This is particularly true for the extremely broad field of machine learning.
Download or read book Federated Learning for IoT Applications written by Satya Prakash Yadav and published by Springer Nature. This book was released on 2022-02-02 with total page 269 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents how federated learning helps to understand and learn from user activity in Internet of Things (IoT) applications while protecting user privacy. The authors first show how federated learning provides a unique way to build personalized models using data without intruding on users’ privacy. The authors then provide a comprehensive survey of state-of-the-art research on federated learning, giving the reader a general overview of the field. The book also investigates how a personalized federated learning framework is needed in cloud-edge architecture as well as in wireless-edge architecture for intelligent IoT applications. To cope with the heterogeneity issues in IoT environments, the book investigates emerging personalized federated learning methods that are able to mitigate the negative effects caused by heterogeneities in different aspects. The book provides case studies of IoT based human activity recognition to demonstrate the effectiveness of personalized federated learning for intelligent IoT applications, as well as multiple controller design and system analysis tools including model predictive control, linear matrix inequalities, optimal control, etc. This unique and complete co-design framework will benefit researchers, graduate students and engineers in the fields of control theory and engineering.
Download or read book Human Activity Recognition and Behaviour Analysis written by Liming Chen and published by Springer. This book was released on 2019-06-11 with total page 255 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book first defines the problems, various concepts and notions related to activity recognition, and introduces the fundamental rationale and state-of-the-art methodologies and approaches. It then describes the use of artificial intelligence techniques and advanced knowledge technologies for the modelling and lifecycle analysis of human activities and behaviours based on real-time sensing observations from sensor networks and the Internet of Things. It also covers inference and decision-support methods and mechanisms, as well as personalization and adaptation techniques, which are required for emerging smart human-machine pervasive systems, such as self-management and assistive technologies in smart healthcare. Each chapter includes theoretical background, technological underpinnings and practical implementation, and step-by-step information on how to address and solve specific problems in topical areas. This monograph can be used as a textbook for postgraduate and PhD students on courses such as computer systems, pervasive computing, data analytics and digital health. It is also a valuable research reference resource for postdoctoral candidates and academics in relevant research and application domains, such as data analytics, smart cities, smart energy, and smart healthcare, to name but a few. Moreover, it offers smart technology and application developers practical insights into the use of activity recognition and behaviour analysis in state-of-the-art cyber-physical systems. Lastly, it provides healthcare solution developers and providers with information about the opportunities and possible innovative solutions for personalized healthcare and stratified medicine.
Download or read book Human Activity Recognition and Prediction written by Yun Fu and published by Springer. This book was released on 2015-12-23 with total page 179 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a unique view of human activity recognition, especially fine-grained human activity structure learning, human-interaction recognition, RGB-D data based action recognition, temporal decomposition, and causality learning in unconstrained human activity videos. The techniques discussed give readers tools that provide a significant improvement over existing methodologies of video content understanding by taking advantage of activity recognition. It links multiple popular research fields in computer vision, machine learning, human-centered computing, human-computer interaction, image classification, and pattern recognition. In addition, the book includes several key chapters covering multiple emerging topics in the field. Contributed by top experts and practitioners, the chapters present key topics from different angles and blend both methodology and application, composing a solid overview of the human activity recognition techniques.
Download or read book Cross domain Scalable Activity Recognition Models in Smart Environments written by Md Abdullah Al Hafiz Khan and published by . This book was released on 2019 with total page 416 pages. Available in PDF, EPUB and Kindle. Book excerpt: The success of Activity Recognition (AR) methodology largely depends on the availability of labeled training samples and adaptability of activity recognition models in cross-domains such as diverse users, heterogeneous devices, and different smart environments. The availability of new era of Internet-of-Things (IoT) devices ranging from smartphones, smartwatches, micro-radars, Amazon Echo in users everyday environments ease the recognition of human activities, behaviors, and occupancy. Nevertheless, the variabilities across emerging sensors, heterogeneities in consumer devices, and inherent variations in users' activities hinder the design and development of scalable activity recognition models. Motivated by this, in this thesis, we investigate the problem of making human activity recognition scalable-i.e., allowing AR classifiers trained in one context to be readily adapted to a different contextual domain. To allow such adaptation without requiring the onerous step of collecting large volumes of labeled training data, we proposed a transfer learning model that is specifically tuned to the properties of convolutional neural networks (CNNs). We designed different variants of this Heterogeneous Deep Convolutional Neural Network (HDCNN) model that help to automatically adapt and learn the model across different domains, such as different users, device-types, device-instances in presence of completely or partially alike activities in source and target. We also extended the above cross-domain activity recognition models to learn the unseen activities using the deep features transfer learning technique while aggregating the domain knowledge from both the source and target domains. Evaluation on real world datasets attested that our proposed cross-domain activity recognition models are able to achieve high accuracy even without any labeled training data in the target domain, and often offer higher accuracy (compared to shallow and deep classifiers) even with a modest amount of labeled training data.
Download or read book Human Activity Sensing written by Nobuo Kawaguchi and published by Springer Nature. This book was released on 2019-09-09 with total page 250 pages. Available in PDF, EPUB and Kindle. Book excerpt: Activity recognition has emerged as a challenging and high-impact research field, as over the past years smaller and more powerful sensors have been introduced in wide-spread consumer devices. Validation of techniques and algorithms requires large-scale human activity corpuses and improved methods to recognize activities and the contexts in which they occur. This book deals with the challenges of designing valid and reproducible experiments, running large-scale dataset collection campaigns, designing activity and context recognition methods that are robust and adaptive, and evaluating activity recognition systems in the real world with real users.
Download or read book 6G Enabled IoT and AI for Smart Healthcare written by Ashish Kumar and published by CRC Press. This book was released on 2023-06-21 with total page 331 pages. Available in PDF, EPUB and Kindle. Book excerpt: In today’s era, there is a need for a system that can automate the process of treatment for the patient if medical facilities are out of reach. Smart healthcare can step in to make the patient more self-dependent. 6G with its features can be seen as the future of smart healthcare with IoT and AI. 6G-Enabled IoT and AI for Smart Healthcare: Challenges, Impact, and Analysis offers the fundamentals, history, reality, and challenges faced in the smart healthcare industry today. It discusses the concepts, tools, and techniques of smart healthcare as well as the analysis used. The book details the role that machine learning-based deep learning and 6G-enabled IoT concepts play in the automation of smart healthcare systems. The book goes on to presents applications of smart healthcare through various real-world examples and includes chapters on security and privacy in the 6G-enabled and IoT environment, as well as research on the future prospects of the smart healthcare industry. This book: Offers the fundamentals, history, reality, and the challenges faced in the smart healthcare industry Discusses the concepts, tools, and techniques of smart healthcare as well as the analysis used Details the role that machine learning-based deep learning and 6G-enabled IoT concepts play in the automation of smart healthcare systems Presents applications of smart healthcare through various real-world examples Includes topics on security and privacy in 6G-enabled IoT, as well as research and future prospectus of the smart healthcare industry Interested readers of this book will include anyone working in or involved in smart healthcare research which includes, but is not limited to healthcare specialists, computer science engineers, electronics engineers, systems engineers, and pharmaceutical practitioners.
Download or read book Activity Recognition in Complex Smart Environment Settings written by Geetika Singla and published by . This book was released on 2009 with total page 110 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book A Fusion of Artificial Intelligence and Internet of Things for Emerging Cyber Systems written by Pardeep Kumar and published by Springer Nature. This book was released on 2021-08-23 with total page 462 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book aims at offering a unique collection of ideas and experiences mainly focusing on the main streams and merger of Artificial Intelligence (AI) and the Internet of Things (IoT) for a wide slice of the communication and networking community. In the era when the world is grappling with many unforeseen challenges, scientists and researchers are envisioning smart cyber systems that guarantee sustainable development for a better human life. The main contributors that destined to play a huge role in developing such systems, among others, are AI and IoT. While AI provides intelligence to machines and data by identifying patterns, developing predictions, and detecting anomalies, IoT performs as a nerve system by connecting a huge number of machines and capturing an enormous amount of data. AI-enabled IoT, therefore, redefines the way industries, businesses, and economies function with increased automation and efficiency and reduced human interaction and costs. This book is an attempt to publish innovative ideas, emerging trends, implementation experience, and use-cases pertaining to the merger of AI and IoT. The primary market of this book is centered around students, researchers, academicians, industrialists, entrepreneurs, and professionals working in electrical/computer engineering, IT, telecom/electronic engineering, and related fields. The secondary market of this book is related to individuals working in the fields such as finance, management, mathematics, physics, environment, mechatronics, and the automation industry.
Download or read book Decision Making and Security Risk Management for IoT Environments written by Wadii Boulila and published by Springer Nature. This book was released on with total page 231 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Recent Trends in Computational Intelligence Enabled Research written by Siddhartha Bhattacharyya and published by Academic Press. This book was released on 2021-07-31 with total page 420 pages. Available in PDF, EPUB and Kindle. Book excerpt: The field of computational intelligence has grown tremendously over that past five years, thanks to evolving soft computing and artificial intelligent methodologies, tools and techniques for envisaging the essence of intelligence embedded in real life observations. Consequently, scientists have been able to explain and understand real life processes and practices which previously often remain unexplored by virtue of their underlying imprecision, uncertainties and redundancies, and the unavailability of appropriate methods for describing the incompleteness and vagueness of information represented. With the advent of the field of computational intelligence, researchers are now able to explore and unearth the intelligence, otherwise insurmountable, embedded in the systems under consideration. Computational Intelligence is now not limited to only specific computational fields, it has made inroads in signal processing, smart manufacturing, predictive control, robot navigation, smart cities, and sensor design to name a few. Recent Trends in Computational Intelligence Enabled Research: Theoretical Foundations and Applications explores the use of this computational paradigm across a wide range of applied domains which handle meaningful information. Chapters investigate a broad spectrum of the applications of computational intelligence across different platforms and disciplines, expanding our knowledge base of various research initiatives in this direction. This volume aims to bring together researchers, engineers, developers and practitioners from academia and industry working in all major areas and interdisciplinary areas of computational intelligence, communication systems, computer networks, and soft computing. Provides insights into the theory, algorithms, implementation, and application of computational intelligence techniques Covers a wide range of applications of deep learning across various domains which are researching the applications of computational intelligence Investigates novel techniques and reviews the state-of-the-art in the areas of machine learning, computer vision, soft computing techniques
Download or read book Cutting Edge Applications of Computational Intelligence Tools and Techniques written by Kevin Daimi and published by Springer Nature. This book was released on 2023-11-30 with total page 355 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book delivers an excellent professional development resource for educators and practitioners on the cutting-edge computational intelligence techniques and applications. It covers many areas and topics of computational intelligence techniques and applications proposed by computational intelligence experts and researchers and furthers the enhancement of the community outreach and engagement component of computational intelligence techniques and applications. Furthermore, it presents a rich collection of manuscripts in highly regarded computational intelligence techniques and applications topics that have been creatively compiled. Computers are capable of learning from data and observations and providing solutions to real-life complex problems, following the same reasoning approach of human experts in various fields. This book endows a rich collection of applications in widespread areas. Among the areas addressed in this book are Computational Intelligence Principles and Techniques; CI in Manufacturing, Engineering, and Industry; CI in Recognition and Processing; CI in Robotics and Automation; CI in Communications and Networking; CI in Traditional Vehicles, Electric Vehicles, and Autonomous Vehicles; CI in Smart Cities and Smart Energy Systems; and CI in Finance, Business, Economics, and Education. These areas span many topics including repetitive manufacturing, discrete manufacturing, process manufacturing, electronic systems, speech recognition, pattern recognition, signal processing, image processing, industrial monitoring, vision systems for automation and robotics, cooperative and network robotics, perception, planning, control, urban traffic networks control, vehicle-to-roadside communications, smart buildings, smart urbanism, smart infrastructure, smart connected communities, smart energy, security, arts, and music.
Download or read book Advanced Approaches Business Models and Novel Techniques for Management and Control of Smart Grids written by Pierluigi Siano and published by MDPI. This book was released on 2020-12-29 with total page 210 pages. Available in PDF, EPUB and Kindle. Book excerpt: The current power system should be renovated to fulfill social and industrial requests and economic advances. Hence, providing economic, green, and sustainable energy are key goals of advanced societies. In order to meet these goals, recent features of smart grid technologies need to have the potential to improve reliability, flexibility, efficiency, and resiliency. This book aims to address the mentioned challenges by introducing advanced approaches, business models, and novel techniques for the management and control of future smart grids.
Download or read book Smart Environments written by Diane Cook and published by John Wiley & Sons. This book was released on 2004-10-28 with total page 424 pages. Available in PDF, EPUB and Kindle. Book excerpt: Smart Environments contains contributions from leading researchers, describing techniques and issues related to developing and living in intelligent environments. Reflecting the multidisciplinary nature of the design of smart environments, the topics covered include the latest research in smart environment philosophical and computational architecture considerations, network protocols for smart environments, intelligent sensor networks and powerline control of devices, and action prediction and identification.
