Download or read book Smartphone Based Human Activity Recognition written by Jorge Luis Reyes Ortiz and published by Springer. This book was released on 2015-01-14 with total page 147 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book reports on the author’s original work to address the use of today’s state-of-the-art smartphones for human physical activity recognition. By exploiting the sensing, computing and communication capabilities currently available in these devices, the author developed a novel smartphone-based activity-recognition system, which takes into consideration all aspects of online human activity recognition, from experimental data collection, to machine learning algorithms and hardware implementation. The book also discusses and describes solutions to some of the challenges that arose during the development of this approach, such as real-time operation, high accuracy, low battery consumption and unobtrusiveness. It clearly shows that it is possible to perform real-time recognition of activities with high accuracy using current smartphone technologies. As well as a detailed description of the methods, this book also provides readers with a comprehensive review of the fundamental concepts in human activity recognition. It also gives an accurate analysis of the most influential works in the field and discusses them in detail. This thesis was supervised by both the Universitat Politècnica de Catalunya (primary institution) and University of Genoa (secondary institution) as part of the Erasmus Mundus Joint Doctorate in Interactive and Cognitive Environments.

Download or read book Human Activity Recognition written by Miguel A. Labrador and published by CRC Press. This book was released on 2013-12-05 with total page 206 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn How to Design and Implement HAR Systems The pervasiveness and range of capabilities of today's mobile devices have enabled a wide spectrum of mobile applications that are transforming our daily lives, from smartphones equipped with GPS to integrated mobile sensors that acquire physiological data. Human Activity Recognition: Using Wearable Sen

Download or read book Artificial Neural Networks and Machine Learning ICANN 2014 written by Stefan Wermter and published by Springer. This book was released on 2014-08-18 with total page 874 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book constitutes the proceedings of the 24th International Conference on Artificial Neural Networks, ICANN 2014, held in Hamburg, Germany, in September 2014. The 107 papers included in the proceedings were carefully reviewed and selected from 173 submissions. The focus of the papers is on following topics: recurrent networks; competitive learning and self-organisation; clustering and classification; trees and graphs; human-machine interaction; deep networks; theory; reinforcement learning and action; vision; supervised learning; dynamical models and time series; neuroscience; and applications.

Download or read book Human Activity Recognition written by Miguel A. Labrador and published by CRC Press. This book was released on 2013-12-05 with total page 209 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn How to Design and Implement HAR Systems The pervasiveness and range of capabilities of today’s mobile devices have enabled a wide spectrum of mobile applications that are transforming our daily lives, from smartphones equipped with GPS to integrated mobile sensors that acquire physiological data. Human Activity Recognition: Using Wearable Sensors and Smartphones focuses on the automatic identification of human activities from pervasive wearable sensors—a crucial component for health monitoring and also applicable to other areas, such as entertainment and tactical operations. Developed from the authors’ nearly four years of rigorous research in the field, the book covers the theory, fundamentals, and applications of human activity recognition (HAR). The authors examine how machine learning and pattern recognition tools help determine a user’s activity during a certain period of time. They propose two systems for performing HAR: Centinela, an offline server-oriented HAR system, and Vigilante, a completely mobile real-time activity recognition system. The book also provides a practical guide to the development of activity recognition applications in the Android framework.

Download or read book Applications of Artificial Intelligence and Machine Learning written by Ankur Choudhary and published by Springer Nature. This book was released on 2021-07-27 with total page 738 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book presents a collection of peer-reviewed articles from the International Conference on Advances and Applications of Artificial Intelligence and Machine Learning - ICAAAIML 2020. The book covers research in artificial intelligence, machine learning, and deep learning applications in healthcare, agriculture, business, and security. This volume contains research papers from academicians, researchers as well as students. There are also papers on core concepts of computer networks, intelligent system design and deployment, real-time systems, wireless sensor networks, sensors and sensor nodes, software engineering, and image processing. This book will be a valuable resource for students, academics, and practitioners in the industry working on AI applications.

Download or read book Distributed Computing Artificial Intelligence Bioinformatics Soft Computing and Ambient Assisted Living written by Sigeru Omatu and published by Springer Science & Business Media. This book was released on 2009-06-08 with total page 1353 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 10th International Work-Conference on Artificial Neural Networks, IWANN 2009, held in Salamanca, Spain in June 2009. The 167 revised full papers presented together with 3 invited lectures were carefully reviewed and selected from over 230 submissions. The papers are organized in thematic sections on theoretical foundations and models; learning and adaptation; self-organizing networks, methods and applications; fuzzy systems; evolutionary computation and genetic algoritms; pattern recognition; formal languages in linguistics; agents and multi-agent on intelligent systems; brain-computer interfaces (bci); multiobjetive optimization; robotics; bioinformatics; biomedical applications; ambient assisted living (aal) and ambient intelligence (ai); other applications.

Download or read book Handbook of Computational Intelligence in Biomedical Engineering and Healthcare written by Janmenjoy Nayak and published by Academic Press. This book was released on 2021-04-08 with total page 398 pages. Available in PDF, EPUB and Kindle. Book excerpt: Handbook of Computational Intelligence in Biomedical Engineering and Healthcare helps readers analyze and conduct advanced research in specialty healthcare applications surrounding oncology, genomics and genetic data, ontologies construction, bio-memetic systems, biomedical electronics, protein structure prediction, and biomedical data analysis. The book provides the reader with a comprehensive guide to advanced computational intelligence, spanning deep learning, fuzzy logic, connectionist systems, evolutionary computation, cellular automata, self-organizing systems, soft computing, and hybrid intelligent systems in biomedical and healthcare applications. Sections focus on important biomedical engineering applications, including biosensors, enzyme immobilization techniques, immuno-assays, and nanomaterials for biosensors and other biomedical techniques. Other sections cover gene-based solutions and applications through computational intelligence techniques and the impact of nonlinear/unstructured data on experimental analysis. - Presents a comprehensive handbook that covers an Introduction to Computational Intelligence in Biomedical Engineering and Healthcare, Computational Intelligence Techniques, and Advanced and Emerging Techniques in Computational Intelligence - Helps readers analyze and do advanced research in specialty healthcare applications - Includes links to websites, videos, articles and other online content to expand and support primary learning objectives

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 Hybrid Artificial Intelligent Systems written by Emilio Corchado and published by Springer Science & Business Media. This book was released on 2011-05-16 with total page 499 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two LNAI volumes 6678 and 6679 constitute the proceedings of the 6th International Conference on Hybrid Artificial Intelligent Systems, HAIS 2011, held in Wroclaw, Poland, in May 2011. The 114 papers published in these proceedings were carefully reviewed and selected from 241 submissions. They are organized in topical sessions on hybrid intelligence systems on logistics and intelligent optimization; metaheuristics for combinatorial optimization and modelling complex systems; hybrid systems for context-based information fusion; methods of classifier fusion; intelligent systems for data mining and applications; systems, man, and cybernetics; hybrid artificial intelligence systems in management of production systems; habrid artificial intelligent systems for medical applications; and hybrid intelligent approaches in cooperative multi-robot systems.

Download or read book AI IA 2017 Advances in Artificial Intelligence written by Floriana Esposito and published by Springer. This book was released on 2017-11-03 with total page 519 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 16th International Conference of the Italian Association for Artificial Intelligence, AI*IA 2017, held in Bari, Italy, in November 2017. The 37 full papers presented were carefully reviewed and selected from 91 submissions. The papers are organized in topical sections on applications of AI; natural language processing; knowledge representation and reasoning; knowledge engineering, ontologies and the semantic web; machinelearning; philosophical foundations, metacognitive modeling and ethics; and planning and scheduling.

Download or read book Human Activity Recognition Using Smartphone Accelerometer and Machine Learning written by Mira Kamali and published by . This book was released on 2017 with total page 53 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Innovations in Smart Cities Applications Edition 2 written by Mohamed Ben Ahmed and published by Springer. This book was released on 2019-02-06 with total page 1234 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book highlights cutting-edge research presented at the third installment of the International Conference on Smart City Applications (SCA2018), held in Tétouan, Morocco on October 10–11, 2018. It presents original research results, new ideas, and practical lessons learned that touch on all aspects of smart city applications. The respective papers share new and highly original results by leading experts on IoT, Big Data, and Cloud technologies, and address a broad range of key challenges in smart cities, including Smart Education and Intelligent Learning Systems, Smart Healthcare, Smart Building and Home Automation, Smart Environment and Smart Agriculture, Smart Economy and Digital Business, and Information Technologies and Computer Science, among others. In addition, various novel proposals regarding smart cities are discussed. Gathering peer-reviewed chapters written by prominent researchers from around the globe, the book offers an invaluable instructional and research tool for courses on computer and urban sciences; students and practitioners in computer science, information science, technology studies and urban management studies will find it particularly useful. Further, the book is an excellent reference guide for professionals and researchers working in mobility, education, governance, energy, the environment and computer sciences.

Download or read book Soft Computing Theories and Applications written by Tarun K. Sharma and published by Springer Nature. This book was released on 2021-06-26 with total page 572 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on soft computing and how it can be applied to solve real-world problems arising in various domains, ranging from medicine and healthcare, to supply chain management, image processing and cryptanalysis. It gathers high-quality papers presented at the International Conference on Soft Computing: Theories and Applications (SoCTA 2020), organized online. The book is divided into two volumes and offers valuable insights into soft computing for teachers and researchers alike; the book will inspire further research in this dynamic field.

Download or read book Generalization With Deep Learning For Improvement On Sensing Capability written by Zhenghua Chen and published by World Scientific. This book was released on 2021-04-07 with total page 327 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep Learning has achieved great success in many challenging research areas, such as image recognition and natural language processing. The key merit of deep learning is to automatically learn good feature representation from massive data conceptually. In this book, we will show that the deep learning technology can be a very good candidate for improving sensing capabilities.In this edited volume, we aim to narrow the gap between humans and machines by showcasing various deep learning applications in the area of sensing. The book will cover the fundamentals of deep learning techniques and their applications in real-world problems including activity sensing, remote sensing and medical sensing. It will demonstrate how different deep learning techniques help to improve the sensing capabilities and enable scientists and practitioners to make insightful observations and generate invaluable discoveries from different types of data.

Download or read book Deep Learning for Time Series Forecasting written by Jason Brownlee and published by Machine Learning Mastery. This book was released on 2018-08-30 with total page 572 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep learning methods offer a lot of promise for time series forecasting, such as the automatic learning of temporal dependence and the automatic handling of temporal structures like trends and seasonality. With clear explanations, standard Python libraries, and step-by-step tutorial lessons you’ll discover how to develop deep learning models for your own time series forecasting projects.

Download or read book Predictive Classification for Human Activity Recognition Using Smartphones Sensor Data written by Oscar Rivera and published by . This book was released on 2019 with total page 130 pages. Available in PDF, EPUB and Kindle. Book excerpt: The purpose of this project is to apply the methodologies of CRISP-DM to determine the appropriate classifier models for predicting human activity based on data collected by sensors commonly found in smartphones. The classifiers to be evaluated in this project are Neural Net, C&R Tree, CHAID, Bayes Net, SVM, and Random Forest. The overall error rate of each model was used as the final selection criterion. The classifiers will classify six human activities, walking, standing, sitting, lying down, walking upstairs, and walking downstairs. The public domain data set for HAR using smartphones will be used to train and test the models (Anguita, Ghio, Oneto, Parra, & Reyes Ortiz 2013). The data was collected from experiments using a group of 30 volunteers. Each volunteer performed the six activities multiple times, wearing a smartphone attached to their waist for data collection. Raw sensor data from the smartphone's gyroscope and accelerometer was preprocessed to create a dataset of 561 features. The high dimensionality of the dataset is a problem for building a classifier able to operate within the processing capabilities of a smartphone. To reduce the number of dimensions for the classifiers, PCA was used on the dataset, and the feature selection was reduced to the top ten principal components. As an alternative, the full feature set was reduced by nearly 9% by selecting the 50 most important features as ranked by Pearson to create a feature subset for modeling. In all evaluations, the Support Vector Machine (SVM) proved to be the best classifier for predicting the six human activities. Using the full feature set, the SVM had an overall error rate of 3.9%, 14.2% for the feature subset, and 16.2% for the PCA features.

Download or read book Sensor Data Analysis and Management written by A. Suresh and published by John Wiley & Sons. This book was released on 2021-11-22 with total page 228 pages. Available in PDF, EPUB and Kindle. Book excerpt: Discover detailed insights into the methods, algorithms, and techniques for deep learning in sensor data analysis Sensor Data Analysis and Management: The Role of Deep Learning delivers an insightful and practical overview of the applications of deep learning techniques to the analysis of sensor data. The book collects cutting-edge resources into a single collection designed to enlighten the reader on topics as varied as recent techniques for fault detection and classification in sensor data, the application of deep learning to Internet of Things sensors, and a case study on high-performance computer gathering and processing of sensor data. The editors have curated a distinguished group of perceptive and concise papers that show the potential of deep learning as a powerful tool for solving complex modelling problems across a broad range of industries, including predictive maintenance, health monitoring, financial portfolio forecasting, and driver assistance. The book contains real-time examples of analyzing sensor data using deep learning algorithms and a step-by-step approach for installing and training deep learning using the Python keras library. Readers will also benefit from the inclusion of: A thorough introduction to the Internet of Things for human activity recognition, based on wearable sensor data An exploration of the benefits of neural networks in real-time environmental sensor data analysis Practical discussions of supervised learning data representation, neural networks for predicting physical activity based on smartphone sensor data, and deep-learning analysis of location sensor data for human activity recognition An analysis of boosting with XGBoost for sensor data analysis Perfect for industry practitioners and academics involved in deep learning and the analysis of sensor data, Sensor Data Analysis and Management: The Role of Deep Learning will also earn a place in the libraries of undergraduate and graduate students in data science and computer science programs.