Recent Trends and Advances in Artificial Intelligence and Internet of Things


Book Description

This book covers all the emerging trends in artificial intelligence (AI) and the Internet of Things (IoT). The Internet of Things is a term that has been introduced in recent years to define devices that are able to connect and transfer data to other devices via the Internet. While IoT and sensors have the ability to harness large volumes of data, AI can learn patterns in the data and quickly extract insights in order to automate tasks for a variety of business benefits. Machine learning, an AI technology, brings the ability to automatically identify patterns and detect anomalies in the data that smart sensors and devices generate, and it can have significant advantages over traditional business intelligence tools for analyzing IoT data, including being able to make operational predictions up to 20 times earlier and with greater accuracy than threshold-based monitoring systems. Further, other AI technologies, such as speech recognition and computer vision can help extract insights from data that used to require human review. The powerful combination of AI and IoT technology is helping to avoid unplanned downtime, increase operating efficiency, enable new products and services, and enhance risk management.




A Fusion of Artificial Intelligence and Internet of Things for Emerging Cyber Systems


Book Description

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.




Advances in Edge Computing: Massive Parallel Processing and Applications


Book Description

The rapid advance of Internet of Things (IoT) technologies has resulted in the number of IoT-connected devices growing exponentially, with billions of connected devices worldwide. While this development brings with it great opportunities for many fields of science, engineering, business and everyday life, it also presents challenges such as an architectural bottleneck – with a very large number of IoT devices connected to a rather small number of servers in Cloud data centers – and the problem of data deluge. Edge computing aims to alleviate the computational burden of the IoT for the Cloud by pushing some of the computations and logics of processing from the Cloud to the Edge of the Internet. It is becoming commonplace to allocate tasks and applications such as data filtering, classification, semantic enrichment and data aggregation to this layer, but to prevent this new layer from itself becoming another bottleneck for the whole computing stack from IoT to the Cloud, the Edge computing layer needs to be capable of implementing massively parallel and distributed algorithms efficiently. This book, Advances in Edge Computing: Massive Parallel Processing and Applications, addresses these challenges in 11 chapters. Subjects covered include: Fog storage software architecture; IoT-based crowdsourcing; the industrial Internet of Things; privacy issues; smart home management in the Cloud and the Fog; and a cloud robotic solution to assist medical applications. Providing an overview of developments in the field, the book will be of interest to all those working with the Internet of Things and Edge computing.










Artificial Intelligence in Construction Engineering and Management


Book Description

This book highlights the latest technologies and applications of Artificial Intelligence (AI) in the domain of construction engineering and management. The construction industry worldwide has been a late bloomer to adopting digital technology, where construction projects are predominantly managed with a heavy reliance on the knowledge and experience of construction professionals. AI works by combining large amounts of data with fast, iterative processing, and intelligent algorithms (e.g., neural networks, process mining, and deep learning), allowing the computer to learn automatically from patterns or features in the data. It provides a wide range of solutions to address many challenging construction problems, such as knowledge discovery, risk estimates, root cause analysis, damage assessment and prediction, and defect detection. A tremendous transformation has taken place in the past years with the emerging applications of AI. This enables industrial participants to operate projects more efficiently and safely, not only increasing the automation and productivity in construction but also enhancing the competitiveness globally.




Connected Business


Book Description

How do you develop business in a world certain to be dominated by Internet of Things, Artificial Intelligence, and the Economy of Things?This book brings together leading scholars from academia, established practitioners, and thought-leading consultants who analyse and provide guidance to answer this question. Case studies, checklists, success factors, help readers get a grip on this fast-paced development. At the same time, the authors do not shy away from addressing the hurdles and barriers to implementation. This book provides an essential food-for-thought for leaders and managers, both visionary and pragmatic, who are faced with the responsibility of steering their business through these challenging, yet exciting, times.




Microsupercapacitors


Book Description

Microsupercapacitors systematically guides the reader through the key materials, characterization techniques, performance factors and potential applications and benefits to society of this emerging electrical energy storage solution. The book reviews the technical challenges in scaling down supercapacitors, covering materials, performance, design and applications perspectives. Sections provide a fundamental understanding of microsupercapacitors and compare them to existing energy storage technologies. Final discussions consider the factors that impact performance, potential tactics to improve performance, barriers to implementation, emerging solutions to those barriers, and a future outlook. This book will be of particular interest to materials scientists and engineers working in academia, research and development. - Provides a concise introduction of the fundamental science, related technological challenges, and solutions that microsupercapacitors can offer - Compares microsupercapacitors with current technologies - Reviews the applications of new strategies and the challenge of scaling down supercapacitors - Covers the most relevant applications, including energy storage, energy harvesting, sensors and biomedical devices




Hands-On Deep Learning for IoT


Book Description

Implement popular deep learning techniques to make your IoT applications smarter Key FeaturesUnderstand how deep learning facilitates fast and accurate analytics in IoTBuild intelligent voice and speech recognition apps in TensorFlow and ChainerAnalyze IoT data for making automated decisions and efficient predictionsBook Description Artificial Intelligence is growing quickly, which is driven by advancements in neural networks(NN) and deep learning (DL). With an increase in investments in smart cities, smart healthcare, and industrial Internet of Things (IoT), commercialization of IoT will soon be at peak in which massive amounts of data generated by IoT devices need to be processed at scale. Hands-On Deep Learning for IoT will provide deeper insights into IoT data, which will start by introducing how DL fits into the context of making IoT applications smarter. It then covers how to build deep architectures using TensorFlow, Keras, and Chainer for IoT. You’ll learn how to train convolutional neural networks(CNN) to develop applications for image-based road faults detection and smart garbage separation, followed by implementing voice-initiated smart light control and home access mechanisms powered by recurrent neural networks(RNN). You’ll master IoT applications for indoor localization, predictive maintenance, and locating equipment in a large hospital using autoencoders, DeepFi, and LSTM networks. Furthermore, you’ll learn IoT application development for healthcare with IoT security enhanced. By the end of this book, you will have sufficient knowledge need to use deep learning efficiently to power your IoT-based applications for smarter decision making. What you will learnGet acquainted with different neural network architectures and their suitability in IoTUnderstand how deep learning can improve the predictive power in your IoT solutionsCapture and process streaming data for predictive maintenanceSelect optimal frameworks for image recognition and indoor localizationAnalyze voice data for speech recognition in IoT applicationsDevelop deep learning-based IoT solutions for healthcareEnhance security in your IoT solutionsVisualize analyzed data to uncover insights and perform accurate predictionsWho this book is for If you’re an IoT developer, data scientist, or deep learning enthusiast who wants to apply deep learning techniques to build smart IoT applications, this book is for you. Familiarity with machine learning, a basic understanding of the IoT concepts, and some experience in Python programming will help you get the most out of this book.




Business Innovation with New ICT in the Asia-Pacific: Case Studies


Book Description

This book clarifies the direction of business innovation using new ICT such as the Internet of things (IoT), artificial intelligence (AI), smartphones, and cloud computing through a series of case studies on successful trials and advanced businesses in the Asia-Pacific where many industry sectors have been growing successfully in the 21st century. ICT has been playing an important role in value creation for customers and in profit generation for providers, contributing to various service innovation and business innovation. Now, digitalization using IoT and AI provides solutions to address various issues in the human society, which is transforming services and businesses in the 21st century. “What is the direction of the business innovation using new ICT?” is a highly concerned question for business researchers and practitioners. Aiming to answer the question, this book conducts a number of cases studies in the Asia-Pacific region, including the Mainland China, Taiwan, Japan, Malaysia, Vietnam, as well as Australia. Among the studies, there are 4 cases from ICT providers, 4 cases from traditional and services, and 6 cases from new ICT applications and businesses. Each case analyzes social needs and human desires, new value created, roles of new technologies, processes and difficulties in developing new businesses, the relationship among customers, providers, and stakeholders, value chain co-creation and optimization, factors of success, and business models. Finally, the direction of business innovation with new ICT in the Asia-Pacific is suggested by summarizing the findings from the case studies through the lens of the theoretical analysis in service science.