IoT-enabled Convolutional Neural Networks: Techniques and Applications PDF Download

Author: Mohd Naved
Publisher: CRC Press
ISBN: 1000879690
Category : Computers
Languages : en
Pages : 409

View

Book Description
Convolutional neural networks (CNNs), a type of deep neural network that has become dominant in a variety of computer vision tasks, in recent years, CNNs have attracted interest across a variety of domains due to their high efficiency at extracting meaningful information from visual imagery. CNNs excel at a wide range of machine learning and deep learning tasks. As sensor-enabled internet of things (IoT) devices pervade every aspect of modern life, it is becoming increasingly critical to run CNN inference, a computationally intensive application, on resource-constrained devices. Through this edited volume, we aim to provide a structured presentation of CNN-enabled IoT applications in vision, speech, and natural language processing. This book discusses a variety of CNN techniques and applications, including but not limited to, IoT enabled CNN for speech denoising, a smart app for visually impaired people, disease detection, ECG signal analysis, weather monitoring, texture analysis, etc. Unlike other books on the market, this book covers the tools, techniques, and challenges associated with the implementation of CNN algorithms, computation time, and the complexity associated with reasoning and modelling various types of data. We have included CNNs' current research trends and future directions.

Author: V. Ajantha Devi
Publisher: Springer Nature
ISBN: 9819753651
Category :
Languages : en
Pages : 179

View

Book Description

Author: Andrei Velichko
Publisher:
ISBN: 9783036584294
Category :
Languages : en
Pages : 0

View

Book Description
In the age of neural networks and the Internet of Things (IoT), the search for new neural network architectures capable of operating on devices with limited computing power and small memory size is becoming an urgent agenda. This reprint focuses on recent developments in the organization of artificial intelligence (AI) on edge devices for various IoT-enabled smart applications and starts with the illustration of achievements in smart healthcare services. Digitalization of healthcare driven by the IoT and AI leads to the effective use of sensors, enabling various parameters of the human body to be instantly tracked and processed in daily life. The concept of machine learning sensors is applied to the diagnosis of COVID-19 as an IoT application in healthcare and ambient assisted living. Wearable sensors and IoT-enabled technologies also look promising for monitoring motor activity and gait in Parkinson's disease patients. IoT devices with AI can be effectively used in speech recognition and environmental monitoring, for detecting distracting actions in driver activities and for lifesaving applications such as child drowning prevention systems. Smart disaster rescue is an interesting development of a wearable device for search dogs that recognizes the behavior of a dog when a victim is found, using deep learning models. This reprint illustrates advanced cases of using AI technology for IoT-enabled smart applications.

Author: Andrei Velichko
Publisher: Mdpi AG
ISBN: 9783036584287
Category :
Languages : en
Pages : 0

View

Book Description
In the age of neural networks and the Internet of Things (IoT), the search for new neural network architectures capable of operating on devices with limited computing power and small memory size is becoming an urgent agenda. This reprint focuses on recent developments in the organization of artificial intelligence (AI) on edge devices for various IoT-enabled smart applications and starts with the illustration of achievements in smart healthcare services. Digitalization of healthcare driven by the IoT and AI leads to the effective use of sensors, enabling various parameters of the human body to be instantly tracked and processed in daily life. The concept of machine learning sensors is applied to the diagnosis of COVID-19 as an IoT application in healthcare and ambient assisted living. Wearable sensors and IoT-enabled technologies also look promising for monitoring motor activity and gait in Parkinson's disease patients. IoT devices with AI can be effectively used in speech recognition and environmental monitoring, for detecting distracting actions in driver activities and for lifesaving applications such as child drowning prevention systems. Smart disaster rescue is an interesting development of a wearable device for search dogs that recognizes the behavior of a dog when a victim is found, using deep learning models. This reprint illustrates advanced cases of using AI technology for IoT-enabled smart applications. Each case demonstrates a promising trend for applying AI in IoT environments, making a step towards the effective use of modern technologies in our everyday life.

Author: Naim, Arshi
Publisher: IGI Global
ISBN:
Category : Technology & Engineering
Languages : en
Pages : 339

View

Book Description
Climate change, natural resource depletion, and unsustainable agricultural practices pose unprecedented challenges to our planet. The increasing environmental footprint of computer networks, communication systems, and other IT infrastructures exacerbates these issues, contributing significantly to energy consumption and greenhouse gas emissions. Without innovative solutions, these challenges will continue to escalate, threatening the sustainability of our planet for future generations. AI Applications for Business, Medical, and Agricultural Sustainability offers a comprehensive solution by harnessing the power of Artificial Intelligence (AI) and High-Performance Computing (HPC). This book is ideal for educators, environmentalists, industry professionals, researchers, and academics. By introducing new energy models, algorithms, and methodologies, the book provides a roadmap for developing next-generation computing and communication infrastructures that are environmentally sustainable.

Author: Rashmi Gupta
Publisher: CRC Press
ISBN: 1000543021
Category : Computers
Languages : en
Pages : 380

View

Book Description
The book provides future research directions in IoT and image processing based Energy, Industry, and Healthcare domain and explores the different applications of its associated technologies. However, the Internet of Things and image processing is a very big field with a lot of subfields, which are very important such as Smart Homes to improve our daily life, Smart Cities to improve the citizens' life, Smart Towns to recover the livability and traditions, Smart Earth to protect our world, and Industrial Internet of Things to create safer and easier jobs. This book considers very important research areas in Energy, Industry, and Healthcare domain with IoT and image processing applications.The aim of the book to highlights future directions of optimization methods in various engineering and science applications in various IoT and image processing applications. Emphasis is given to deep learning and similar models of neural network-based learning techniques employed in solving optimization problems of different engineering and science applications. The role of AI in mechatronics is also highlighted using suitable optimization methods. This book considers very important research areas in Energy, Industry, and Healthcare. It addresses major issues and challenges in Energy, Industry, and Healthcare and solutions proposed for IoT-enabled cellular/computer networks, routing/communication protocols, surveillances applications, secured data management, and positioning approaches. It focuses mainly on smart and context-aware implementations. Key sailing Features: The impact of the proposed book is to provide a major area of concern to develop a foundation for the implementation process of new image processing and IoT devices based on Energy, Industry, and Healthcare related technology. The researchers working on image processing and IoT devices can correlate their work with other requirements of advanced technology in Energy, Industry, and Healthcare domain. To make aware of the latest technology like AI and Machine learning in Energy, Industry, and Healthcare related technology. Useful for the researcher to explore new things like Security, cryptography, and privacy in Energy, Industry, and Healthcare related technology. People who want to start in Energy, Industry, and Healthcare related technology with image processing and IoT world.

Author: Naim, Arshi
Publisher: IGI Global
ISBN:
Category : Education
Languages : en
Pages : 433

View

Book Description
Higher education institutions must urgently overcome the difficulty of negotiating the complex web of international accreditation standards in a rapidly globalized world. Academic researchers, teachers, and administrators struggle with the intricacy of making sure their programs adhere to strict standards while still attempting to maintain their competitiveness on a global level. These organizations run the risk of stagnation and missing out on possibilities for advancement and recognition if there is no clear path forward. Evaluating Global Accreditation Standards for Higher Education, is a comprehensive guide for overcoming the modern accreditation conundrum. This invaluable resource equips academic scholars and professionals with the tools and knowledge they need to successfully navigate the accreditation process at both local and international levels. From program criteria and curriculum development to faculty professional development and alumni engagement, this book offers a roadmap to excellence. By following the expert guidance within these pages, institutions can unlock their potential, achieve accreditation, and gain the recognition they deserve.

Author: Jorge Rocha
Publisher: BoD – Books on Demand
ISBN: 0854660534
Category : Mathematics
Languages : en
Pages : 300

View

Book Description
Time series analysis describes, explains, and predicts changes in a phenomenon through time. People have utilized techniques that add a distinctive spatial dimension to this type of analysis. Major applications of spatiotemporal analysis include forecasting epidemics, analyzing the development of traffic conditions in urban networks, and forecasting/backcasting economic risks such as those associated with changing house prices and the occurrence of hazardous events. This book includes contributions from researchers, scholars, and professionals about the most recent theory, models, and applications for interdisciplinary and multidisciplinary research encircling disciplines of computer science, mathematics, statistics, geography, and more in time series analysis and forecasting/backcasting.

Author: Pawan Singh
Publisher: CRC Press
ISBN: 1000967948
Category : Computers
Languages : en
Pages : 376

View

Book Description
We have seen a sharp increase in the development of data transfer techniques in the networking industry over the past few years. We can see that the photos are assisting clinicians in detecting infection in patients even in the current COVID-19 pandemic condition. With the aid of ML/AI, medical imaging, such as lung X-rays for COVID-19 infection, is crucial in the early detection of many diseases. We also learned that in the COVID-19 scenario, both wired and wireless networking are improved for data transfer but have network congestion. An intriguing concept that has the ability to reduce spectrum congestion and continuously offer new network services is providing wireless network virtualization. The degree of virtualization and resource sharing varies between the paradigms. Each paradigm has both technical and non-technical issues that need to be handled before wireless virtualization becomes a common technology. For wireless network virtualization to be successful, these issues need careful design and evaluation. Future wireless network architecture must adhere to a number of Quality of Service (QoS) requirements. Virtualization has been extended to wireless networks as well as conventional ones. By enabling multi-tenancy and tailored services with a wider range of carrier frequencies, it improves efficiency and utilization. In the IoT environment, wireless users are heterogeneous, and the network state is dynamic, making network control problems extremely difficult to solve as dimensionality and computational complexity keep rising quickly. Deep Reinforcement Learning (DRL) has been developed by the use of Deep Neural Networks (DNNs) as a potential approach to solve high-dimensional and continuous control issues effectively. Deep Reinforcement Learning techniques provide great potential in IoT, edge and SDN scenarios and are used in heterogeneous networks for IoT-based management on the QoS required by each Software Defined Network (SDN) service. While DRL has shown great potential to solve emerging problems in complex wireless network virtualization, there are still domain-specific challenges that require further study, including the design of adequate DNN architectures with 5G network optimization issues, resource discovery and allocation, developing intelligent mechanisms that allow the automated and dynamic management of the virtual communications established in the SDNs which is considered as research perspective.

Author: Uttam Ghosh
Publisher: CRC Press
ISBN: 1000431894
Category : Computers
Languages : en
Pages : 267

View

Book Description
This book promotes and facilitates exchanges of research knowledge and findings across different disciplines on the design and investigation of deep learning (DL)–based data analytics of IoT (Internet of Things) infrastructures. Deep Learning for Internet of Things Infrastructure addresses emerging trends and issues on IoT systems and services across various application domains. The book investigates the challenges posed by the implementation of deep learning on IoT networking models and services. It provides fundamental theory, model, and methodology in interpreting, aggregating, processing, and analyzing data for intelligent DL-enabled IoT. The book also explores new functions and technologies to provide adaptive services and intelligent applications for different end users. FEATURES Promotes and facilitates exchanges of research knowledge and findings across different disciplines on the design and investigation of DL-based data analytics of IoT infrastructures Addresses emerging trends and issues on IoT systems and services across various application domains Investigates the challenges posed by the implementation of deep learning on IoT networking models and services Provides fundamental theory, model, and methodology in interpreting, aggregating, processing, and analyzing data for intelligent DL-enabled IoT Explores new functions and technologies to provide adaptive services and intelligent applications for different end users Uttam Ghosh is an Assistant Professor in the Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, Tennessee, USA. Mamoun Alazab is an Associate Professor in the College of Engineering, IT and Environment at Charles Darwin University, Australia. Ali Kashif Bashir is a Senior Lecturer/Associate Professor and Program Leader of BSc (H) Computer Forensics and Security at the Department of Computing and Mathematics, Manchester Metropolitan University, United Kingdom. Al-Sakib Khan Pathan is an Adjunct Professor of Computer Science and Engineering at the Independent University, Bangladesh.