Author: Prabin K. Bora
Publisher: Springer Nature
ISBN: 9811615500
Category : Technology & Engineering
Languages : en
Pages : 209
Book Description
This book comprises the select proceedings of the International Conference on Emerging Global Trends in Engineering and Technology (EGTET 2020), held in Guwahati, India. The chapters in this book focus on the latest cleaner, greener, and efficient technologies being developed for the implementation of smart cities across the world. The broader topical sections include Smart Buildings, Infrastructures and Disaster Management; Smart Governance; Technologies for Smart Cities, and Wireless Connectivity for Smart Cities. This book will cater to students, researchers, industry professionals, and policy making bodies interested and involved in the planning and implementation of smart city projects.
Emerging Technologies for Smart Cities
Author: Prabin K. Bora
Publisher: Springer Nature
ISBN: 9811615500
Category : Technology & Engineering
Languages : en
Pages : 209
Book Description
This book comprises the select proceedings of the International Conference on Emerging Global Trends in Engineering and Technology (EGTET 2020), held in Guwahati, India. The chapters in this book focus on the latest cleaner, greener, and efficient technologies being developed for the implementation of smart cities across the world. The broader topical sections include Smart Buildings, Infrastructures and Disaster Management; Smart Governance; Technologies for Smart Cities, and Wireless Connectivity for Smart Cities. This book will cater to students, researchers, industry professionals, and policy making bodies interested and involved in the planning and implementation of smart city projects.
Publisher: Springer Nature
ISBN: 9811615500
Category : Technology & Engineering
Languages : en
Pages : 209
Book Description
This book comprises the select proceedings of the International Conference on Emerging Global Trends in Engineering and Technology (EGTET 2020), held in Guwahati, India. The chapters in this book focus on the latest cleaner, greener, and efficient technologies being developed for the implementation of smart cities across the world. The broader topical sections include Smart Buildings, Infrastructures and Disaster Management; Smart Governance; Technologies for Smart Cities, and Wireless Connectivity for Smart Cities. This book will cater to students, researchers, industry professionals, and policy making bodies interested and involved in the planning and implementation of smart city projects.
Advancing Intelligent Networks Through Distributed Optimization
Author: Rajest, S. Suman
Publisher: IGI Global
ISBN:
Category : Computers
Languages : en
Pages : 618
Book Description
The numerous developments in wireless communications and artificial intelligence (AI) have recently transformed the Internet of Things (IoT) networks to a level of connectivity and intelligence beyond any prior design. This topology is sharply exemplified in mobile edge computing, smart cities, smart homes, smart grids, and the IoT, among many other intelligent applications. Intelligent networks are founded on integrating caching and multi-agent systems that optimize data storage and the entire devices learning process. However, a central node through which all agents transmit status messages and reward information is a major drawback of this design pattern. This central node condition instigates more communication overhead, potential data leakage, and the birth of data islands. To reverse this trend, using distributed optimization techniques and methodologies in cache-enabled multi-agent learning environments is increasingly beneficial. Advancing Intelligent Networks Through Distributed Optimization explains the current race for sophisticated and accurate distributed optimization in cache-enabled intelligent IoT networks given the need to make multi-agent learning converge faster and reduce communication overhead. These techniques will require innovative resource allocation strategies stretching from system training to caching, communication, and processing amongst millions of agents. This book combines the key recent research in these races into a single binder that can serve all the interested theoretical and practical scholars. The book focuses broadly on intelligent systems optimization trends. It identifies the various applications of advanced distributed optimization from manufacturing to medicine, agriculture and smart cities.
Publisher: IGI Global
ISBN:
Category : Computers
Languages : en
Pages : 618
Book Description
The numerous developments in wireless communications and artificial intelligence (AI) have recently transformed the Internet of Things (IoT) networks to a level of connectivity and intelligence beyond any prior design. This topology is sharply exemplified in mobile edge computing, smart cities, smart homes, smart grids, and the IoT, among many other intelligent applications. Intelligent networks are founded on integrating caching and multi-agent systems that optimize data storage and the entire devices learning process. However, a central node through which all agents transmit status messages and reward information is a major drawback of this design pattern. This central node condition instigates more communication overhead, potential data leakage, and the birth of data islands. To reverse this trend, using distributed optimization techniques and methodologies in cache-enabled multi-agent learning environments is increasingly beneficial. Advancing Intelligent Networks Through Distributed Optimization explains the current race for sophisticated and accurate distributed optimization in cache-enabled intelligent IoT networks given the need to make multi-agent learning converge faster and reduce communication overhead. These techniques will require innovative resource allocation strategies stretching from system training to caching, communication, and processing amongst millions of agents. This book combines the key recent research in these races into a single binder that can serve all the interested theoretical and practical scholars. The book focuses broadly on intelligent systems optimization trends. It identifies the various applications of advanced distributed optimization from manufacturing to medicine, agriculture and smart cities.
Image-Based Rendering
Author: Heung-Yeung Shum
Publisher: Springer Science & Business Media
ISBN: 0387326685
Category : Computers
Languages : en
Pages : 425
Book Description
Focusing exclusively on Image-Based Rendering (IBR) this book examines the theory, practice, and applications associated with image-based rendering and modeling. Topics covered vary from IBR basic concepts and representations on the theory side to signal processing and data compression on the practical side. One of the only titles devoted exclusively to IBR this book is intended for researchers, professionals, and general readers interested in the topics of computer graphics, computer vision, image process, and video processing. With this book advanced-level students in EECS studying related disciplines will be able to seriously expand their knowledge about image-based rendering.
Publisher: Springer Science & Business Media
ISBN: 0387326685
Category : Computers
Languages : en
Pages : 425
Book Description
Focusing exclusively on Image-Based Rendering (IBR) this book examines the theory, practice, and applications associated with image-based rendering and modeling. Topics covered vary from IBR basic concepts and representations on the theory side to signal processing and data compression on the practical side. One of the only titles devoted exclusively to IBR this book is intended for researchers, professionals, and general readers interested in the topics of computer graphics, computer vision, image process, and video processing. With this book advanced-level students in EECS studying related disciplines will be able to seriously expand their knowledge about image-based rendering.
AI Tools and Applications for Women’s Safety
Author: Ponnusamy, Sivaram
Publisher: IGI Global
ISBN:
Category : Computers
Languages : en
Pages : 386
Book Description
In an era marked by rapid technological progress, women's safety remains a pressing concern despite strides toward gender equality. Women continue to grapple with safety challenges in both public and private spaces, enduring harassment, violence, and discrimination driven by entrenched societal norms and modern complexities. Amidst these challenges, harnessing the potential of artificial intelligence (AI) emerges as a promising avenue to reshape the landscape of women's safety. The groundbreaking book, AI Tools and Applications for Women’s Safety, curated by experts Sivaram Ponnusamy, Vibha Bora, Prema Daigavane, and Sampada Wazalwar, delves into the transformative power of AI to address the daily safety concerns women face. This timely volume explores innovative AI-driven resources and applications that redefine personal security, offering tailored protection through real-time threat assessment and emergency response coordination. With comprehensive insights spanning academia, law enforcement, policymaking, and advocacy, this book covers predictive safety analytics, smart surveillance, ethical considerations, and more. AI Tools and Applications for Women’s Safety not only sheds light on the promise of AI but also paves the way for informed discourse and meaningful action, ushering in a future defined by women's empowerment and security.
Publisher: IGI Global
ISBN:
Category : Computers
Languages : en
Pages : 386
Book Description
In an era marked by rapid technological progress, women's safety remains a pressing concern despite strides toward gender equality. Women continue to grapple with safety challenges in both public and private spaces, enduring harassment, violence, and discrimination driven by entrenched societal norms and modern complexities. Amidst these challenges, harnessing the potential of artificial intelligence (AI) emerges as a promising avenue to reshape the landscape of women's safety. The groundbreaking book, AI Tools and Applications for Women’s Safety, curated by experts Sivaram Ponnusamy, Vibha Bora, Prema Daigavane, and Sampada Wazalwar, delves into the transformative power of AI to address the daily safety concerns women face. This timely volume explores innovative AI-driven resources and applications that redefine personal security, offering tailored protection through real-time threat assessment and emergency response coordination. With comprehensive insights spanning academia, law enforcement, policymaking, and advocacy, this book covers predictive safety analytics, smart surveillance, ethical considerations, and more. AI Tools and Applications for Women’s Safety not only sheds light on the promise of AI but also paves the way for informed discourse and meaningful action, ushering in a future defined by women's empowerment and security.
Artificial Intelligence in Healthcare
Author: Adam Bohr
Publisher: Academic Press
ISBN: 0128184396
Category : Computers
Languages : en
Pages : 385
Book Description
Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. - Highlights different data techniques in healthcare data analysis, including machine learning and data mining - Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks - Includes applications and case studies across all areas of AI in healthcare data
Publisher: Academic Press
ISBN: 0128184396
Category : Computers
Languages : en
Pages : 385
Book Description
Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. - Highlights different data techniques in healthcare data analysis, including machine learning and data mining - Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks - Includes applications and case studies across all areas of AI in healthcare data
Cognitive Computing for Human-Robot Interaction
Author: Mamta Mittal
Publisher: Academic Press
ISBN: 0323856470
Category : Computers
Languages : en
Pages : 420
Book Description
Cognitive Computing for Human-Robot Interaction: Principles and Practices explores the efforts that should ultimately enable society to take advantage of the often-heralded potential of robots to provide economical and sustainable computing applications. This book discusses each of these applications, presents working implementations, and combines coherent and original deliberative architecture for human–robot interactions (HRI). Supported by experimental results, it shows how explicit knowledge management promises to be instrumental in building richer and more natural HRI, by pushing for pervasive, human-level semantics within the robot's deliberative system for sustainable computing applications. This book will be of special interest to academics, postgraduate students, and researchers working in the area of artificial intelligence and machine learning. Key features: - Introduces several new contributions to the representation and management of humans in autonomous robotic systems; - Explores the potential of cognitive computing, robots, and HRI to generate a deeper understanding and to provide a better contribution from robots to society; - Engages with the potential repercussions of cognitive computing and HRI in the real world. - Introduces several new contributions to the representation and management of humans in an autonomous robotic system - Explores cognitive computing, robots and HRI, presenting a more in-depth understanding to make robots better for society - Gives a challenging approach to those several repercussions of cognitive computing and HRI in the actual global scenario
Publisher: Academic Press
ISBN: 0323856470
Category : Computers
Languages : en
Pages : 420
Book Description
Cognitive Computing for Human-Robot Interaction: Principles and Practices explores the efforts that should ultimately enable society to take advantage of the often-heralded potential of robots to provide economical and sustainable computing applications. This book discusses each of these applications, presents working implementations, and combines coherent and original deliberative architecture for human–robot interactions (HRI). Supported by experimental results, it shows how explicit knowledge management promises to be instrumental in building richer and more natural HRI, by pushing for pervasive, human-level semantics within the robot's deliberative system for sustainable computing applications. This book will be of special interest to academics, postgraduate students, and researchers working in the area of artificial intelligence and machine learning. Key features: - Introduces several new contributions to the representation and management of humans in autonomous robotic systems; - Explores the potential of cognitive computing, robots, and HRI to generate a deeper understanding and to provide a better contribution from robots to society; - Engages with the potential repercussions of cognitive computing and HRI in the real world. - Introduces several new contributions to the representation and management of humans in an autonomous robotic system - Explores cognitive computing, robots and HRI, presenting a more in-depth understanding to make robots better for society - Gives a challenging approach to those several repercussions of cognitive computing and HRI in the actual global scenario
Urban Informatics
Author: Wenzhong Shi
Publisher: Springer Nature
ISBN: 9811589836
Category : Social Science
Languages : en
Pages : 941
Book Description
This open access book is the first to systematically introduce the principles of urban informatics and its application to every aspect of the city that involves its functioning, control, management, and future planning. It introduces new models and tools being developed to understand and implement these technologies that enable cities to function more efficiently – to become ‘smart’ and ‘sustainable’. The smart city has quickly emerged as computers have become ever smaller to the point where they can be embedded into the very fabric of the city, as well as being central to new ways in which the population can communicate and act. When cities are wired in this way, they have the potential to become sentient and responsive, generating massive streams of ‘big’ data in real time as well as providing immense opportunities for extracting new forms of urban data through crowdsourcing. This book offers a comprehensive review of the methods that form the core of urban informatics from various kinds of urban remote sensing to new approaches to machine learning and statistical modelling. It provides a detailed technical introduction to the wide array of tools information scientists need to develop the key urban analytics that are fundamental to learning about the smart city, and it outlines ways in which these tools can be used to inform design and policy so that cities can become more efficient with a greater concern for environment and equity.
Publisher: Springer Nature
ISBN: 9811589836
Category : Social Science
Languages : en
Pages : 941
Book Description
This open access book is the first to systematically introduce the principles of urban informatics and its application to every aspect of the city that involves its functioning, control, management, and future planning. It introduces new models and tools being developed to understand and implement these technologies that enable cities to function more efficiently – to become ‘smart’ and ‘sustainable’. The smart city has quickly emerged as computers have become ever smaller to the point where they can be embedded into the very fabric of the city, as well as being central to new ways in which the population can communicate and act. When cities are wired in this way, they have the potential to become sentient and responsive, generating massive streams of ‘big’ data in real time as well as providing immense opportunities for extracting new forms of urban data through crowdsourcing. This book offers a comprehensive review of the methods that form the core of urban informatics from various kinds of urban remote sensing to new approaches to machine learning and statistical modelling. It provides a detailed technical introduction to the wide array of tools information scientists need to develop the key urban analytics that are fundamental to learning about the smart city, and it outlines ways in which these tools can be used to inform design and policy so that cities can become more efficient with a greater concern for environment and equity.
Social Sensing
Author: Dong Wang
Publisher: Morgan Kaufmann
ISBN: 0128011319
Category : Computers
Languages : en
Pages : 232
Book Description
Increasingly, human beings are sensors engaging directly with the mobile Internet. Individuals can now share real-time experiences at an unprecedented scale. Social Sensing: Building Reliable Systems on Unreliable Data looks at recent advances in the emerging field of social sensing, emphasizing the key problem faced by application designers: how to extract reliable information from data collected from largely unknown and possibly unreliable sources. The book explains how a myriad of societal applications can be derived from this massive amount of data collected and shared by average individuals. The title offers theoretical foundations to support emerging data-driven cyber-physical applications and touches on key issues such as privacy. The authors present solutions based on recent research and novel ideas that leverage techniques from cyber-physical systems, sensor networks, machine learning, data mining, and information fusion. Offers a unique interdisciplinary perspective bridging social networks, big data, cyber-physical systems, and reliability Presents novel theoretical foundations for assured social sensing and modeling humans as sensors Includes case studies and application examples based on real data sets Supplemental material includes sample datasets and fact-finding software that implements the main algorithms described in the book
Publisher: Morgan Kaufmann
ISBN: 0128011319
Category : Computers
Languages : en
Pages : 232
Book Description
Increasingly, human beings are sensors engaging directly with the mobile Internet. Individuals can now share real-time experiences at an unprecedented scale. Social Sensing: Building Reliable Systems on Unreliable Data looks at recent advances in the emerging field of social sensing, emphasizing the key problem faced by application designers: how to extract reliable information from data collected from largely unknown and possibly unreliable sources. The book explains how a myriad of societal applications can be derived from this massive amount of data collected and shared by average individuals. The title offers theoretical foundations to support emerging data-driven cyber-physical applications and touches on key issues such as privacy. The authors present solutions based on recent research and novel ideas that leverage techniques from cyber-physical systems, sensor networks, machine learning, data mining, and information fusion. Offers a unique interdisciplinary perspective bridging social networks, big data, cyber-physical systems, and reliability Presents novel theoretical foundations for assured social sensing and modeling humans as sensors Includes case studies and application examples based on real data sets Supplemental material includes sample datasets and fact-finding software that implements the main algorithms described in the book
TinyML
Author: Pete Warden
Publisher: O'Reilly Media
ISBN: 1492052019
Category : Computers
Languages : en
Pages : 504
Book Description
Deep learning networks are getting smaller. Much smaller. The Google Assistant team can detect words with a model just 14 kilobytes in size—small enough to run on a microcontroller. With this practical book you’ll enter the field of TinyML, where deep learning and embedded systems combine to make astounding things possible with tiny devices. Pete Warden and Daniel Situnayake explain how you can train models small enough to fit into any environment. Ideal for software and hardware developers who want to build embedded systems using machine learning, this guide walks you through creating a series of TinyML projects, step-by-step. No machine learning or microcontroller experience is necessary. Build a speech recognizer, a camera that detects people, and a magic wand that responds to gestures Work with Arduino and ultra-low-power microcontrollers Learn the essentials of ML and how to train your own models Train models to understand audio, image, and accelerometer data Explore TensorFlow Lite for Microcontrollers, Google’s toolkit for TinyML Debug applications and provide safeguards for privacy and security Optimize latency, energy usage, and model and binary size
Publisher: O'Reilly Media
ISBN: 1492052019
Category : Computers
Languages : en
Pages : 504
Book Description
Deep learning networks are getting smaller. Much smaller. The Google Assistant team can detect words with a model just 14 kilobytes in size—small enough to run on a microcontroller. With this practical book you’ll enter the field of TinyML, where deep learning and embedded systems combine to make astounding things possible with tiny devices. Pete Warden and Daniel Situnayake explain how you can train models small enough to fit into any environment. Ideal for software and hardware developers who want to build embedded systems using machine learning, this guide walks you through creating a series of TinyML projects, step-by-step. No machine learning or microcontroller experience is necessary. Build a speech recognizer, a camera that detects people, and a magic wand that responds to gestures Work with Arduino and ultra-low-power microcontrollers Learn the essentials of ML and how to train your own models Train models to understand audio, image, and accelerometer data Explore TensorFlow Lite for Microcontrollers, Google’s toolkit for TinyML Debug applications and provide safeguards for privacy and security Optimize latency, energy usage, and model and binary size
Encyclopedia of Data Science and Machine Learning
Author: Wang, John
Publisher: IGI Global
ISBN: 1799892212
Category : Computers
Languages : en
Pages : 3296
Book Description
Big data and machine learning are driving the Fourth Industrial Revolution. With the age of big data upon us, we risk drowning in a flood of digital data. Big data has now become a critical part of both the business world and daily life, as the synthesis and synergy of machine learning and big data has enormous potential. Big data and machine learning are projected to not only maximize citizen wealth, but also promote societal health. As big data continues to evolve and the demand for professionals in the field increases, access to the most current information about the concepts, issues, trends, and technologies in this interdisciplinary area is needed. The Encyclopedia of Data Science and Machine Learning examines current, state-of-the-art research in the areas of data science, machine learning, data mining, and more. It provides an international forum for experts within these fields to advance the knowledge and practice in all facets of big data and machine learning, emphasizing emerging theories, principals, models, processes, and applications to inspire and circulate innovative findings into research, business, and communities. Covering topics such as benefit management, recommendation system analysis, and global software development, this expansive reference provides a dynamic resource for data scientists, data analysts, computer scientists, technical managers, corporate executives, students and educators of higher education, government officials, researchers, and academicians.
Publisher: IGI Global
ISBN: 1799892212
Category : Computers
Languages : en
Pages : 3296
Book Description
Big data and machine learning are driving the Fourth Industrial Revolution. With the age of big data upon us, we risk drowning in a flood of digital data. Big data has now become a critical part of both the business world and daily life, as the synthesis and synergy of machine learning and big data has enormous potential. Big data and machine learning are projected to not only maximize citizen wealth, but also promote societal health. As big data continues to evolve and the demand for professionals in the field increases, access to the most current information about the concepts, issues, trends, and technologies in this interdisciplinary area is needed. The Encyclopedia of Data Science and Machine Learning examines current, state-of-the-art research in the areas of data science, machine learning, data mining, and more. It provides an international forum for experts within these fields to advance the knowledge and practice in all facets of big data and machine learning, emphasizing emerging theories, principals, models, processes, and applications to inspire and circulate innovative findings into research, business, and communities. Covering topics such as benefit management, recommendation system analysis, and global software development, this expansive reference provides a dynamic resource for data scientists, data analysts, computer scientists, technical managers, corporate executives, students and educators of higher education, government officials, researchers, and academicians.