This book provides comprehensive coverage of the major aspects in designing, implementing, and deploying wireless sensor networks by discussing present research on WSNs and their applications in various disciplines. It familiarizes readers with the current state of WSNs and how such networks can be improved to achieve effectiveness and efficiency. It starts with a detailed introduction of wireless sensor networks and their applications and proceeds with layered architecture of WSNs. It also addresses prominent issues such as mobility, heterogeneity, fault-tolerance, intermittent connectivity, and cross layer optimization along with a number of existing solutions to stimulate future research.

This book provides comprehensive coverage of the major aspects in designing, implementing, and deploying wireless sensor networks by discussing present research on WSNs and their applications in various disciplines. It familiarizes readers with the current state of WSNs and how such networks can be improved to achieve effectiveness and efficiency. It starts with a detailed introduction of wireless sensor networks and their applications and proceeds with layered architecture of WSNs. It also addresses prominent issues such as mobility, heterogeneity, fault-tolerance, intermittent connectivity, and cross layer optimization along with a number of existing solutions to stimulate future research.

This volume helps to address the genuine 21st century need for advances in data science and computing technology. It provides an abundance of new research and studies on progressive and innovative technologies, including artificial intelligence, communication systems, cyber security applications, data analytics, Internet of Things (IoT), machine learning, power systems, VLSI, embedded systems, and much more. The book presents a variety of interesting and important aspects of data science and computing technologies and methodologies in a wide range of applications, including deep learning, DNA cryptography, classy fuzzy MPPT controller, driving assistance, and safety systems. Novel algorithms and their applications for solving cutting-edge computational and data science problems are included also for an interdisciplinary research perspective.

The book addresses recent applications of deep learning and ANN paradigms, the role and impact of big data in the e-commerce and retail sectors, algorithms for load balancing in cloud computing, advances in embedded system based applications, optimization techniques using a MATLAB platform, and techniques for improving information and network security.

Advances in Data Science and Computing Technology: Methodology and Applications provides a wealth of valuable information and food for thought on many important issues for data scientists and researchers, industry professionals, and faculty and students in the data and computing sciences.

This volume helps to address the genuine 21st century need for advances in data science and computing technology. It provides an abundance of new research and studies on progressive and innovative technologies, including artificial intelligence, communication systems, cyber security applications, data analytics, Internet of Things (IoT), machine learning, power systems, VLSI, embedded systems, and much more. The book presents a variety of interesting and important aspects of data science and computing technologies and methodologies in a wide range of applications, including deep learning, DNA cryptography, classy fuzzy MPPT controller, driving assistance, and safety systems. Novel algorithms and their applications for solving cutting-edge computational and data science problems are included also for an interdisciplinary research perspective.

The book addresses recent applications of deep learning and ANN paradigms, the role and impact of big data in the e-commerce and retail sectors, algorithms for load balancing in cloud computing, advances in embedded system based applications, optimization techniques using a MATLAB platform, and techniques for improving information and network security.

Advances in Data Science and Computing Technology: Methodology and Applications provides a wealth of valuable information and food for thought on many important issues for data scientists and researchers, industry professionals, and faculty and students in the data and computing sciences.

The mushrooming of illegal housing on the periphery of cities is one of the main consequences of rapid urbanisation associated with social and environmental problems in the developing countries. Sustainable Urbanism in Developing Countries discusses the linkage between urbanism and sustainability and how sustainable urbanism can be implemented to overcome the problems of housing and living conditions in urban areas. Through case studies from India, Indonesia, China, etc., using advanced GIS techniques, this book analyses several planning and design criteria to solve the physical, social, and economic problems of urbanisation and refers to urban planning as an effective measure to protect and promote the cultural characteristics of specific locations in these developing countries.

FEATURES

The mushrooming of illegal housing on the periphery of cities is one of the main consequences of rapid urbanisation associated with social and environmental problems in the developing countries. Sustainable Urbanism in Developing Countries discusses the linkage between urbanism and sustainability and how sustainable urbanism can be implemented to overcome the problems of housing and living conditions in urban areas. Through case studies from India, Indonesia, China, etc., using advanced GIS techniques, this book analyses several planning and design criteria to solve the physical, social, and economic problems of urbanisation and refers to urban planning as an effective measure to protect and promote the cultural characteristics of specific locations in these developing countries.

FEATURES

While technology is developing at a fast pace, urban planners and cities are still behind in finding effective ways to use technology to address citizen’s needs. Multiple aspects of sustainable urbanism are brought together in this book, along with advanced technologies and their connections to urban planning and management. It integrates urban studies, smart cities, AI, IoT, remote sensing, and GIS. Highlights include land use planning, spatial planning, and ecosystem-based information to improve economic opportunities. Urban planners and engineers will understand the use of AI in disaster management and the use of GIS in finding suitable landfill sites for sustainable waste management.

Features

While technology is developing at a fast pace, urban planners and cities are still behind in finding effective ways to use technology to address citizen’s needs. Multiple aspects of sustainable urbanism are brought together in this book, along with advanced technologies and their connections to urban planning and management. It integrates urban studies, smart cities, AI, IoT, remote sensing, and GIS. Highlights include land use planning, spatial planning, and ecosystem-based information to improve economic opportunities. Urban planners and engineers will understand the use of AI in disaster management and the use of GIS in finding suitable landfill sites for sustainable waste management.

Features

Computational Intelligence for Wireless Sensor Networks: Principles and Applications provides an integrative overview of the computational intelligence (CI) in wireless sensor networks and enabled technologies. It aims to demonstrate how the paradigm of computational intelligence can benefit Wireless Sensor Networks (WSNs) and sensor-enabled technologies to overcome their existing issues.

This book provides extensive coverage of the multiple design challenges of WSNs and associated technologies such as clustering, routing, media access, security, mobility, and design of energy-efficient network operations.

It also describes various CI strategies such as fuzzy computing, evolutionary computing, reinforcement learning, artificial intelligence, swarm intelligence, teaching learning-based optimization, etc. It also discusses applying the techniques mentioned above in wireless sensor networks and sensor-enabled technologies to improve their design.

The book offers comprehensive coverage of related topics, including:

This book mainly addresses the challenges pertaining to the development of intelligent network systems via computational intelligence. It provides insights into how intelligence has been pursued and can be further integrated in the development of sensor-enabled applications.

Computational Intelligence for Wireless Sensor Networks: Principles and Applications provides an integrative overview of the computational intelligence (CI) in wireless sensor networks and enabled technologies. It aims to demonstrate how the paradigm of computational intelligence can benefit Wireless Sensor Networks (WSNs) and sensor-enabled technologies to overcome their existing issues.

This book provides extensive coverage of the multiple design challenges of WSNs and associated technologies such as clustering, routing, media access, security, mobility, and design of energy-efficient network operations.

It also describes various CI strategies such as fuzzy computing, evolutionary computing, reinforcement learning, artificial intelligence, swarm intelligence, teaching learning-based optimization, etc. It also discusses applying the techniques mentioned above in wireless sensor networks and sensor-enabled technologies to improve their design.

The book offers comprehensive coverage of related topics, including:

This book mainly addresses the challenges pertaining to the development of intelligent network systems via computational intelligence. It provides insights into how intelligence has been pursued and can be further integrated in the development of sensor-enabled applications.

This book explores the discourse on urban and regional inequality within the framework of neoliberalism. It analyzes the widespread application of neoliberal policies in Asian city regions and identifies their influence on rising inequality. The book captures inequality through spatial and non-spatial policy narratives with empirical evidence from India, Japan, South Korea, Taiwan, and Thailand. The book uses analytics, narratives and simulation to unfold the opportunities and threats to urban regions that bear the impacts of globalization and neoliberal policies.

Lucid and topical, this book will be an essential read for scholars and researchers of urban economics, urban and regional planning, urban studies, urban sociology, political economy, public policy, governance, development studies and Asian economy.

This book explores the discourse on urban and regional inequality within the framework of neoliberalism. It analyzes the widespread application of neoliberal policies in Asian city regions and identifies their influence on rising inequality. The book captures inequality through spatial and non-spatial policy narratives with empirical evidence from India, Japan, South Korea, Taiwan, and Thailand. The book uses analytics, narratives and simulation to unfold the opportunities and threats to urban regions that bear the impacts of globalization and neoliberal policies.

Lucid and topical, this book will be an essential read for scholars and researchers of urban economics, urban and regional planning, urban studies, urban sociology, political economy, public policy, governance, development studies and Asian economy.

Despite the increasing population (the Food and Agriculture Organization of the United Nations estimates 70% more food will be needed in 2050 than was produced in 2006), issues related to food production have yet to be completely addressed. In recent years, Internet of Things technology has begun to be used to address different industrial and technical challenges to meet this growing need. These Agro-IoT tools boost productivity and minimize the pitfalls of traditional farming, which is the backbone of the world''s economy. Aided by the IoT, continuous monitoring of fields provides useful and critical information to farmers, ushering in a new era in farming. The IoT can be used as a tool to combat climate change through greenhouse automation; monitor and manage water, soil and crops; increase productivity; control insecticides/pesticides; detect plant diseases; increase the rate of crop sales; cattle monitoring etc.

Agricultural Informatics: Automation Using the IoT and Machine Learning focuses on all these topics, including a few case studies, and they give a clear indication as to why these techniques should now be widely adopted by the agriculture and farming industries.

Despite the increasing population (the Food and Agriculture Organization of the United Nations estimates 70% more food will be needed in 2050 than was produced in 2006), issues related to food production have yet to be completely addressed. In recent years, Internet of Things technology has begun to be used to address different industrial and technical challenges to meet this growing need. These Agro-IoT tools boost productivity and minimize the pitfalls of traditional farming, which is the backbone of the world''s economy. Aided by the IoT, continuous monitoring of fields provides useful and critical information to farmers, ushering in a new era in farming. The IoT can be used as a tool to combat climate change through greenhouse automation; monitor and manage water, soil and crops; increase productivity; control insecticides/pesticides; detect plant diseases; increase the rate of crop sales; cattle monitoring etc.

Agricultural Informatics: Automation Using the IoT and Machine Learning focuses on all these topics, including a few case studies, and they give a clear indication as to why these techniques should now be widely adopted by the agriculture and farming industries.

This book provides comprehensive coverage of the major aspects in designing, implementing, and deploying wireless sensor networks by discussing present research on WSNs and their applications in various disciplines. It familiarizes readers with the current state of WSNs and how such networks can be improved to achieve effectiveness and efficiency. It starts with a detailed introduction of wireless sensor networks and their applications and proceeds with layered architecture of WSNs. It also addresses prominent issues such as mobility, heterogeneity, fault-tolerance, intermittent connectivity, and cross layer optimization along with a number of existing solutions to stimulate future research.

This book provides comprehensive coverage of the major aspects in designing, implementing, and deploying wireless sensor networks by discussing present research on WSNs and their applications in various disciplines. It familiarizes readers with the current state of WSNs and how such networks can be improved to achieve effectiveness and efficiency. It starts with a detailed introduction of wireless sensor networks and their applications and proceeds with layered architecture of WSNs. It also addresses prominent issues such as mobility, heterogeneity, fault-tolerance, intermittent connectivity, and cross layer optimization along with a number of existing solutions to stimulate future research.

This volume helps to address the genuine 21st century need for advances in data science and computing technology. It provides an abundance of new research and studies on progressive and innovative technologies, including artificial intelligence, communication systems, cyber security applications, data analytics, Internet of Things (IoT), machine learning, power systems, VLSI, embedded systems, and much more. The book presents a variety of interesting and important aspects of data science and computing technologies and methodologies in a wide range of applications, including deep learning, DNA cryptography, classy fuzzy MPPT controller, driving assistance, and safety systems. Novel algorithms and their applications for solving cutting-edge computational and data science problems are included also for an interdisciplinary research perspective.

The book addresses recent applications of deep learning and ANN paradigms, the role and impact of big data in the e-commerce and retail sectors, algorithms for load balancing in cloud computing, advances in embedded system based applications, optimization techniques using a MATLAB platform, and techniques for improving information and network security.

Advances in Data Science and Computing Technology: Methodology and Applications provides a wealth of valuable information and food for thought on many important issues for data scientists and researchers, industry professionals, and faculty and students in the data and computing sciences.

This volume helps to address the genuine 21st century need for advances in data science and computing technology. It provides an abundance of new research and studies on progressive and innovative technologies, including artificial intelligence, communication systems, cyber security applications, data analytics, Internet of Things (IoT), machine learning, power systems, VLSI, embedded systems, and much more. The book presents a variety of interesting and important aspects of data science and computing technologies and methodologies in a wide range of applications, including deep learning, DNA cryptography, classy fuzzy MPPT controller, driving assistance, and safety systems. Novel algorithms and their applications for solving cutting-edge computational and data science problems are included also for an interdisciplinary research perspective.

The book addresses recent applications of deep learning and ANN paradigms, the role and impact of big data in the e-commerce and retail sectors, algorithms for load balancing in cloud computing, advances in embedded system based applications, optimization techniques using a MATLAB platform, and techniques for improving information and network security.

Advances in Data Science and Computing Technology: Methodology and Applications provides a wealth of valuable information and food for thought on many important issues for data scientists and researchers, industry professionals, and faculty and students in the data and computing sciences.

The mushrooming of illegal housing on the periphery of cities is one of the main consequences of rapid urbanisation associated with social and environmental problems in the developing countries. Sustainable Urbanism in Developing Countries discusses the linkage between urbanism and sustainability and how sustainable urbanism can be implemented to overcome the problems of housing and living conditions in urban areas. Through case studies from India, Indonesia, China, etc., using advanced GIS techniques, this book analyses several planning and design criteria to solve the physical, social, and economic problems of urbanisation and refers to urban planning as an effective measure to protect and promote the cultural characteristics of specific locations in these developing countries.

FEATURES

The mushrooming of illegal housing on the periphery of cities is one of the main consequences of rapid urbanisation associated with social and environmental problems in the developing countries. Sustainable Urbanism in Developing Countries discusses the linkage between urbanism and sustainability and how sustainable urbanism can be implemented to overcome the problems of housing and living conditions in urban areas. Through case studies from India, Indonesia, China, etc., using advanced GIS techniques, this book analyses several planning and design criteria to solve the physical, social, and economic problems of urbanisation and refers to urban planning as an effective measure to protect and promote the cultural characteristics of specific locations in these developing countries.

FEATURES

While technology is developing at a fast pace, urban planners and cities are still behind in finding effective ways to use technology to address citizen’s needs. Multiple aspects of sustainable urbanism are brought together in this book, along with advanced technologies and their connections to urban planning and management. It integrates urban studies, smart cities, AI, IoT, remote sensing, and GIS. Highlights include land use planning, spatial planning, and ecosystem-based information to improve economic opportunities. Urban planners and engineers will understand the use of AI in disaster management and the use of GIS in finding suitable landfill sites for sustainable waste management.

Features

While technology is developing at a fast pace, urban planners and cities are still behind in finding effective ways to use technology to address citizen’s needs. Multiple aspects of sustainable urbanism are brought together in this book, along with advanced technologies and their connections to urban planning and management. It integrates urban studies, smart cities, AI, IoT, remote sensing, and GIS. Highlights include land use planning, spatial planning, and ecosystem-based information to improve economic opportunities. Urban planners and engineers will understand the use of AI in disaster management and the use of GIS in finding suitable landfill sites for sustainable waste management.

Features

Computational Intelligence for Wireless Sensor Networks: Principles and Applications provides an integrative overview of the computational intelligence (CI) in wireless sensor networks and enabled technologies. It aims to demonstrate how the paradigm of computational intelligence can benefit Wireless Sensor Networks (WSNs) and sensor-enabled technologies to overcome their existing issues.

This book provides extensive coverage of the multiple design challenges of WSNs and associated technologies such as clustering, routing, media access, security, mobility, and design of energy-efficient network operations.

It also describes various CI strategies such as fuzzy computing, evolutionary computing, reinforcement learning, artificial intelligence, swarm intelligence, teaching learning-based optimization, etc. It also discusses applying the techniques mentioned above in wireless sensor networks and sensor-enabled technologies to improve their design.

The book offers comprehensive coverage of related topics, including:

This book mainly addresses the challenges pertaining to the development of intelligent network systems via computational intelligence. It provides insights into how intelligence has been pursued and can be further integrated in the development of sensor-enabled applications.

Computational Intelligence for Wireless Sensor Networks: Principles and Applications provides an integrative overview of the computational intelligence (CI) in wireless sensor networks and enabled technologies. It aims to demonstrate how the paradigm of computational intelligence can benefit Wireless Sensor Networks (WSNs) and sensor-enabled technologies to overcome their existing issues.

This book provides extensive coverage of the multiple design challenges of WSNs and associated technologies such as clustering, routing, media access, security, mobility, and design of energy-efficient network operations.

It also describes various CI strategies such as fuzzy computing, evolutionary computing, reinforcement learning, artificial intelligence, swarm intelligence, teaching learning-based optimization, etc. It also discusses applying the techniques mentioned above in wireless sensor networks and sensor-enabled technologies to improve their design.

The book offers comprehensive coverage of related topics, including:

This book mainly addresses the challenges pertaining to the development of intelligent network systems via computational intelligence. It provides insights into how intelligence has been pursued and can be further integrated in the development of sensor-enabled applications.

This book explores the discourse on urban and regional inequality within the framework of neoliberalism. It analyzes the widespread application of neoliberal policies in Asian city regions and identifies their influence on rising inequality. The book captures inequality through spatial and non-spatial policy narratives with empirical evidence from India, Japan, South Korea, Taiwan, and Thailand. The book uses analytics, narratives and simulation to unfold the opportunities and threats to urban regions that bear the impacts of globalization and neoliberal policies.

Lucid and topical, this book will be an essential read for scholars and researchers of urban economics, urban and regional planning, urban studies, urban sociology, political economy, public policy, governance, development studies and Asian economy.

This book explores the discourse on urban and regional inequality within the framework of neoliberalism. It analyzes the widespread application of neoliberal policies in Asian city regions and identifies their influence on rising inequality. The book captures inequality through spatial and non-spatial policy narratives with empirical evidence from India, Japan, South Korea, Taiwan, and Thailand. The book uses analytics, narratives and simulation to unfold the opportunities and threats to urban regions that bear the impacts of globalization and neoliberal policies.

Lucid and topical, this book will be an essential read for scholars and researchers of urban economics, urban and regional planning, urban studies, urban sociology, political economy, public policy, governance, development studies and Asian economy.

Despite the increasing population (the Food and Agriculture Organization of the United Nations estimates 70% more food will be needed in 2050 than was produced in 2006), issues related to food production have yet to be completely addressed. In recent years, Internet of Things technology has begun to be used to address different industrial and technical challenges to meet this growing need. These Agro-IoT tools boost productivity and minimize the pitfalls of traditional farming, which is the backbone of the world''s economy. Aided by the IoT, continuous monitoring of fields provides useful and critical information to farmers, ushering in a new era in farming. The IoT can be used as a tool to combat climate change through greenhouse automation; monitor and manage water, soil and crops; increase productivity; control insecticides/pesticides; detect plant diseases; increase the rate of crop sales; cattle monitoring etc.

Agricultural Informatics: Automation Using the IoT and Machine Learning focuses on all these topics, including a few case studies, and they give a clear indication as to why these techniques should now be widely adopted by the agriculture and farming industries.

Despite the increasing population (the Food and Agriculture Organization of the United Nations estimates 70% more food will be needed in 2050 than was produced in 2006), issues related to food production have yet to be completely addressed. In recent years, Internet of Things technology has begun to be used to address different industrial and technical challenges to meet this growing need. These Agro-IoT tools boost productivity and minimize the pitfalls of traditional farming, which is the backbone of the world''s economy. Aided by the IoT, continuous monitoring of fields provides useful and critical information to farmers, ushering in a new era in farming. The IoT can be used as a tool to combat climate change through greenhouse automation; monitor and manage water, soil and crops; increase productivity; control insecticides/pesticides; detect plant diseases; increase the rate of crop sales; cattle monitoring etc.

Agricultural Informatics: Automation Using the IoT and Machine Learning focuses on all these topics, including a few case studies, and they give a clear indication as to why these techniques should now be widely adopted by the agriculture and farming industries.