AI and data-driven methods, particularly machine and deep learning models, have revolutionized image processing tasks such as object detection and segmentation, as well as inverse sensing tasks such as atmospheric condition monitoring. These models enable highly accurate predictions from large, labelled datasets. However, one of the key challenges with current AI systems is their opacity. While they deliver precise results, they often fail to provide clear insights into the underlying mechanisms driving these predictions. The lack of interpretability, especially in the context of sensing data, complicates the understanding of how internal features are represented and utilized. This issue is particularly pronounced in smart environment applications, where artificial intelligence techniques are increasingly employed, yet their internal workings remain largely opaque.In this edited book, the contributors explore the potential of machine intelligence, deep learning and sensing technologies, with a focus on their integration and applications. They present new methods, cutting-edge technologies and practical solutions to real-world challenges. The goal is to help readers better grasp the concepts necessary for designing and deploying the next generation of smarter and more sustainable systems and environments.The Convergence of AI, IoT, Smart Sensors and Remote Sensing for Sustainable Smart Environment Applications is a useful reference for researchers, engineers and scientists in academia and industry, as well as advanced students in the fields of data science and security, AI and networking, communication engineering, smart sensing, remote sensing and automation. It will also be of interest to system designers and developers of AI and sensing technologies for smart environment applications.

This book discusses the potential of the Internet of Unmanned Things (IoUT), which is considered a promising paradigm resulting in numerous applications including shipment of goods, home package delivery, crop monitoring, agricultural surveillance, and rescue operations. The authors discuss how IoUT nodes collaborate with each other in ad hoc manner through a Line-of-Sight (LoS) link to exchange data packets. Also discussed is how Unmanned Arial Vehicles (UAVs) can communicate with fixed ground stations, with an air traffic controller, or through a Non-Line-of-Sight (NLoS) link with a satellite-aided controller, generally based on preloaded missions. The authors go on to cover how to tackle issues that arise with dissimilar communication technologies. They cover how various problems can appear in inter-UAV and UAV-to-X communications including energy management, lack of security and the unreliability of wireless communication links, and handover from LoS to NLoS, and vice versa. In this book, the editors invited front-line researchers and authors to submit research exploring emerging technologies for IoUT and mission-based networking and how to overcome challenges.

This book discusses the potential of the Internet of Unmanned Things (IoUT), which is considered a promising paradigm resulting in numerous applications including shipment of goods, home package delivery, crop monitoring, agricultural surveillance, and rescue operations. The authors discuss how IoUT nodes collaborate with each other in ad hoc manner through a Line-of-Sight (LoS) link to exchange data packets. Also discussed is how Unmanned Arial Vehicles (UAVs) can communicate with fixed ground stations, with an air traffic controller, or through a Non-Line-of-Sight (NLoS) link with a satellite-aided controller, generally based on preloaded missions. The authors go on to cover how to tackle issues that arise with dissimilar communication technologies. They cover how various problems can appear in inter-UAV and UAV-to-X communications including energy management, lack of security and the unreliability of wireless communication links, and handover from LoS to NLoS, and vice versa. In this book, the editors invited front-line researchers and authors to submit research exploring emerging technologies for IoUT and mission-based networking and how to overcome challenges.

This book discusses the potential of the Internet of Unmanned Things (IoUT), which is considered a promising paradigm resulting in numerous applications including shipment of goods, home package delivery, crop monitoring, agricultural surveillance, and rescue operations. The authors discuss how IoUT nodes collaborate with each other in ad hoc manner through a Line-of-Sight (LoS) link to exchange data packets. Also discussed is how Unmanned Arial Vehicles (UAVs) can communicate with fixed ground stations, with an air traffic controller, or through a Non-Line-of-Sight (NLoS) link with a satellite-aided controller, generally based on preloaded missions. The authors go on to cover how to tackle issues that arise with dissimilar communication technologies. They cover how various problems can appear in inter-UAV and UAV-to-X communications including energy management, lack of security and the unreliability of wireless communication links, and handover from LoS to NLoS, and vice versa. In this book, the editors invited front-line researchers and authors to submit research exploring emerging technologies for IoUT and mission-based networking and how to overcome challenges.

This book focuses on the benefits of mobile crowdsensing (MCS) and remote sensing applications in smart cities, particularly in creating an intelligent context-aware environment, especially in cases of infectious diseases that cause widespread loss of life. The authors first introduce the concepts of MCS and remote sensing in smart cities. The authors go on to discuss topics such as power of mobile edge and cloud computing for data analytics; strategies to effectively manage and mitigate data redundancy; crowd management during the Covid-19 pandemic; techniques to detect communities in complex data through social sensing; and much more. The authors also aim to show that the efficient implementation of MCS and remote sensing in various applications comes with several challenging issues that need to be addressed, including data quality and reliability, security and privacy, and ethical considerations.Focuses on the benefits of mobile crowdsensing (MCS) and remote sensing applications in smart cities;Covers technical details of remote sensing starting from the communication support to the application;Includes overcoming challenges including data quality and reliability, security and privacy, and ethical considerations.

This book focuses on the benefits of mobile crowdsensing (MCS) and remote sensing applications in smart cities, particularly in creating an intelligent context-aware environment, especially in cases of infectious diseases that cause widespread loss of life. The authors first introduce the concepts of MCS and remote sensing in smart cities. The authors go on to discuss topics such as power of mobile edge and cloud computing for data analytics; strategies to effectively manage and mitigate data redundancy; crowd management during the Covid-19 pandemic; techniques to detect communities in complex data through social sensing; and much more. The authors also aim to show that the efficient implementation of MCS and remote sensing in various applications comes with several challenging issues that need to be addressed, including data quality and reliability, security and privacy, and ethical considerations.

Focuses on the benefits of mobile crowdsensing (MCS) and remote sensing applications in smart cities;Covers technical details of remote sensing starting from the communication support to the application;Includes overcoming challenges including data quality and reliability, security and privacy, and ethical considerations.

AI and data-driven methods, particularly machine and deep learning models, have revolutionized image processing tasks such as object detection and segmentation, as well as inverse sensing tasks such as atmospheric condition monitoring. These models enable highly accurate predictions from large, labelled datasets. However, one of the key challenges with current AI systems is their opacity. While they deliver precise results, they often fail to provide clear insights into the underlying mechanisms driving these predictions. The lack of interpretability, especially in the context of sensing data, complicates the understanding of how internal features are represented and utilized. This issue is particularly pronounced in smart environment applications, where artificial intelligence techniques are increasingly employed, yet their internal workings remain largely opaque.In this edited book, the contributors explore the potential of machine intelligence, deep learning and sensing technologies, with a focus on their integration and applications. They present new methods, cutting-edge technologies and practical solutions to real-world challenges. The goal is to help readers better grasp the concepts necessary for designing and deploying the next generation of smarter and more sustainable systems and environments.The Convergence of AI, IoT, Smart Sensors and Remote Sensing for Sustainable Smart Environment Applications is a useful reference for researchers, engineers and scientists in academia and industry, as well as advanced students in the fields of data science and security, AI and networking, communication engineering, smart sensing, remote sensing and automation. It will also be of interest to system designers and developers of AI and sensing technologies for smart environment applications.

This book discusses the potential of the Internet of Unmanned Things (IoUT), which is considered a promising paradigm resulting in numerous applications including shipment of goods, home package delivery, crop monitoring, agricultural surveillance, and rescue operations. The authors discuss how IoUT nodes collaborate with each other in ad hoc manner through a Line-of-Sight (LoS) link to exchange data packets. Also discussed is how Unmanned Arial Vehicles (UAVs) can communicate with fixed ground stations, with an air traffic controller, or through a Non-Line-of-Sight (NLoS) link with a satellite-aided controller, generally based on preloaded missions. The authors go on to cover how to tackle issues that arise with dissimilar communication technologies. They cover how various problems can appear in inter-UAV and UAV-to-X communications including energy management, lack of security and the unreliability of wireless communication links, and handover from LoS to NLoS, and vice versa. In this book, the editors invited front-line researchers and authors to submit research exploring emerging technologies for IoUT and mission-based networking and how to overcome challenges.

This book discusses the potential of the Internet of Unmanned Things (IoUT), which is considered a promising paradigm resulting in numerous applications including shipment of goods, home package delivery, crop monitoring, agricultural surveillance, and rescue operations. The authors discuss how IoUT nodes collaborate with each other in ad hoc manner through a Line-of-Sight (LoS) link to exchange data packets. Also discussed is how Unmanned Arial Vehicles (UAVs) can communicate with fixed ground stations, with an air traffic controller, or through a Non-Line-of-Sight (NLoS) link with a satellite-aided controller, generally based on preloaded missions. The authors go on to cover how to tackle issues that arise with dissimilar communication technologies. They cover how various problems can appear in inter-UAV and UAV-to-X communications including energy management, lack of security and the unreliability of wireless communication links, and handover from LoS to NLoS, and vice versa. In this book, the editors invited front-line researchers and authors to submit research exploring emerging technologies for IoUT and mission-based networking and how to overcome challenges.

This book discusses the potential of the Internet of Unmanned Things (IoUT), which is considered a promising paradigm resulting in numerous applications including shipment of goods, home package delivery, crop monitoring, agricultural surveillance, and rescue operations. The authors discuss how IoUT nodes collaborate with each other in ad hoc manner through a Line-of-Sight (LoS) link to exchange data packets. Also discussed is how Unmanned Arial Vehicles (UAVs) can communicate with fixed ground stations, with an air traffic controller, or through a Non-Line-of-Sight (NLoS) link with a satellite-aided controller, generally based on preloaded missions. The authors go on to cover how to tackle issues that arise with dissimilar communication technologies. They cover how various problems can appear in inter-UAV and UAV-to-X communications including energy management, lack of security and the unreliability of wireless communication links, and handover from LoS to NLoS, and vice versa. In this book, the editors invited front-line researchers and authors to submit research exploring emerging technologies for IoUT and mission-based networking and how to overcome challenges.

This book focuses on the benefits of mobile crowdsensing (MCS) and remote sensing applications in smart cities, particularly in creating an intelligent context-aware environment, especially in cases of infectious diseases that cause widespread loss of life. The authors first introduce the concepts of MCS and remote sensing in smart cities. The authors go on to discuss topics such as power of mobile edge and cloud computing for data analytics; strategies to effectively manage and mitigate data redundancy; crowd management during the Covid-19 pandemic; techniques to detect communities in complex data through social sensing; and much more. The authors also aim to show that the efficient implementation of MCS and remote sensing in various applications comes with several challenging issues that need to be addressed, including data quality and reliability, security and privacy, and ethical considerations.Focuses on the benefits of mobile crowdsensing (MCS) and remote sensing applications in smart cities;Covers technical details of remote sensing starting from the communication support to the application;Includes overcoming challenges including data quality and reliability, security and privacy, and ethical considerations.

This book focuses on the benefits of mobile crowdsensing (MCS) and remote sensing applications in smart cities, particularly in creating an intelligent context-aware environment, especially in cases of infectious diseases that cause widespread loss of life. The authors first introduce the concepts of MCS and remote sensing in smart cities. The authors go on to discuss topics such as power of mobile edge and cloud computing for data analytics; strategies to effectively manage and mitigate data redundancy; crowd management during the Covid-19 pandemic; techniques to detect communities in complex data through social sensing; and much more. The authors also aim to show that the efficient implementation of MCS and remote sensing in various applications comes with several challenging issues that need to be addressed, including data quality and reliability, security and privacy, and ethical considerations.

Focuses on the benefits of mobile crowdsensing (MCS) and remote sensing applications in smart cities;Covers technical details of remote sensing starting from the communication support to the application;Includes overcoming challenges including data quality and reliability, security and privacy, and ethical considerations.