S Vijayalakshmi – författare

The future policing ought to cover identification of new assaults, disclosure of new ill-disposed patterns, and forecast of any future vindictive patterns from accessible authentic information. Such keen information will bring about building clever advanced proof handling frameworks that will help cops investigate violations. Artificial Intelligence for Cyber Defense and Smart Policing will describe the best way of practicing artificial intelligence for cyber defense and smart policing.

Salient Features:

Combines AI for both cyber defense and smart policing in one place Covers novel strategies in future to help cybercrime examinations and police Discusses different AI models to fabricate more exact techniques Elaborates on problematization and international issues Includes case studies and real-life examples

This book is primarily aimed at graduates, researchers, and IT professionals. Business executives will also find this book helpful.

The future policing ought to cover identification of new assaults, disclosure of new ill-disposed patterns, and forecast of any future vindictive patterns from accessible authentic information. Such keen information will bring about building clever advanced proof handling frameworks that will help cops investigate violations. Artificial Intelligence for Cyber Defense and Smart Policing will describe the best way of practicing artificial intelligence for cyber defense and smart policing.

Salient Features:

Combines AI for both cyber defense and smart policing in one place Covers novel strategies in future to help cybercrime examinations and police Discusses different AI models to fabricate more exact techniques Elaborates on problematization and international issues Includes case studies and real-life examples

This book is primarily aimed at graduates, researchers, and IT professionals. Business executives will also find this book helpful.

The future policing ought to cover identification of new assaults, disclosure of new ill-disposed patterns, and forecast of any future vindictive patterns from accessible authentic information. Such keen information will bring about building clever advanced proof handling frameworks that will help cops investigate violations. Artificial Intelligence for Cyber Defense and Smart Policing will describe the best way of practicing artificial intelligence for cyber defense and smart policing.Salient Features:Combines AI for both cyber defense and smart policing in one placeCovers novel strategies in future to help cybercrime examinations and policeDiscusses different AI models to fabricate more exact techniquesElaborates on problematization and international issuesIncludes case studies and real-life examplesThis book is primarily aimed at graduates, researchers, and IT professionals. Business executives will also find this book helpful.

The future policing ought to cover identification of new assaults, disclosure of new ill-disposed patterns, and forecast of any future vindictive patterns from accessible authentic information. Such keen information will bring about building clever advanced proof handling frameworks that will help cops investigate violations. Artificial Intelligence for Cyber Defense and Smart Policing will describe the best way of practicing artificial intelligence for cyber defense and smart policing.Salient Features:Combines AI for both cyber defense and smart policing in one placeCovers novel strategies in future to help cybercrime examinations and policeDiscusses different AI models to fabricate more exact techniquesElaborates on problematization and international issuesIncludes case studies and real-life examplesThis book is primarily aimed at graduates, researchers, and IT professionals. Business executives will also find this book helpful.

Smart Systems for Disease Prediction: Advancements, Applications and Challenges is a comprehensive book that explores the use of intelligent technologies to predict diseases accurately and efficiently. It covers a wide range of topics, including image and signal processing, behavioural analysis, and the integration of multimodal data in healthcare. The book examines the application of artificial intelligence, machine learning, and data analytics in creating predictive models for diseases. It also addresses the challenges, ethical considerations, and future directions in the field. This work emphasises the significant impact of intelligent systems on enabling early diagnosis, personalised medicine, and improving patient outcomes.

Smart Systems for Disease Prediction: Advancements, Applications and Challenges is a comprehensive book that explores the use of intelligent technologies to predict diseases accurately and efficiently. It covers a wide range of topics, including image and signal processing, behavioural analysis, and the integration of multimodal data in healthcare. The book examines the application of artificial intelligence, machine learning, and data analytics in creating predictive models for diseases. It also addresses the challenges, ethical considerations, and future directions in the field. This work emphasises the significant impact of intelligent systems on enabling early diagnosis, personalised medicine, and improving patient outcomes.

Smart Systems for Disease Prediction: Advancements, Applications and Challenges is a comprehensive book that explores the use of intelligent technologies to predict diseases accurately and efficiently. It covers a wide range of topics, including image and signal processing, behavioural analysis, and the integration of multimodal data in healthcare. The book examines the application of artificial intelligence, machine learning, and data analytics in creating predictive models for diseases. It also addresses the challenges, ethical considerations, and future directions in the field. This work emphasises the significant impact of intelligent systems on enabling early diagnosis, personalised medicine, and improving patient outcomes.

This book presents the recent and multidisciplinary concepts of disruptive technologies, emerging technologies and design thinking. These themes enable the readers to enhance their creativity and innovation, and explore a human-centered approach for improved problem-solving. As the articles presented here are the extended, selected best outcome of the conference titled IACIDS, the book promotes collaboration and exchange of ideas among the authors and readers. The scope of these technologies in the current world is vast and continues to grow as organizations across various industries recognize the value of adopting a design-led approach to innovation. Disruptive technologies have a significant impact on the existing industries and often create new ones, leading to increased productivity, efficiency, and innovation. The importance of disruptive technologies in the current world can be seen in several way such as driving economic growth, improving quality of life, driving innovation, thus shaping the future. Design thinking is being applied in various domains such as product design, service design, user experience design, organizational design, and societal design. It is also increasingly being used in fields such as healthcare, education, and government to create more effective and efficient systems. One of the key advantages of design thinking is its ability to bring together diverse perspectives and disciplines, which allows for a more comprehensive understanding of a problem and the development of more innovative solutions. As a result, design thinking is becoming an important tool for organizations looking to drive innovation, increase efficiency, and improve customer satisfaction.

AI-Powered IoT in the Energy Industry: Digital Technology and Sustainable Energy Systems looks at opportunities to employ cutting-edge applications of artificial intelligence (AI), the Internet of Things (IoT), and Machine Learning (ML) in designing and modeling energy and renewable energy systems. The book's main objectives are to demonstrate how big data can help with energy efficiency and demand reduction, increase the usage of renewable energy sources, and assist in transitioning from a centralized system to a distributed, efficient, and embedded energy system. Contributions cover the fundamentals of the renewable energy sector, including solar, wind, biomass, and hydrogen, as well as building services and power generation systems. Chapters also examine renewable energy property prediction methods and discuss AI and IoT prediction models for biomass thermal properties.​Covers renewable energy sector fundamentals;Explains the application of big data in distributed energy domains;Discusses AI and IoT prediction methods and models.

AI-Powered IoT in the Energy Industry: Digital Technology and Sustainable Energy Systems looks at opportunities to employ cutting-edge applications of artificial intelligence (AI), the Internet of Things (IoT), and Machine Learning (ML) in designing and modeling energy and renewable energy systems. The book''s main objectives are to demonstrate how big data can help with energy efficiency and demand reduction, increase the usage of renewable energy sources, and assist in transitioning from a centralized system to a distributed, efficient, and embedded energy system. Contributions cover the fundamentals of the renewable energy sector, including solar, wind, biomass, and hydrogen, as well as building services and power generation systems. Chapters also examine renewable energy property prediction methods and discuss AI and IoT prediction models for biomass thermal properties.

​Covers renewable energy sector fundamentals;Explains the application of big data in distributed energy domains;Discusses AI and IoT prediction methods and models.

 

 

AI-Powered IoT in the Energy Industry: Digital Technology and Sustainable Energy Systems looks at opportunities to employ cutting-edge applications of artificial intelligence (AI), the Internet of Things (IoT), and Machine Learning (ML) in designing and modeling energy and renewable energy systems. The book's main objectives are to demonstrate how big data can help with energy efficiency and demand reduction, increase the usage of renewable energy sources, and assist in transitioning from a centralized system to a distributed, efficient, and embedded energy system. Contributions cover the fundamentals of the renewable energy sector, including solar, wind, biomass, and hydrogen, as well as building services and power generation systems. Chapters also examine renewable energy property prediction methods and discuss AI and IoT prediction models for biomass thermal properties.​Covers renewable energy sector fundamentals;Explains the application of big data in distributed energy domains;Discusses AI and IoT prediction methods and models.

As the demand for electricity grows, the need for efficient and cleaner energy sources becomes increasingly critical. This book looks at the world of smart power systems, where artificial intelligence (AI) and the Internet of Things (IoT) are revolutionizing traditional power grids. This book covers a wide range of topics, starting with smart grid fundamentals, benefits, and deployment strategies. It explores power system models and the application of AI and IoT in power forecasting and the assembly of smart grids, the benefits and limitations of grid automation, and the use of machine-learning algorithms to identify equipment congestion. Efficient power distribution methods with AI-IoT and ML-based methodologies are explained, along with power quality checking, smart intelligence-based control, and intelligent power and energy management, as well as the role of blockchain technology in creating smart power systems and their potential impact. The book concludes by examining efficient methods for energy price prediction, secure e-payment solutions, fault detection in transmission lines using AI-based methods and algorithms, and optimized storage systems for energy. With practical case studies and real-world examples, this book will help students, researchers, and professionals in electrical engineering, power systems, and renewable energy expand their knowledge and skills in the emerging field of smart power systems and be at the forefront of the energy transition.

As the demand for electricity grows, the need for efficient and cleaner energy sources becomes increasingly critical. This book looks at the world of smart power systems, where artificial intelligence (AI) and the Internet of Things (IoT) are revolutionizing traditional power grids. This book covers a wide range of topics, starting with smart grid fundamentals, benefits, and deployment strategies. It explores power system models and the application of AI and IoT in power forecasting and the assembly of smart grids, the benefits and limitations of grid automation, and the use of machine-learning algorithms to identify equipment congestion. Efficient power distribution methods with AI-IoT and ML-based methodologies are explained, along with power quality checking, smart intelligence-based control, and intelligent power and energy management, as well as the role of blockchain technology in creating smart power systems and their potential impact. The book concludes by examining efficient methods for energy price prediction, secure e-payment solutions, fault detection in transmission lines using AI-based methods and algorithms, and optimized storage systems for energy. With practical case studies and real-world examples, this book will help students, researchers, and professionals in electrical engineering, power systems, and renewable energy expand their knowledge and skills in the emerging field of smart power systems and be at the forefront of the energy transition.

This book provides an in-depth exploration of Sustainable Development Goal 15: Life on Land. It delves into complex global issues related to environmental sustainability, human activity, and terrestrial ecosystems, examining the intricate connections between humanity and the land, with a focus on India, its neighboring nations, and collaborative efforts with Japan. The book aims to help readers understand the urgent need for conservation measures and the importance of sustainable land management and biodiversity-integrated urban planning. It discusses the diversity of flora and fauna and the crucial role of keystone species. Coverage includes topics such as climate change mitigation and education for sustainable practices. This unique guide sheds light on the fundamental connections between humanity and the land, equipping readers with the knowledge and tools to become proactive agents of change and take action to preserve our planet for future generations.