Anjali Raghav – författare

The book provides a complete overview of forensic science, AI, and data management in law and business. It reviews the applications of AI and advanced data management methods across various legal and forensic domains. Topics discussed include digital forensics, predictive modelling, automatic classification, anomaly detection, cold case analysis, metadata analysis, and pattern recognition using blockchain technology.The book explores the cutting-edge intersection of fields such as ethical AI in legal systems, forensic science, data privacy, and forensic accounting laws. It examines the ethical implications of integrating computational intelligence including AI and machine learning into legal and judicial systems. The challenges and opportunities of applying AI to decision-making in human rights contexts are analysed, with emphasis on transparency, accountability, and fairness in algorithmic decision-making within legal frameworks.Further, it evaluates the intersection of data privacy and human rights with respect to biometric data collection, discussing the implications of mass surveillance, data harvesting, and profiling on individual privacy and civil liberties. The book also investigates how computational intelligence can be used to analyse large-scale datasets and enhance legal research and decision-making within the framework of human rights and the rule of law.Key Features:Studies the use of AI in criminal scene managementReviews the use of AI in data handlingReviews anomaly detection in companiesEvaluated the use of AI in legal assistanceCovers emotion and sentiment analysis by AI in criminal matters.

This edited book represents a groundbreaking effort to illustrate how artificial intelligence (AI) shapes the future of agrifood systems in terms of sustainability and resilience. As the global food system faces challenges like climate change, depletion of water and biodiversity and increases in population and consumption, this book is the first comprehensive review of how systems utilizing artificial intelligence can help solve these important challenges. The chapters cover themes from precision farming to crop monitoring, predictive modeling and smart irrigation, offering real-world insights and interdisciplinary perspectives on the transformative potential of AI for agri-tech. This volume brings together contributions from leading experts, researchers and practitioners in agriculture, technology, and policy, illuminating case studies, scalable innovations, and ethical implications. It explores the socio-economic implications of AI adoption in farming communities, emphasizing the need for innovation to be driven by principles of equity and environmental stewardship. This book provides bold visions as well as practical approaches, such as developing and implementing AI tools to craft policy frameworks, to revolutionize agri-food systems for a more sustainable, food-secure future.

The emergence of global terrorism has led to new, innovative artificial intelligence (AI) and deep learning techniques for effective counterterrorism. This book explores the transformative role of AI and deep learning in combating global terrorism, providing a comprehensive analysis of how these technologies can safeguard nations and societies. It presents strategies for utilizing AI and deep learning in intelligence gathering, predictive analysis, surveillance, and threat detection. The book examines the use of machine learning algorithms to analyze vast amounts of data, identifying patterns and trends to anticipate potential terrorist activities. It highlights how AI-powered systems enhance counterterrorism operations, real-time responses, and decision-making processes. Offering technical insights and practical applications, this book will appeal to students, researchers, and scholars of security studies, international relations, law, and political science, as well as to policymakers, and security professionals interested in a forward-thinking approach to combating terrorism in an interconnected world.