Internet of Things and AI for Natural Disaster Management and Prediction - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Internet of Things and AI for Natural Disaster Management and Prediction write by Satishkumar, D.. This book was released on 2024-03-07. Internet of Things and AI for Natural Disaster Management and Prediction available in PDF, EPUB and Kindle. In a world where natural disasters wreak havoc with increasing frequency and severity, the need for accurate prediction and effective management has never been more critical. From earthquakes shattering communities to floods submerging vast regions, these events endanger lives and strain resources and infrastructure to their limits. Yet, amidst this turmoil, traditional forecasting methods often need to catch up, leaving us vulnerable and reactive rather than proactive. This comprehensive academic collection provides a beacon of hope in uncertain circumstances: Internet of Things and AI for Natural Disaster Management and Prediction. By bridging the gap between theory and practice, this book empowers academics, policymakers, and practitioners alike to harness the full potential of machine learning in safeguarding lives and livelihoods.
AI and IoT for Proactive Disaster Management
AI and IoT for Proactive Disaster Management - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook AI and IoT for Proactive Disaster Management write by Ouaissa, Mariyam. This book was released on 2024-05-06. AI and IoT for Proactive Disaster Management available in PDF, EPUB and Kindle. In our rapidly evolving digital landscape, the threat of natural disasters looms large, necessitating innovative solutions for effective disaster management. Integrating Artificial Intelligence (AI) and the Internet of Things (IoT) presents a transformative approach to addressing these challenges. However, despite the potential benefits, the field needs more comprehensive resources that explore the full extent of AI and IoT applications in disaster management. AI and IoT for Proactive Disaster Management fills that gap by examining how AI and IoT can revolutionize disaster preparedness, response, and recovery. It offers a deep dive into AI frameworks, IoT infrastructures, and the synergy of these technologies in predicting and managing natural disasters. Ideal for undergraduate and postgraduate students, academicians, research scholars, industry professionals, and technology enthusiasts, this book serves as a comprehensive guide to understanding the intersection of AI, IoT, and disaster management. By showcasing cutting-edge research and practical applications, this book equips readers with the knowledge and tools to harness AI and IoT for more efficient and effective disaster management strategies.
Utilizing AI and Machine Learning for Natural Disaster Management
Utilizing AI and Machine Learning for Natural Disaster Management - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Utilizing AI and Machine Learning for Natural Disaster Management write by Satishkumar, D.. This book was released on 2024-04-29. Utilizing AI and Machine Learning for Natural Disaster Management available in PDF, EPUB and Kindle. Acute events of natural origin, spanning atmospheric, biological, geophysical, hydrologic, and oceanographic realms, persistently menace societies globally. Approximately 160 million people annually bear the brunt of these disasters, with certain regions facing disproportionate impacts. The lack of predictability intensifies the challenge, creating intercommunal capacity gaps and amplifying the dire consequences. Utilizing AI and Machine Learning for Natural Disaster Management provides instances of ML in predicting earthquakes. By leveraging seismic data, AI systems can analyze magnitude and patterns, providing invaluable insights to forecast earthquake occurrences and aftershocks. Similarly, the book unveils the potential of ML in simulating floods by recording and analyzing rainfall patterns from previous years. The predictive power extends to hurricanes, where data on wind speed, rainfall, temperature, and moisture converge to anticipate future occurrences, potentially saving millions in property damage.
Predicting Natural Disasters With AI and Machine Learning
Predicting Natural Disasters With AI and Machine Learning - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Predicting Natural Disasters With AI and Machine Learning write by Satishkumar, D.. This book was released on 2024-02-16. Predicting Natural Disasters With AI and Machine Learning available in PDF, EPUB and Kindle. In a world where the relentless force of natural and man-made disasters threatens societies, the need for effective disaster management has never been more critical. Predicting Natural Disasters With AI and Machine Learning addresses the challenges of disasters and charts a path toward proactive solutions by applying artificial intelligence (AI) and machine learning (ML). This book begins by interpreting the nature of disasters, clearly distinguishing between natural and man-made hazards. It delves into the intricacies of disaster risk reduction (DRR), emphasizing the human contribution to most disasters. Recognizing the necessity for a multifaceted approach, the book advocates the four ‘R’s - Risk Mitigation, Response Readiness, Response Execution, and Recovery - as integral components of comprehensive disaster management. This book explores various AI and ML applications designed to predict, manage, and mitigate the impact of natural disasters, focusing on natural language processing, and early warning systems. The contrast between weak AI, simulating human intelligence for specific tasks, and strong AI, capable of autonomous problem-solving, is thoroughly examined in the context of disaster management. Its chapters systematically address critical issues, including real-world data handling, challenges related to data accessibility, completeness, security, privacy, and ethical considerations.
Reshaping Environmental Science Through Machine Learning and IoT
Reshaping Environmental Science Through Machine Learning and IoT - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Reshaping Environmental Science Through Machine Learning and IoT write by Rajeev Kumar Gupta. This book was released on 2024. Reshaping Environmental Science Through Machine Learning and IoT available in PDF, EPUB and Kindle. In the face of escalating environmental challenges such as climate change, air and water pollution, and natural disasters, traditional approaches to understanding and addressing these issues have yet to be proven sufficient. Academic scholars are compelled to seek innovative solutions that marry digital intelligence and natural ecosystems. Reshaping Environmental Science Through Machine Learning and IoT serves as a comprehensive exploration into the transformative potential of Machine Learning (ML) and the Internet of Things (IoT) to address critical environmental challenges. The book establishes a robust foundation in ML and IoT, explaining their relevance to environmental science. As the narrative unfolds, it delves into diverse applications, providing theoretical insights alongside practical knowledge. From interpreting weather patterns to predicting air and water quality, the book navigates through the intricate web of environmental complexities. Notably, it unveils approaches to disaster management, waste sorting, and climate change monitoring, showcasing the symbiotic relationship between digital intelligence and natural ecosystems. This book is ideal for audiences from students and researchers to data scientists and disaster management professionals with a nuanced understanding of IoT, ML, and Artificial Intelligence (AI). It systematically addresses fundamental principles, components, and real-world applications in environmental sciences. It extends to practical applications, illuminating how IoT can interpret weather patterns, predict air and water quality, and guide resource allocation based on pollution data. The chapters span various topics, encompassing time series forecasting, remote sensing, anomaly detection, and AI-driven solutions for predicting climate behavior.
