Utilizing AI and Machine Learning for Natural Disaster Management
Utilizing AI and Machine Learning for Natural Disaster Management

Author: Satishkumar, D.

Publisher: IGI Global

Published: 2024-04-29

Total Pages: 374

ISBN-13:

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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.

AI and Robotics in Disaster Studies
AI and Robotics in Disaster Studies

Author: T. V. Vijay Kumar

Publisher: Springer Nature

Published: 2020-10-12

Total Pages: 267

ISBN-13: 9811542910

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This book promotes a meaningful and appropriate dialogue and cross-disciplinary partnerships on Artificial Intelligence (AI) in governance and disaster management. The frequency and the cost of losses and damages due to disasters are rising every year. From wildfires to tsunamis, drought to hurricanes, floods to landslides combined with chemical, nuclear and biological disasters of epidemic proportions has increased human vulnerability and ecosystem sustainability. Life is not as it used to be and governance to manage disasters cannot be a business as usual. The quantum and proportion of responsibilities with the emergency services has increased many times to strain them beyond their human capacities. Its time that the struggling disaster management services get supported and facilitated by new technology of combining Artificial Intelligence (AI) and Machine Learning (ML) with Data Analytics Technologies (DAT)to serve people and government in disaster management. AI and ML have advanced to a state where they could be utilized for many operations in disaster risk reduction. Even though many disasters cannot be prevented and a number of them are blind natural disasters yet through an appropriate application of AI and ML quick predictions, vulnerability identification and classification of relief and rescue operations could be achieved.

Future Role of Sustainable Innovative Technologies in Crisis Management
Future Role of Sustainable Innovative Technologies in Crisis Management

Author: Ali, Mohammed

Publisher: IGI Global

Published: 2022-04-18

Total Pages: 280

ISBN-13: 1799898172

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The increasing use of innovative technologies by global businesses has sparked debate about their application in crisis resolution. Resolution tools can be used by global businesses to manage various types of crisis situations, such as natural disasters, information security issues, economic downturns, health crisis situations, and sustainability issues in education, among others. Further study and consideration of the uses of technology in the areas of crisis and change management and intra-company communication practice in the context of global business must be done to ensure successful and sustainable businesses. Future Role of Sustainable Innovative Technologies in Crisis Management raises awareness of the multifaceted field of new technology in crisis management that has resulted in a paradigm shift in the way contemporary industries and global businesses communicate and conduct their daily business operations. This book defines the scope of innovative technologies as the application of new technologies to support the resolution of various types of crisis situations to achieve regulatory compliance and improved risk management in an effective and automated manner. Covering topics such as sustainable business and disaster scenarios, this reference work is ideal for managers, entrepreneurs, researchers, academicians, scholars, practitioners, instructors, and students.

Internet of Things and AI for Natural Disaster Management and Prediction
Internet of Things and AI for Natural Disaster Management and Prediction

Author: Satishkumar, D.

Publisher: IGI Global

Published: 2024-03-07

Total Pages: 378

ISBN-13:

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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.

Disasters and Public Health
Disasters and Public Health

Author: Bruce W. Clements

Publisher: Butterworth-Heinemann

Published: 2016-02-23

Total Pages: 526

ISBN-13: 0128019891

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Disasters and Public Health: Planning and Response, Second Edition, examines the critical intersection between emergency management and public health. It provides a succinct overview of the actions that may be taken before, during, and after a major public health emergency or disaster to reduce morbidity and mortality. Five all-new chapters at the beginning of the book describe how policy and law drive program structures and strategies leading to the establishment and maintenance of preparedness capabilities. New topics covered in this edition include disaster behavioral health, which is often the most expensive and longest-term recovery challenge in a public health emergency, and community resilience, a valuable resource upon which most emergency programs and responses depend. The balance of the book provides an in-depth review of preparedness, response, and recovery challenges for 15 public health threats. These chapters also provide lessons learned from responses to each threat, giving users a well-rounded introduction to public health preparedness and response that is rooted in experience and practice. - Contains seven new chapters that cover law, vulnerable populations, behavioral health, community resilience, preparedness capabilities, emerging and re-emerging infectious diseases, and foodborne threats - Provides clinical updates by new MD co-author - Includes innovative preparedness approaches and lessons learned from current and historic public health and medical responses that enhance clarity and provide valuable examples to readers - Presents increased international content and case studies for a global perspective on public health

Predicting Natural Disasters With AI and Machine Learning
Predicting Natural Disasters With AI and Machine Learning

Author: Satishkumar, D.

Publisher: IGI Global

Published: 2024-02-16

Total Pages: 360

ISBN-13:

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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.

Disrupting Finance
Disrupting Finance

Author: Theo Lynn

Publisher: Springer

Published: 2018-12-06

Total Pages: 194

ISBN-13: 3030023303

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This open access Pivot demonstrates how a variety of technologies act as innovation catalysts within the banking and financial services sector. Traditional banks and financial services are under increasing competition from global IT companies such as Google, Apple, Amazon and PayPal whilst facing pressure from investors to reduce costs, increase agility and improve customer retention. Technologies such as blockchain, cloud computing, mobile technologies, big data analytics and social media therefore have perhaps more potential in this industry and area of business than any other. This book defines a fintech ecosystem for the 21st century, providing a state-of-the art review of current literature, suggesting avenues for new research and offering perspectives from business, technology and industry.

Sustainable Development and Disaster Risk Reduction
Sustainable Development and Disaster Risk Reduction

Author: Juha I. Uitto

Publisher: Springer

Published: 2015-11-05

Total Pages: 289

ISBN-13: 443155078X

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This book focuses on exploring the linkages between natural disasters and sustainable development at the global, regional, and national levels. Disasters and development are closely related, yet the disciplinary silos prevail and there is little communication and cooperation between the disaster management, environment, and development communities. One catastrophic event, such as an earthquake, tsunami, or cyclone, can destroy infrastructure, people’s lives and livelihoods, and set back development. Similarly, slow onset disasters—often associated with global climate change—pose threats to development, livelihoods, food security, and long-term sustainable development. This book is uniquely aimed at bridging the gaps between the environmental, development, and disaster management communities. It traces the evolution of concepts and practice and highlights the linkages between natural disasters and sustainable development in key sectors, including food security, health, and water. The book includes case studies from the field highlighting the complex issues that challenge sustainable development and disaster risk management in practice. It draws policy conclusions for the global community based on state-of-the art knowledge from research and practice. The primary target groups for the book are researchers, including graduate students, in the fields of environment and sustainable development, geography, disaster risk reduction, and climate change studies. The second target group comprises practitioners and policymakers working in national and international organizations, the private sector, and civil society.

Second International Conference on Image Processing and Capsule Networks
Second International Conference on Image Processing and Capsule Networks

Author: Joy Iong-Zong Chen

Publisher: Springer Nature

Published: 2021-09-09

Total Pages: 840

ISBN-13: 3030847608

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This book includes the papers presented in 2nd International Conference on Image Processing and Capsule Networks [ICIPCN 2021]. In this digital era, image processing plays a significant role in wide range of real-time applications like sensing, automation, health care, industries etc. Today, with many technological advances, many state-of-the-art techniques are integrated with image processing domain to enhance its adaptiveness, reliability, accuracy and efficiency. With the advent of intelligent technologies like machine learning especially deep learning, the imaging system can make decisions more and more accurately. Moreover, the application of deep learning will also help to identify the hidden information in volumetric images. Nevertheless, capsule network, a type of deep neural network, is revolutionizing the image processing domain; it is still in a research and development phase. In this perspective, this book includes the state-of-the-art research works that integrate intelligent techniques with image processing models, and also, it reports the recent advancements in image processing techniques. Also, this book includes the novel tools and techniques for deploying real-time image processing applications. The chapters will briefly discuss about the intelligent image processing technologies, which leverage an authoritative and detailed representation by delivering an enhanced image and video recognition and adaptive processing mechanisms, which may clearly define the image and the family of image processing techniques and applications that are closely related to the humanistic way of thinking.

Powering the Digital Economy: Opportunities and Risks of Artificial Intelligence in Finance
Powering the Digital Economy: Opportunities and Risks of Artificial Intelligence in Finance

Author: El Bachir Boukherouaa

Publisher: International Monetary Fund

Published: 2021-10-22

Total Pages: 35

ISBN-13: 1589063953

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This paper discusses the impact of the rapid adoption of artificial intelligence (AI) and machine learning (ML) in the financial sector. It highlights the benefits these technologies bring in terms of financial deepening and efficiency, while raising concerns about its potential in widening the digital divide between advanced and developing economies. The paper advances the discussion on the impact of this technology by distilling and categorizing the unique risks that it could pose to the integrity and stability of the financial system, policy challenges, and potential regulatory approaches. The evolving nature of this technology and its application in finance means that the full extent of its strengths and weaknesses is yet to be fully understood. Given the risk of unexpected pitfalls, countries will need to strengthen prudential oversight.