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| artificial intelligence in emergency management: AI and Robotics in Disaster Studies T. V. Vijay Kumar, Keshav Sud, 2020-10-12 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. |
| artificial intelligence in emergency management: Utilizing AI and Machine Learning for Natural Disaster Management Satishkumar, D., Sivaraja, M., 2024-04-29 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. |
| artificial intelligence in emergency management: Intelligent Systems for Crisis Management Orhan Altan, Madhu Chandra, Filiz Sunar, Tullio Joseph Tanzi, 2019-02-06 In the past several years, there have been significant technological advances in the field of crisis response. However, many aspects concerning the efficient collection and integration of geo-information, applied semantics and situation awareness for disaster management remain open. Improving crisis response systems and making them intelligent requires extensive collaboration between emergency responders, disaster managers, system designers and researchers alike. To facilitate this process, the Gi4DM (GeoInformation for Disaster Management) conferences have been held regularly since 2005. The events are coordinated by the Joint Board of Geospatial Information Societies (JB GIS) and ICSU GeoUnions. This book presents the outcomes of the Gi4DM 2018 conference, which was organised by the ISPRS-URSI Joint Working Group ICWG III/IVa: Disaster Assessment, Monitoring and Management and held in Istanbul, Turkey on 18-21 March 2018. It includes 12 scientific papers focusing on the intelligent use of geo-information, semantics and situation awareness. |
| artificial intelligence in emergency management: Artificial Intelligence, Machine Learning, and Optimization Tools for Smart Cities Panos M. Pardalos, Stamatina Th. Rassia, Arsenios Tsokas, 2022-01-09 This volume offers a wealth of interdisciplinary approaches to artificial intelligence, machine learning and optimization tools, which contribute to the optimization of urban features towards forming smart, sustainable, and livable future cities. Special features include: New research on the design of city elements and smart systems with respect to new technologies and scientific thinking Discussions on the theoretical background that lead to smart cities for the future New technologies and principles of research that can promote ideas of artificial intelligence and machine learning in optimized urban environments The book engages students and researchers in the subjects of artificial intelligence, machine learning, and optimization tools in smart sustainable cities as eminent international experts contribute their research results and thinking in its chapters. Overall, its audience can benefit from a variety of disciplines including, architecture, engineering, physics, mathematics, computer science, and related fields. |
| artificial intelligence in emergency management: Internet of Things and AI for Natural Disaster Management and Prediction Satishkumar, D., Sivaraja, M., 2024-03-07 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. |
| artificial intelligence in emergency management: Artificial Intelligence in Healthcare Adam Bohr, Kaveh Memarzadeh, 2020-06-21 Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. - Highlights different data techniques in healthcare data analysis, including machine learning and data mining - Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks - Includes applications and case studies across all areas of AI in healthcare data |
| artificial intelligence in emergency management: Disasters and Public Health Bruce W. Clements, Julie Casani, 2016-02-23 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 |
| artificial intelligence in emergency management: Disaster Robotics Robin R. Murphy, 2014-02-14 A comprehensive, authoritative, and accessible reference for disaster robotics that covers theory, specific deployments, and ground, air, and marine modalities. This book offers the definitive guide to the theory and practice of disaster robotics. It can serve as an introduction for researchers and technologists, a reference for emergency managers, and a textbook in field robotics. Written by a pioneering researcher in the field who has herself participated in fifteen deployments of robots in disaster response and recovery, the book covers theory and practice, the history of the field, and specific missions. After a broad overview of rescue robotics in the context of emergency informatics, the book provides a chronological summary and formal analysis of the thirty-four documented deployments of robots to disasters that include the 2001 collapse of the World Trade Center, Hurricane Katrina, the 2010 Haiti earthquake, the Deepwater Horizon oil spill, the 2011 Japanese earthquake and tsunami, and numerous mining accidents. It then examines disaster robotics in the typical robot modalities of ground, air, and marine, addressing such topics as robot types, missions and tasks, and selection heuristics for each modality. Finally, the book discusses types of fieldwork, providing practical advice on matters that include collecting data and collaborating with emergency professionals. The field of disaster robotics has lacked a comprehensive overview. This book by a leader in the field, offering a unique combination of the theoretical and the practical, fills the gap. |
| artificial intelligence in emergency management: Justice, Equity and Emergency Management Alessandra Jerolleman, William L. Waugh Jr, 2022-01-26 Justice, Equity and Emergency Management applies a justice and equity lens across all phases of emergency management, focusing on key topics such as hazard mitigation, emerging technologies, long-term recovery, and others. |
| artificial intelligence in emergency management: Advances and Applications of Artificial Intelligence and Numerical Simulation in Risk Emergency Management and Treatment, volume II Yunhui Zhang, Yihuai Zhang, Long Yan, Lei Xia, Chengyi Pu, 2024-09-13 This Research Topic is Volume II of a series. The previous volume can be found here: Advances and Applications of Artificial Intelligence and Numerical Simulation in Risk Emergency Management and Treatment Our world is composed of multidimensional and multifaceted risks. In general, geological, environmental, and ecological risks would exist in both natural and engineering situations, such as karst desertification, water inrush, rock burst, debris flow, and landslide. These risks have great safety threats to human survival. In this regard, risk emergency management and treatment (REMT) has become a pivotal topic addressing the national governance system and its governance capacity. It underlines how to prevent and resolve grand security risks, to timely respond to all kinds of disasters and accidents, as well as to safeguard people’s lives and property and social stability. |
| artificial intelligence in emergency management: Computational Thinking for Problem Solving and Managerial Mindset Training Dall'Acqua, Luisa, 2021-06-25 The cultural, social, and economic history of mankind is characterized by a succession of needs and problems that have stimulated the invention of operational and conceptual tools to facilitate their solution. The continuous presentation of new needs, an attempt to improve partial solutions to old problems, curiosity, and the disinterested search for knowledge then constituted the fundamental push for scientific, cultural, economic, and social progress. In an increasingly digital society, where software technological tools permeate daily life and, consequently, change the management of reality, mastering of transversal skills is crucial for success. Computational thinking is a set of transversal skills related to the foundations of computer science as a scientific discipline and means a mastering to the process of solving problems. The goal of computational thinking is to acquire interpretative perspectives of reality, which allows one to read the digital experience competently and responsibly. Computational Thinking for Problem Solving and Managerial Mindset Training explores how individuals can be trained into managerial mindsets through computational thinking and computer science. It explores how computer science can be used as a valid guideline to develop skills such as effective soft skills, communication skills, and collaboration. Further, the chapters explore the adoption of computational thinking for individuals to gain managerial mindsets and successfully solve questions and problems in their domain of interest. This will include artificial intelligence applications, strategic thinking, management training, ethics, emergency managerial mindsets, and more. This book is valuable for managers, professionals, practitioners, researchers, academicians, and students interested in how computational thinking can be applied for the training of managerial mindsets. |
| artificial intelligence in emergency management: Sustainable Development and Disaster Risk Reduction Juha I. Uitto, Rajib Shaw, 2015-11-05 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. |
| artificial intelligence in emergency management: Social Media, Crisis Communication, and Emergency Management Connie M. White, 2011-09-20 Although recent global disasters have clearly demonstrated the power of social media to communicate critical information in real-time, its true potential has yet to be unleashed. Social Media, Crisis Communication, and Emergency Management: Leveraging Web 2.0 Technologies teaches emergency management professionals how to use social media to improve emergency planning, preparedness, and response capabilities. It provides a set of guidelines and safe practices for using social media effectively across a range of emergency management applications. Explaining how emergency management agencies can take advantage of the extended reach these technologies offer, the book supplies cutting-edge methods for leveraging these technologies to manage information more efficiently, reduce information overload, inform the public, and ultimately save lives. Filled with real-world examples and case studies, it is an ideal self-study resource. Its easy-to-navigate structure and numerous exercises also make it suitable for courses at both the undergraduate and graduate levels. From crowdsourcing and digital volunteers to mapping and collective intelligence, Social Media, Crisis Communication, and Emergency Management: Leveraging Web 2.0 Technologies facilitates a clear understanding of the essential principles of social media. Each chapter includes an example of a local-level practitioner, organization, or agency using social media that demonstrates the transformative power of social media in the real world. The book also includes numerous exercises that supply readers with models for building their own social media sites and groups—making it a must-read for anyone who wants to learn more about the communication and information structures supported by social media. Visit the author’s homepage: http://sites.google.com/site/conniemwhite/Home |
| artificial intelligence in emergency management: WebGIS for Disaster Management and Emergency Response Rifaat Abdalla, Marwa Esmail, 2018-12-06 This book aims to help students, researchers and policy makers understand the latest research and development trends in the application of WebGIS for Disaster Management and Emergency Response. It is designed as a useful tool to better assess the mechanisms for planning, response and mitigation of the impact of disaster scenarios at the local, regional or national levels. It contains details on how to use WebGIS to solve real-world problems associated with Disaster Management Scenarios for the long-term sustainability. The book broadens the reader understanding of the policy and decision-making issues related to Disaster Management response and planning. |
| artificial intelligence in emergency management: Achieving Organizational Agility, Intelligence, and Resilience Through Information Systems Rahman, Hakikur, 2021-09-10 As technology continues to be a ubiquitous force that propels businesses to success, it is imperative that updated studies are continuously undertaken to ensure that the most efficient tools and techniques are being utilized. In the current business environment, organizations that can improve their agility and business intelligence are able to become much more resilient and viable competitors in the global economy. Achieving Organizational Agility, Intelligence, and Resilience Through Information Systems is a critical reference book that provides the latest empirical studies, conceptual research, and methodologies that enable organizations to enhance and improve their agility, competitiveness, and sustainability in order to position them for paramount success in today’s economy. Covering topics that include knowledge management, human development, and sustainable development, this book is ideal for managers, executives, entrepreneurs, IT specialists and consultants, academicians, researchers, and students. |
| artificial intelligence in emergency management: Digital Humanitarians Patrick Meier, 2015-01-06 The overflow of information generated during disasters can be as paralyzing to humanitarian response as the lack of information. This flash flood of information‘social media, satellite imagery and more is often referred to as Big Data. Making sense of this data deluge during disasters is proving an impossible challenge for traditional humanitarian |
| artificial intelligence in emergency management: Future Role of Sustainable Innovative Technologies in Crisis Management Ali, Mohammed, 2022-04-18 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. |
| artificial intelligence in emergency management: Incidents That Define Process Safety CCPS (Center for Chemical Process Safety), 2013-07-01 Incidents That Define Process Safety describes approximately fifty incidents that have had a significant impact on the chemical and refining industries' approaches to modern process safety. Events are described in detail so readers get a fundamental understanding of the root causes, the consequences, the lessons learned, and actions that can prevent a recurrence. There are exhaustive investigative reports about these events, allowing you to apply the resulting safety principles to their current operations. |
| artificial intelligence in emergency management: Digital Services in Crisis, Disaster, and Emergency Situations Oliveira, Lídia, Tajariol, Federico, Gonçalves, Liliana Baptista, 2021-01-29 The contemporary world is characterized by the massive use of digital communication platforms and services that allow people to stay in touch with each other and their organizations. On the other hand, it is also a world with great challenges in terms of crisis, disaster, and emergency situations of various kinds. Thus, it is crucial to understand the role of digital platforms/services in the context of crisis, disaster, and emergency situations. Digital Services in Crisis, Disaster, and Emergency Situations presents recent studies on crisis, disaster, and emergency situations in which digital technologies are considered as a key mediator. Featuring multi- and interdisciplinary research findings, this comprehensive reference work highlights the relevance of society’s digitization and its usefulness and contribution to the different phases and types of risk scenarios. Thus, the book investigates the design of digital services that are specifically developed for use in crisis situations and examines services such as online social networks that can be used for communication purposes in emergency events. Highlighting themes that include crisis management communication, risk monitoring, digital crisis intervention, and smartphone applications, this book is of particular use to governments, institutions, corporations, and professionals who deal with crisis, disaster, and emergency scenarios, as well as researchers, academicians, and students working in fields such as communications, multimedia, sociology, political science, and engineering. |
| artificial intelligence in emergency management: AI and IoT for Proactive Disaster Management Ouaissa, Mariyam, Ouaissa, Mariya, Boulouard, Zakaria, Iwendi, Celestine, Krichen, Moez, 2024-05-06 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. |
| artificial intelligence in emergency management: Emergency Alert and Warning Systems National Academies of Sciences, Engineering, and Medicine, Division on Engineering and Physical Sciences, Computer Science and Telecommunications Board, Committee on the Future of Emergency Alert and Warning Systems: Research Directions, 2018-04-19 Following a series of natural disasters, including Hurricane Katrina, that revealed shortcomings in the nation's ability to effectively alert populations at risk, Congress passed the Warning, Alert, and Response Network (WARN) Act in 2006. Today, new technologies such as smart phones and social media platforms offer new ways to communicate with the public, and the information ecosystem is much broader, including additional official channels, such as government social media accounts, opt-in short message service (SMS)-based alerting systems, and reverse 911 systems; less official channels, such as main stream media outlets and weather applications on connected devices; and unofficial channels, such as first person reports via social media. Traditional media have also taken advantage of these new tools, including their own mobile applications to extend their reach of beyond broadcast radio, television, and cable. Furthermore, private companies have begun to take advantage of the large amounts of data about users they possess to detect events and provide alerts and warnings and other hazard-related information to their users. More than 60 years of research on the public response to alerts and warnings has yielded many insights about how people respond to information that they are at risk and the circumstances under which they are most likely to take appropriate protective action. Some, but not all, of these results have been used to inform the design and operation of alert and warning systems, and new insights continue to emerge. Emergency Alert and Warning Systems reviews the results of past research, considers new possibilities for realizing more effective alert and warning systems, explores how a more effective national alert and warning system might be created and some of the gaps in our present knowledge, and sets forth a research agenda to advance the nation's alert and warning capabilities. |
| artificial intelligence in emergency management: Automated Planning Malik Ghallab, Dana Nau, Paolo Traverso, 2004-05-03 Publisher Description |
| artificial intelligence in emergency management: Federal Response Plan , 1999 |
| artificial intelligence in emergency management: Artificial Intelligence in Medical Imaging Erik R. Ranschaert, Sergey Morozov, Paul R. Algra, 2019-01-29 This book provides a thorough overview of the ongoing evolution in the application of artificial intelligence (AI) within healthcare and radiology, enabling readers to gain a deeper insight into the technological background of AI and the impacts of new and emerging technologies on medical imaging. After an introduction on game changers in radiology, such as deep learning technology, the technological evolution of AI in computing science and medical image computing is described, with explanation of basic principles and the types and subtypes of AI. Subsequent sections address the use of imaging biomarkers, the development and validation of AI applications, and various aspects and issues relating to the growing role of big data in radiology. Diverse real-life clinical applications of AI are then outlined for different body parts, demonstrating their ability to add value to daily radiology practices. The concluding section focuses on the impact of AI on radiology and the implications for radiologists, for example with respect to training. Written by radiologists and IT professionals, the book will be of high value for radiologists, medical/clinical physicists, IT specialists, and imaging informatics professionals. |
| artificial intelligence in emergency management: Smart Technologies for Emergency Response and Disaster Management Zhi Liu, Kaoru Ota, 2017-05-16 This book address the difficulties, challenges and solution in Smart Technologies for Emergency Response & Disaster Management. The chapters address different aspects of Smart Technologies for Emergency Response & Disaster Management, ranging from network technology for emergency response and disaster management, big data for emergency response and disaster management to robotics emergency response and disaster management-- |
| artificial intelligence in emergency management: Guide for All-Hazard Emergency Operations Planning Kay C. Goss, 1998-05 Meant to aid State & local emergency managers in their efforts to develop & maintain a viable all-hazard emergency operations plan. This guide clarifies the preparedness, response, & short-term recovery planning elements that warrant inclusion in emergency operations plans. It offers the best judgment & recommendations on how to deal with the entire planning process -- from forming a planning team to writing the plan. Specific topics of discussion include: preliminary considerations, the planning process, emergency operations plan format, basic plan content, functional annex content, hazard-unique planning, & linking Federal & State operations. |
| artificial intelligence in emergency management: Guidelines for Safe and Reliable Instrumented Protective Systems CCPS (Center for Chemical Process Safety), 2011-11-16 This book explains the decision-making processes for the management of instrumented protective systems (IPS) throughout a project's life cycle. It uses the new IEC 61511 standard as a basis for the work processes used to achieve safe and reliable process operation. By walking the reader through a project's life cycle, engineering, maintenance, and operations, the information allows users to easily focus on their responsibilities and duties. Using this approach, the book is useful as a primer, guidelines reference, and resource manual. Examples provide the added real-world experience applications. |
| artificial intelligence in emergency management: Handbook of Research on Artificial Intelligence Applications in the Aviation and Aerospace Industries Shmelova, Tetiana, Sikirda, Yuliya, Sterenharz, Arnold, 2019-10-11 With the emergence of smart technology and automated systems in today’s world, artificial intelligence (AI) is being incorporated into an array of professions. The aviation and aerospace industry, specifically, is a field that has seen the successful implementation of early stages of automation in daily flight operations through flight management systems and autopilot. However, the effectiveness of aviation systems and the provision of flight safety still depend primarily upon the reliability of aviation specialists and human decision making. The Handbook of Research on Artificial Intelligence Applications in the Aviation and Aerospace Industries is a pivotal reference source that explores best practices for AI implementation in aviation to enhance security and the ability to learn, improve, and predict. While highlighting topics such as computer-aided design, automated systems, and human factors, this publication explores the enhancement of global aviation security as well as the methods of modern information systems in the aeronautics industry. This book is ideally designed for pilots, scientists, engineers, aviation operators, air crash investigators, teachers, academicians, researchers, and students seeking current research on the application of AI in the field of aviation. |
| artificial intelligence in emergency management: Intelligent Systems and Decision Making for Risk Analysis and Crisis Response Chongfu Huang, Cengiz Kahraman, 2013-07-25 In this present internet age, risk analysis and crisis response based on information will make up a digital world full of possibilities and improvements to people’s daily life and capabilities. These services will be supported by more intelligent systems and more effective decisionmaking. This book contains all the papers presented at the 4th International Conference on Risk Analysis and Crisis Response, August 27-29, 2013, Istanbul, Turkey. The theme was intelligent systems and decision making for risk analysis and crisis response. The risk issues in the papers cluster around the following topics: natural disasters, finance risks, food and feed safety, catastrophic accidents, critical infrastructure, global climate change, project management, supply chains, public health, threats to social safety, energy and environment. This volume will be of interest to all professionals and academics in the field of risk analysis, crisis response, intelligent systems and decision-making, as well as related fields of enquiry. |
| artificial intelligence in emergency management: Proceedings of International Conference on Data Science and Applications Mukesh Saraswat, Sarbani Roy, Chandreyee Chowdhury, Amir H. Gandomi, 2021-11-23 This book gathers outstanding papers presented at the International Conference on Data Science and Applications (ICDSA 2021), organized by Soft Computing Research Society (SCRS) and Jadavpur University, Kolkata, India, from April 10 to 11, 2021. It covers theoretical and empirical developments in various areas of big data analytics, big data technologies, decision tree learning, wireless communication, wireless sensor networking, bioinformatics and systems, artificial neural networks, deep learning, genetic algorithms, data mining, fuzzy logic, optimization algorithms, image processing, computational intelligence in civil engineering, and creative computing. |
| artificial intelligence in emergency management: Dynamic Fleet Management Vasileios S. Zeimpekis, Christos D. Tarantilis, George M. Giaglis, Ioannis E. Minis, 2007-10-05 This book focuses on real time management of distribution systems, integrating the latest results in system design, algorithm development and system implementation to capture the state-of-the art research and application trends. The book important topics such as goods dispatching, couriers, rescue and repair services, taxi cab services, and more. The book includes real-life case studies that describe the solution to actual distribution problems by combining systemic and algorithmic approaches. |
| artificial intelligence in emergency management: Data Science Advancements in Pandemic and Outbreak Management Asimakopoulou, Eleana, Bessis, Nik, 2021-04-09 Pandemics are disruptive. Thus, there is a need to prepare and plan actions in advance for identifying, assessing, and responding to such events to manage uncertainty and support sustainable livelihood and wellbeing. A detailed assessment of a continuously evolving situation needs to take place, and several aspects must be brought together and examined before the declaration of a pandemic even happens. Various health organizations; crisis management bodies; and authorities at local, national, and international levels are involved in the management of pandemics. There is no better time to revisit current approaches to cope with these new and unforeseen threats. As countries must strike a fine balance between protecting health, minimizing economic and social disruption, and respecting human rights, there has been an emerging interest in lessons learned and specifically in revisiting past and current pandemic approaches. Such approaches involve strategies and practices from several disciplines and fields including healthcare, management, IT, mathematical modeling, and data science. Using data science to advance in-situ practices and prompt future directions could help alleviate or even prevent human, financial, and environmental compromise, and loss and social interruption via state-of-the-art technologies and frameworks. Data Science Advancements in Pandemic and Outbreak Management demonstrates how strategies and state-of-the-art IT have and/or could be applied to serve as the vehicle to advance pandemic and outbreak management. The chapters will introduce both technical and non-technical details of management strategies and advanced IT, data science, and mathematical modelling and demonstrate their applications and their potential utilization within the identification and management of pandemics and outbreaks. It also prompts revisiting and critically reviewing past and current approaches, identifying good and bad practices, and further developing the area for future adaptation. This book is ideal for data scientists, data analysts, infectious disease experts, researchers studying pandemics and outbreaks, IT, crisis and disaster management, academics, practitioners, government officials, and students interested in applicable theories and practices in data science to mitigate, prepare for, respond to, and recover from future pandemics and outbreaks. |
| artificial intelligence in emergency management: Humanitarian Ethics Hugo Slim, 2015-01-09 Humanitarians are required to be impartial, independent, professionally competent and focused only on preventing and alleviating human suffering. It can be hard living up to these principles when others do not share them, while persuading political and military authorities and non-state actors to let an agency assist on the ground requires savvy ethical skills. Getting first to a conflict or natural catastrophe is only the beginning, as aid workers are usually and immediately presented with practical and moral questions about what to do next. For example, when does working closely with a warring party or an immoral regime move from practical cooperation to complicity in human rights violations? Should one operate in camps for displaced people and refugees if they are effectively places of internment? Do humanitarian agencies inadvertently encourage ethnic cleansing by always being ready to 'mop-up' the consequences of scorched earth warfare? This book has been written to help humanitarians assess and respond to these and other ethical dilemmas. |
| artificial intelligence in emergency management: Artificial Intelligence for COVID-19 Diego Oliva, Said Ali Hassan, Ali Mohamed, 2021-07-19 This book presents a compilation of the most recent implementation of artificial intelligence methods for solving different problems generated by the COVID-19. The problems addressed came from different fields and not only from medicine. The information contained in the book explores different areas of machine and deep learning, advanced image processing, computational intelligence, IoT, robotics and automation, optimization, mathematical modeling, neural networks, information technology, big data, data processing, data mining, and likewise. Moreover, the chapters include the theory and methodologies used to provide an overview of applying these tools to the useful contribution to help to face the emerging disaster. The book is primarily intended for researchers, decision makers, practitioners, and readers interested in these subject matters. The book is useful also as rich case studies and project proposals for postgraduate courses in those specializations. |
| artificial intelligence in emergency management: Artificial Intelligence in Surgery: Understanding the Role of AI in Surgical Practice Daniel A. Hashimoto, Guy Rosman, Ozanan R. Meireles, 2021-03-08 Build a solid foundation in surgical AI with this engaging, comprehensive guide for AI novices Machine learning, neural networks, and computer vision in surgical education, practice, and research will soon be de rigueur. Written for surgeons without a background in math or computer science, Artificial Intelligence in Surgery provides everything you need to evaluate new technologies and make the right decisions about bringing AI into your practice. Comprehensive and easy to understand, this first-of-its-kind resource illustrates the use of AI in surgery through real-life examples. It covers the issues most relevant to your practice, including: Neural Networks and Deep Learning Natural Language Processing Computer Vision Surgical Education and Simulation Preoperative Risk Stratification Intraoperative Video Analysis OR Black Box and Tracking of Intraoperative Events Artificial Intelligence and Robotic Surgery Natural Language Processing for Clinical Documentation Leveraging Artificial Intelligence in the EMR Ethical Implications of Artificial Intelligence in Surgery Artificial Intelligence and Health Policy Assessing Strengths and Weaknesses of Artificial Intelligence Research Finally, the appendix includes a detailed glossary of terms and important learning resources and techniques―all of which helps you interpret claims made by studies or companies using AI. |
| artificial intelligence in emergency management: Oxford Handbook of Ethics of AI Markus D. Dubber, Frank Pasquale, Sunit Das, 2020-06-30 This volume tackles a quickly-evolving field of inquiry, mapping the existing discourse as part of a general attempt to place current developments in historical context; at the same time, breaking new ground in taking on novel subjects and pursuing fresh approaches. The term A.I. is used to refer to a broad range of phenomena, from machine learning and data mining to artificial general intelligence. The recent advent of more sophisticated AI systems, which function with partial or full autonomy and are capable of tasks which require learning and 'intelligence', presents difficult ethical questions, and has drawn concerns from many quarters about individual and societal welfare, democratic decision-making, moral agency, and the prevention of harm. This work ranges from explorations of normative constraints on specific applications of machine learning algorithms today-in everyday medical practice, for instance-to reflections on the (potential) status of AI as a form of consciousness with attendant rights and duties and, more generally still, on the conceptual terms and frameworks necessarily to understand tasks requiring intelligence, whether human or A.I. |
| artificial intelligence in emergency management: Big Crisis Data Carlos Castillo, 2016-07-04 Social media is invaluable during crises like natural disasters, but difficult to analyze. This book shows how computer science can help. |
| artificial intelligence in emergency management: Science-Based Approaches to Respond to COVID and Other Public Health Threats Erick Guerrero, 2021-12-01 COVID-19 and other public health threats have contributed to more than six million deaths globally in a short amount of time. As such, there is an urgent need to respond to these threats in a way that improves global health and wellbeing. Written by a diverse group of exemplary scientists, the thirteen chapters in this volume provide unique, comprehensive, and science-based approaches to respond to macro-structural, human process, and micro issues affecting public health threats. |
| artificial intelligence in emergency management: Information Technology Applications for Crisis Response and Management Beard, Jon W., 2021-02-19 Properly addressing a crisis requires more than just guesswork and a reaction; it requires a properly structured approach supported by good information. With the rapid evolution of information systems and information technology, including hardware, software, the internet, and communications capabilities, there are abundant opportunities to apply these technology capabilities and resources to support and improve responses to and management of crisis situations. Approaches to crisis response and management include the design, development, implementation, and application of systematic methodologies on how to respond, as well as how to apply information systems to enhance and extend responses to crises. Information Technology Applications for Crisis Response and Management provides a multi-disciplinary perspective on current and cutting-edge research exploring and extending our understanding of the use of information systems and information technology to support responses to crises of all kinds—accidental, intentional, and acts of nature. The chapters in this book focus on the design, development, implementation, use, and evaluation of information system technologies and methodologies to support crisis response and management, as well as technology management-related issues for crisis response and management. While highlighting technical, cognitive, organizational, and human-focused issues within the field, this book is ideal for policymakers, IT specialists, government officials, crisis response teams, managers, practitioners, researchers, academicians, and students interested in the use of information technology and information systems to support diverse types of crises. |
| artificial intelligence in emergency management: Predicting Natural Disasters With AI and Machine Learning Satishkumar, D., Sivaraja, M., 2024-02-16 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. |
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