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Palgrave Macmillan

AI and Robotics in Disaster Studies

  • Book
  • © 2020

Overview

Editors:
  1. T. V. Vijay Kumar

    1. School of Computer and Systems Sciences, Jawaharlal Nehru University, New Delhi, India

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    You can also search for this editor in PubMed   Google Scholar

  2. Keshav Sud

    1. Data Science, Keurig Dr Pepper, Burlington, USA

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    You can also search for this editor in PubMed   Google Scholar

  • Introduces policy makers to benefits and challenges of artificial intelligence and robotics
  • Liberates disaster management from technology deterministic approach to a more holistic and inclusive dialogue of technology incorporation
  • Presents strategies appropriate for encountering varieties of fast changing situations in disaster management

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Table of contents (18 chapters)

  1. Front Matter

    Pages i-xix
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  2. Introduction: Enhancing Capacity to Manage Disasters

    • Amita Singh
    Pages 1-10

  3. New Technologies in Disaster Management

    1. Front Matter

      Pages 11-11
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    2. Artificial Intelligence and Early Warning Systems

      • Rabindra Lamsal, T. V. Vijay Kumar
      Pages 13-32

    3. Artificial Intelligence in Disaster Management: Rescue Robotics, Aerial Mapping and Information Sourcing

      • Keshav Sud
      Pages 33-46

    4. Optimal Visual Cues for Smartphone Earthquake Alert Systems: Preliminary Data from Lab and Field Experiments

      • Eran Lederman, Tomer Shemi, Noga Ensenberg-Diamant, Lior Shalev, Amir Hazan, Naama Marcovits et al.
      Pages 47-62

    5. Using Artificial Intelligence and Social Media for Disaster Response and Management: An Overview

      • Ferda Ofli, Muhammad Imran, Firoj Alam
      Pages 63-81

    6. ‘Internet of Things’ Applications in Disaster Management

      • Malavika Singh
      Pages 83-92

    7. Samvad: Reaching Out Through Radio and Wireless Network

      • Sampark
      Pages 93-101

    8. Usages of AI Technologies in Nepal’s Disaster Management

      • Gajendra Sharma, Subarna Shakya
      Pages 103-115

  5. Building Community Resilience Through AI

    1. Front Matter

      Pages 197-197
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    2. Can Community Plans Really Talk? Integrating and Strengthening Communications Through Artificial Intelligence

      • Andrew Estrain, Deepa Srinivasan, Pat Pathade
      Pages 199-217

    3. The Challenge of Resilience in an Age of Artificial Intelligence

      • Acharya Shambhushivananda Avadhuta
      Pages 219-233

    4. AI in an Urban Village in Delhi

      • Natasha Goyal, Anurag Singh
      Pages 235-246
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Keywords

About this book

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.

Editors and Affiliations

  • School of Computer and Systems Sciences, Jawaharlal Nehru University, New Delhi, India

    T. V. Vijay Kumar

  • Data Science, Keurig Dr Pepper, Burlington, USA

    Keshav Sud

About the editors

Prof. Dr T.V. Vijay Kumar is Professor and Dean, School of Computer and Systems Sciences, Jawaharlal Nehru University (JNU), Delhi, India.

Dr Keshav Sud is currently working as Senior Manager of Data Science at Keurig Dr Pepper where he is leading the development of recommendation engines. Dr. Sud is a well-recognized expert in the field of AI with first authorship of numerous scholarly articles in internationally recognized professional publications.

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