{"id":252254,"date":"2026-07-13T01:54:34","date_gmt":"2026-07-12T22:54:34","guid":{"rendered":"https:\/\/1kitap1.com\/en\/artificial-intelligence-big-data-and-iot-rajesh-singh-1\/"},"modified":"2026-07-13T01:54:34","modified_gmt":"2026-07-12T22:54:34","slug":"artificial-intelligence-big-data-and-iot-rajesh-singh-1","status":"publish","type":"post","link":"https:\/\/1kitap1.com\/en\/artificial-intelligence-big-data-and-iot-rajesh-singh-1\/","title":{"rendered":"Artificial Intelligence Big Data And IoT – Rajesh Singh (1)"},"content":{"rendered":"
\"<\/figure>\n

NOAA and the IPCC, the number of category 4 to 5 hurricanes in North America during the previous 50 years has significantly increased by 37% (2022-23). According to scientific simulations of climate change, the average worldwide temperature increase is more than about 1\u00b0C throughout the same time span [1]. While no singular natural disaster can be definitively causally linked to anthropogenic activities, the aggregated shift towards harsher extremes follows expected patterns of climate change consequences.<\/p>\n

Some climate researchers posit that feedback loops accelerating ice cap melting, sea temperature rise, and increasing atmospheric water vapor may contribute to the rapidity of recently observed changes [2]. However, significant gaps remain in current understanding of the precise mechanisms driving the intensification. Implementing predictive models that accurately project the impacts of hazardous weather will be vital for resilience planning and emergency preparedness in increasingly climate- vulnerable population centers.<\/p>\n

Additional cross-disciplinary research combining high-resolution climatology data with machine learning analysis is warranted to provide these actionable projections for urban infrastructure and management officials in coastal municipalities. Urban municipalities are increasingly adopting technological innovations, digital governance, and data-driven policy initiatives with the strategic objectives to improve the quality of life for citizens, promote environmental sustainability, and enhance resilience to external shocks or disasters. For example, Songdo, South Korea and Shenzhen, China have implemented citywide sensor networks, artificial intelligence enabled transportation systems, automated emergency response communication pipelines and embedded adaptive infrastructure in order to systematically address urbanization challenges related to population density, health risks from pollution, climate change vulnerabilities, as well as economic and social turbulence from potential technology or health crises [4].<\/p>\n

\n

Artificial Intelligence, Big Data, and Internet of Things for Sustainable Industry and Infrastructure Development Editors: Rajesh Singh, Rakesh Kumar and Rupa Khanna Malhotra ISBN (Online): 978-981-5322-97-2 ISBN (Paperback): 978-981-5322-99-6 \u00a9 2026, Bentham Books imprint. ISBN (Print): 978-981-5322-98-9 Published by Bentham Science Publishers Pte. Ltd. Singapore. All Rights Reserved. First published in 2026. BSP-EB-EBH-9789815322972-TP-194-TC-10-PD-20260126 BENTHAM SCIENCE PUBLISHERS LTD. End User License Agreement (for non-institutional, personal use) This is an agreement between you and Bentham Science Publishers Ltd.<\/p>\n

Please read this License Agreement carefully before using the ebook\/echapter\/ejournal (\u201cWork\u201d). Your use of the Work constitutes your agreement to the terms and conditions set forth in this License Agreement. If you do not agree to these terms and conditions then you should not use the Work. Bentham Science Publishers agrees to grant you a non-exclusive, non-transferable limited license to use the Work subject to and in accordance with the following terms and conditions. This License Agreement is for non-library, personal use only.<\/p>\n

For a library \/ institutional \/ multi user license in respect of the Work, please contact: permission@benthamscience.org. Usage Rules: All rights reserved: The Work is the subject of copyright and Bentham Science Publishers either owns the 1. Work (and the copyright in it) or is licensed to distribute the Work. You shall not copy, reproduce, modify, remove, delete, augment, add to, publish, transmit, sell, resell, create derivative works from, or in any way exploit the Work or make the Work available for others to do any of the same, in any form or by any means, in whole or in part, in each case without the prior written permission of Bentham Science Publishers, unless stated otherwise in this License Agreement.<\/p>\n

You may download a copy of the Work on one occasion to one personal computer (including tablet, 2. laptop, desktop, or other such devices). You may make one back-up copy of the Work to avoid losing it. The unauthorised use or distribution of copyrighted or other proprietary content is illegal and could subject 3. you to liability for substantial money damages. You will be liable for any damage resulting from your misuse of the Work or any violation of this License Agreement, including any infringement by you of copyrights or proprietary rights.<\/p>\n<\/blockquote>\n

This is a short excerpt from the opening of “” by Unknown, quoted for review and introduction purposes. All rights belong to the copyright holders.<\/em><\/p>\n

\n
\n

Table of Contents<\/p>\nToggle<\/span><\/path><\/svg><\/svg><\/span><\/span><\/span><\/a><\/span><\/div>\n