Big data analytics and knowledge discovery for urban computing and intelligence

Author:

Singh Krishna Kant,Rho Seungmin,Singh Akansha,Sergei Chernyi

Abstract

AbstractIt is anticipated that during the next 3 decades, approximately two-thirds of the world’s population would live in urban regions. This represents a significant movement towards urbanisation on the part of the world’s population. Thus, urban planners need effective methods for regulating both the use of land and the management of infrastructure. The accessibility of data that is accurate, up to date, and insightful is an extremely important factor in the formation of effective methods of urban administration and smart cities. Combining technologies for pervasive sensing, intelligent computing, cooperative communication, and mass data management may enhance urban surroundings, quality of life, and smart city systems. To do this, we need to develop novel strategies for integrating computation and intelligence into urban environments. This field of study focuses on the intersection of computing and intelligence in urban settings.

Publisher

Springer Science and Business Media LLC

Subject

Computational Mathematics,Engineering (miscellaneous),Information Systems,Artificial Intelligence

Reference6 articles.

1. Vandana Kolisetty V, Rajput DS (2021) Integration and classification approach based on probabilistic semantic association for big data. Complex Intell Syst 11:1–4

2. Kumar R, Dhiman G, Kumar N, Chandrawat RK, Joshi V, Kaur A (2021) A novel approach to optimize the production cost of railway coaches of India using situational-based composite triangular and trapezoidal fuzzy LPP models. Complex Intell Syst 27:1–6

3. Ghanem S, Kanungo P, Panda G, Satapathy SC, Sharma R (2021) Lane detection under artificial colored light in tunnels and on highways: an IoT-based framework for smart city infrastructure. Complex Intell Syst 2:1–2

4. Jain SK, Kesswani N (2021) A noise-based privacy preserving model for internet of things. Complex Intell Syst 25:1–25

5. Kaur S, Singh A, Geetha G, Cheng X (2021) IHWC: intelligent hidden web crawler for harvesting data in urban domains. Complex Intell Syst 24:1–9

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3