Using multi-sourced big data to correlate sleep deprivation and road traffic noise: A US county-level ecological study

Tong, Hanxing; Warren, Joshua L.; Kang, Jian; Li, Mingxiao

doi:10.1016/j.envres.2022.115029

Cited by 6 publications

(3 citation statements)

References 27 publications

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“…The first class has articles regarding vehicles in smart city (Balbin et al 2020;Cui et al 2019;Guo and Xu 2022). The second sub-class collects articles on city planning: (Failed 2017e, 2022; Khan et al 2017;Ng et al 2017;Chang 2021;Tong et al 2022;Zhang et al 2022b;Mortaheb and Jankowski 2023). The third category focuses on surveillance systems (Tian et al 2018;Ramsahai, et al 2023;Huang et al 2023).…”

Section: Smart City Applicationsmentioning

confidence: 99%

“…However, the point that was neglected in ethical issues of smart cities was the security and data release without authorization. Tong, et al (Tong et al 2022) conducted research using concurrent data driven by the government and national traffic noise to look further into sleep deprivation based on the structure of cities and homes in city planning. One of the highlights was that above 62% of the people had suffered from a lack of sleep due to traffic noise.…”

Section: Overview Of Smart City Articlesmentioning

confidence: 99%

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Big data and predictive analytics: A systematic review of applications

Jamarani,

Haddadi,

Sarvizadeh

et al. 2024

Artif Intell Rev

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Big data involves processing vast amounts of data using advanced techniques. Its potential is harnessed for predictive analytics, a sophisticated branch that anticipates unknown future events by discerning patterns observed in historical data. Various techniques obtained from modeling, data mining, statistics, artificial intelligence, and machine learning are employed to analyze available history to extract discriminative patterns for predictors. This study aims to analyze the main research approaches on Big Data Predictive Analytics (BDPA) based on very up-to-date published articles from 2014 to 2023. In this article, we fully concentrate on predictive analytics using big data mining techniques, where we perform a Systematic Literature Review (SLR) by reviewing 109 articles. Based on the application and content of current studies, we introduce taxonomy including seven major categories of industrial, e-commerce, smart healthcare, smart agriculture, smart city, Information and Communications Technologies (ICT), and weather. The benefits and weaknesses of each approach, potentially important changes, and open issues, in addition to future paths, are discussed. The compiled SLR not only extends on BDPA’s strengths, open issues, and future works but also detects the need for optimizing the insufficient metrics in big data applications, such as timeliness, accuracy, and scalability, which would enable organizations to apply big data to shift from retrospective analytics to prospective predictive if fulfilled.

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Section: Smart City Applicationsmentioning

confidence: 99%

Section: Overview Of Smart City Articlesmentioning

confidence: 99%

Big data and predictive analytics: A systematic review of applications

Jamarani,

Haddadi,

Sarvizadeh

et al. 2024

Artif Intell Rev

View full text Add to dashboard Cite

show abstract

“…The general population has perceived that noise has a serious effect on our daily life. [2,3] Noise problems not only can cause tinnitus [4] and hearing loss, [5] but also can produce many extra-auditory effects, [6] such as sleep disturbance, [7,8] psychological health problems, [9] cognitive impairment, [10,11] and metabolic disorders. [6,12] There is no doubt that exposure to high sound pressure for prolonged periods will result in the decline in the sense of contentment and happiness.…”

mentioning

confidence: 99%

Recent Advances in Preparation and Structure of Polyurethane Porous Materials for Sound Absorbing Application

Dong,

Duan,

Chen

et al. 2024

Macromol. Rapid Commun.

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Various acoustic materials have been developed to resolve noise pollution problem in many industries. Especially, materials with porous structure have been broadly used to absorb sound energy in civil construction and transportation area. Polyurethane (PU) porous materials possess excellent damping properties, good toughness and well‐developed pore structures, which have a broad application prospect in sound absorption field. This work aimed to summarize the recent progress of fabrication and structure for PU porous materials in sound absorption application. The sound absorption mechanisms of porous materials were introduced. Different kinds of structure for typical PU porous materials in sound absorption application were covered and highlighted, which included PU foam, modified PU porous materials, aerogel, templated PU and special PU porous materials. Finally, the development direction and existing problems of PU material in sound absorption application were briefly prospected. It can be expected that porous PU with high sound absorption coefficient can be obtained by using some facile methods. The design and accurate regulation of porous structures or construction of multilayer sound absorption structure will be favorably recommended to fulfill the high demand of industrial and commercial applications in the future work.This article is protected by copyright. All rights reserved

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