智能手机在噪声绘图中的可用性综述

Faysal M. Omar, Bülent Bostancı
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摘要

全球城市人口稳步增长,目前世界上一半以上的人口居住在城市,预计到 2050 年这一趋势将翻一番。随着城市化进程的不断推进,噪声污染已成为一个重大问题,影响着 60% 以上的主要城市居民,并从生理和心理层面影响着人类健康。为解决这一问题,各国政府和组织正在努力制定有效的噪声评估、监管和缓解政策。本文献综述探讨了噪声测绘的作用以及智能手机在收集噪声数据以制定相关政策方面的潜力。文中讨论了传统的噪声绘图技术和基于智能手机的数据收集方法,以及它们在城市规划、环境研究和公共卫生方面的重要性。确定了关键的研究问题,包括基于智能手机的噪声绘图所采用的方法、与传统测量方法相比智能手机收集数据的准确性、实际应用、挑战和新兴趋势。综述显示,智能手机为收集噪声数据提供了一种具有成本效益且广泛应用的方法,可实现实时洞察并增强各领域的实际应用。然而,数据准确性、隐私问题和设备限制等挑战必须得到解决。随着传感器技术、人工智能和数据分析工具的进步,研究人员、城市规划者和政策制定者将有能力就城市环境中的噪声污染问题做出明智的决策,基于智能手机的噪声绘图技术的未来前景一片光明。
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General Review of Smartphone Usability in Noise Mapping
The global urban population is steadily increasing, with more than half of the world's population currently residing in cities, and this trend is expected to double by 2050. As urbanization continues, noise pollution becomes a significant concern, affecting over 60% of major city dwellers and impacting human health on both physiological and psychological levels. To address this issue, governments and organizations are striving to develop effective noise assessment, regulation, and mitigation policies. This literature review explores the role of noise mapping and the potential of smartphones in collecting noise data to inform these policies. Traditional noise mapping techniques and smartphone-based data collection methods are discussed, along with their importance in urban planning, environmental studies, and public health. Key research questions are identified, including the methodologies employed for smartphone-based noise mapping, the accuracy of smartphone-collected data compared to traditional measurements, practical applications, challenges, and emerging trends. The review reveals that smartphones offer a cost-effective and widespread means of gathering noise data, enabling real-time insights and enhancing various domains' practical applications. However, challenges such as data accuracy, privacy concerns, and device limitations must be addressed. The future of smartphone-based noise mapping looks promising, with advancements in sensor technologies, artificial intelligence, and data analysis tools empowering researchers, urban planners, and policymakers to make informed decisions about noise pollution in urban environments.
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