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将手机用作夜间光照和噪声测量仪器:真实条件下的验证测试。

Using mobile phones as light at night and noise measurement instruments: a validation test in real world conditions.

机构信息

Department of Natural Resources and Environmental Management, Faculty of Social Sciences, University of Haifa, Haifa, Israel.

出版信息

Chronobiol Int. 2022 Jan;39(1):26-44. doi: 10.1080/07420528.2021.1964520. Epub 2021 Aug 31.

DOI:10.1080/07420528.2021.1964520
PMID:34465262
Abstract

Exposure to noise from road traffic and industries is known to be linked to various health dysfunctions, including hypertension, cardiovascular diseases and hearing loss. Exposure to artificial light at night (ALAN) is also increasingly recognized as being associated with ecosystem damage and various illnesses, including cancers, excessive weight gain and sleep disorders. However, measuring and monitoring these environmental risk factors by professional equipment are laborious and expensive, which impede large-scale research and various citizen science initiatives. In this study, we test a possibility that reliable noise and ALAN exposure estimates can be gathered using smartphones (SPs) sensors. To verify this assumption, we develop a standardized testing protocol, and use Andro-Sensor app, installed on three different Samsung Galaxy SPs - S7, S20FE5G, and SM520F, - to perform measurements of ALAN and noise in real-world conditions while comparing these measurements with measurements performed by professional (type 2) equipment - SL814 for noise and LX-1330B for illumination. The analysis of 3450 measurements, performed in two different locations in Israel, reveals that the SPs measurements and measurements performed by control instruments correlate strongly for noise (r = 0.76-0.94) and are nearly identical for ALAN (r = 0.998-0.999). The association between the two types of measurements is also found to be close to linear, with the slope of the trend line being close to 45° for ALAN and varying between 30° and 45° for noise, depending on the SPs used. Our conclusion is that the level of accuracy of ALAN measurements by SPs is greater for ALAN than for noise, which can make SPs a useful tool for large-scale ALAN studies that do not require the accuracy of professional instruments.

摘要

道路交通和工业噪声暴露已知与各种健康功能障碍有关,包括高血压、心血管疾病和听力损失。夜间人工光(ALAN)暴露也越来越被认为与生态系统破坏和各种疾病有关,包括癌症、体重过度增加和睡眠障碍。然而,使用专业设备测量和监测这些环境风险因素既费力又昂贵,这阻碍了大规模研究和各种公民科学计划的开展。在这项研究中,我们测试了使用智能手机(SPs)传感器收集可靠噪声和 ALAN 暴露估计值的可能性。为了验证这一假设,我们制定了一个标准化的测试方案,并使用安装在三部不同三星 Galaxy SPs 上的 Andro-Sensor 应用程序——S7、S20FE5G 和 SM520F——在现实条件下进行 ALAN 和噪声测量,并将这些测量值与专业(类型 2)设备——SL814 用于噪声和 LX-1330B 用于照明——进行的测量值进行比较。对在以色列两个不同地点进行的 3450 次测量的分析表明,SPs 测量值与对照仪器进行的测量值在噪声方面高度相关(r=0.76-0.94),在 ALAN 方面几乎相同(r=0.998-0.999)。还发现两种类型的测量值之间的相关性也接近线性,对于 ALAN,趋势线的斜率接近 45°,而对于噪声,斜率则在 30°至 45°之间变化,具体取决于所使用的 SPs。我们的结论是,SPs 进行的 ALAN 测量的准确性水平高于噪声,这使得 SPs 成为不需要专业仪器精度的大规模 ALAN 研究的有用工具。

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