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VISIBILITY MONITORING USING MOBILE APPLICATION

机译:使用移动应用程序进行可见性监控

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Visibility is clarity with which the distant objects are perceived in the atmosphere with the naked eye. Visibility monitoring is an important concern in health, environment and transport safety context. Quantitative measures of visibility are increasingly becoming important in various areas as they are representative of the particles present in the environment that causes degradation of the visibility. Existing techniques of visibility estimation employ human observers, optical instruments, chemical sensors or combination of some of them. These techniques suffer from poor spatial and temporal resolution, high cost of installation and maintenance, need of specialized personnel, continuous power supply requirement and difficulty in portability. We propose a smart phone-based visibility monitoring system which estimates air visibility/quality in terms of a quantitative measure: Turbidity. In principle, the application calculates turbidity as difference of intensity of captured sky image and analytical value of sky luminance obtained by implementing Perez model. The estimated turbidity tagged with date, time, location, solar position and luminance is sent to the backend server generating consolidated database for mapping of turbidity and generating various analytical reports. The application can easily be deployed to be used by large number of people facilitating citizen science. The results from application were validated against the observations from SAFAR INDIA application at different stations in Ahmedabad, dates and under variable weather conditions.
机译:可见性是用肉眼在大气中感知远处物体的清晰度。可见性监视是健康,环境和运输安全方面的重要问题。在各个领域中,可见性的定量度量变得越来越重要,因为它们代表了环境中存在的导致可见性降低的颗粒。现有的能见度估计技术采用人类观察者,光学仪器,化学传感器或其中一些的组合。这些技术的空间和时间分辨率差,安装和维护成本高,需要专业人员,持续的电源需求以及便携性困难。我们提出了一种基于智能手机的能见度监测系统,该系统可通过定量方法来估算空气能见度/质量:浊度。原则上,该应用程序将浊度计算为捕获的天空图像的强度与通过实施Perez模型获得的天空亮度的分析值之差。用日期,时间,位置,太阳位置和亮度标记的估计浊度被发送到后端服务器,该服务器生成合并的数据库以绘制浊度并生成各种分析报告。可以轻松地将该应用程序部署为促进公民科学的大量人员使用。对照来自SAFAR INDIA在艾哈迈达巴德(Ahmedab​​ad)不同站点,日期和不同天气条件下应用的观察结果验证了应用结果。

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