Mathematical Estimation of Particulate Air Pollution Levels by Multi-angle Imaging - Environmental Software Systems. Data Science in Action Access content directly
Conference Papers Year : 2020

Mathematical Estimation of Particulate Air Pollution Levels by Multi-angle Imaging

Or Vernik
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Abstract

Air pollution control and mitigation are important factors in wellbeing and sustainability. To this end, air pollution monitoring has a significant role. Today, air pollution monitoring is mainly done by standardized stations. The spread of those stations is sparse and their cost hinders the option of adding more. Thus, arises the need for cheaper and available means to assess air pollution. In this article, a method for assessing air pollution levels by means of multi angle imaging is presented. Specifically, the focus is on estimating images’ blur as an indication for PM (Particulate Matter) ambient levels. The suggested method applies back-projection Radon transform. By back projection methodology, particles’ concentration at each voxel in a 3D space is reconstructed from photos taken from a few different angles.
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hal-03361876 , version 1 (01-10-2021)

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Or Vernik, Barak Fishbain. Mathematical Estimation of Particulate Air Pollution Levels by Multi-angle Imaging. 13th International Symposium on Environmental Software Systems (ISESS), Feb 2020, Wageningen, Netherlands. pp.249-257, ⟨10.1007/978-3-030-39815-6_24⟩. ⟨hal-03361876⟩
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