Real-Time Automatic Cloud Detection Using a Low-Cost Sky Camera
Characterizing the atmosphere is one of the most complex studies one can undertake due to the non-linearity and phenomenological variability. Clouds are also among the most variable atmospheric constituents, changing their size and shape over a short period of time. There are several sectors in whic...
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| Format: | info:eu-repo/semantics/article |
| Language: | English |
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MDPI
2020
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| Online Access: | http://hdl.handle.net/10835/8182 |
| _version_ | 1789406563961667584 |
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| author | Alonso Montesinos, Joaquín Blas |
| author_facet | Alonso Montesinos, Joaquín Blas |
| author_sort | Alonso Montesinos, Joaquín Blas |
| collection | DSpace |
| description | Characterizing the atmosphere is one of the most complex studies one can undertake due to the non-linearity and phenomenological variability. Clouds are also among the most variable atmospheric constituents, changing their size and shape over a short period of time. There are several sectors in which the study of cloudiness is of vital importance. In the renewable field, the increasing development of solar technology and the emerging trend for constructing and operating solar plants across the earth’s surface requires very precise control systems that provide optimal energy production management. Similarly, airports are hubs where cloud coverage is required to provide high-precision periodic observations that inform airport operators about the state of the atmosphere. This work presents an autonomous cloud detection system, in real time, based on the digital image processing of a low-cost sky camera. An algorithm was developed to identify the clouds in the whole image using the relationships established between the channels of the RGB and Hue, Saturation, Value (HSV) color spaces. The system’s overall success rate is approximately 94% for all types of sky conditions; this is a novel development which makes it possible to identify clouds from a ground perspective without the use of radiometric parameters. |
| format | info:eu-repo/semantics/article |
| id | oai:repositorio.ual.es:10835-8182 |
| institution | Universidad de Cuenca |
| language | English |
| publishDate | 2020 |
| publisher | MDPI |
| record_format | dspace |
| spelling | oai:repositorio.ual.es:10835-81822023-04-12T19:47:32Z Real-Time Automatic Cloud Detection Using a Low-Cost Sky Camera Alonso Montesinos, Joaquín Blas cloud detection cloud coverage sky camera image processing remote sensing CSP plant solar energy solar irradiance forecasting total sky imagery Characterizing the atmosphere is one of the most complex studies one can undertake due to the non-linearity and phenomenological variability. Clouds are also among the most variable atmospheric constituents, changing their size and shape over a short period of time. There are several sectors in which the study of cloudiness is of vital importance. In the renewable field, the increasing development of solar technology and the emerging trend for constructing and operating solar plants across the earth’s surface requires very precise control systems that provide optimal energy production management. Similarly, airports are hubs where cloud coverage is required to provide high-precision periodic observations that inform airport operators about the state of the atmosphere. This work presents an autonomous cloud detection system, in real time, based on the digital image processing of a low-cost sky camera. An algorithm was developed to identify the clouds in the whole image using the relationships established between the channels of the RGB and Hue, Saturation, Value (HSV) color spaces. The system’s overall success rate is approximately 94% for all types of sky conditions; this is a novel development which makes it possible to identify clouds from a ground perspective without the use of radiometric parameters. 2020-05-12T08:02:47Z 2020-05-12T08:02:47Z 2020-04-27 info:eu-repo/semantics/article 2072-4292 http://hdl.handle.net/10835/8182 en https://www.mdpi.com/2072-4292/12/9/1382 Attribution-NonCommercial-NoDerivatives 4.0 Internacional http://creativecommons.org/licenses/by-nc-nd/4.0/ info:eu-repo/semantics/openAccess MDPI |
| spellingShingle | cloud detection cloud coverage sky camera image processing remote sensing CSP plant solar energy solar irradiance forecasting total sky imagery Alonso Montesinos, Joaquín Blas Real-Time Automatic Cloud Detection Using a Low-Cost Sky Camera |
| title | Real-Time Automatic Cloud Detection Using a Low-Cost Sky Camera |
| title_full | Real-Time Automatic Cloud Detection Using a Low-Cost Sky Camera |
| title_fullStr | Real-Time Automatic Cloud Detection Using a Low-Cost Sky Camera |
| title_full_unstemmed | Real-Time Automatic Cloud Detection Using a Low-Cost Sky Camera |
| title_short | Real-Time Automatic Cloud Detection Using a Low-Cost Sky Camera |
| title_sort | real-time automatic cloud detection using a low-cost sky camera |
| topic | cloud detection cloud coverage sky camera image processing remote sensing CSP plant solar energy solar irradiance forecasting total sky imagery |
| url | http://hdl.handle.net/10835/8182 |
| work_keys_str_mv | AT alonsomontesinosjoaquinblas realtimeautomaticclouddetectionusingalowcostskycamera |