In this work, a new approach for Sun tracking systems is presented. Due to the current system limitations regarding costs and operational problems, a new approach based on low cost, computer vision open hardware and deep learning has been developed. The preliminary tests carried out successfully in Plataforma solar de Almería (PSA), reveal the great potential and show the new approach as a good alternative to traditional systems. The proposed approach can provide key variables for the Sun tracking system control like cloud movements prediction, block and shadow detection, atmospheric attenuation or measures of concentrated solar radiation, which can improve the control strategies of the system and therefore the system performance.
In this work, we have studied the relationship among the colorimetric properties of different types of paper, having different finishing and grammage. Their color reproduction capability has also been analyzed by using the same printing technology (inkjet printing). On the one hand, we have plotted CIELAB data under the illuminant D50 into constant lightness and hue-angle planes to be compared with MacAdam limits and with Pointer's real-world surface color. On the other hand, we have calculated the volume gamut of the color solid associated to each color paper gamut. Analyzing the results, we have checked that there is not any clear relationship among the colorimetric properties of paper (for instance, CIE whiteness index, etc.) and the color gamut volume associated. However, the colorimetric parameters associated to the printed sample showed a quite good linear correlation between the minimum lightness (or the maximum blackness value) of the printed color chart and the color gamut volume. In particular, the greatest color gamut volume corresponds to the glossy papers taking into account this correlation for inkjet printing.
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