Abstract
The smart heliostat is a concept that arises from applying artificial intelligence and computer vision techniques, mainly the machine learning technique called object detection, to the traditional heliostat to increase its efficiency and reduce costs [1,2]. Continuing with previous work at CIEMAT-PSA focused on the development of a smart heliostat and especially the solar tracking subsystem [3], a powerful tool (Hel-IoT web server) has been developed helping us with the laborious task of creating the dataset and training the model employed for object detection in solar tracking. The main goal of the Hel-IoT web server is to enhance the image data set employed to train new models and, at the same time, to improve the model that the web server is continuously running. The first conclusions that it can be extracted from the use of the Hel-IoT web Server for more than 4 working months is that it is a very powerful tool for the creation of labeled data sets with meteorological information, especially for the creation of data sets for smart heliostats. Furthermore, thanks to the joint use of CETA cluster (Centro Extremeño de Tecnologías Avanzadas), the Hel-IoT web server can improve the model automatically by periodically retraining it.
Funder
Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas
Ministerio de Ciencia e Innovación
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