Design of a Sun Tracking System Based on the Brightest Point in Sky Image - Ching-Chuan Wei; Yu-Chang Song; Chuan-Bi Lin; Chiang, Lawrence (2016 Third International Conference on Computing Measurement Control and Sensor Network (CMCSN), 2016)
It is inevitable for human beings to face exhaustion of fossil energy. Finding an alternative energy source that can sustain global demand for energy is one of the most crucial and critical challenges faced by today's society. In addition, the air pollution caused by fossil energy such as particulate matter (PM 2.5) is becoming more substantial. As a result, solar energy is certainly an energy source worth exploring and utilizing because of the environmental protection. In this article, the camera of Raspberry pi was used as the main sensor, and Raspberry pi is the processor for processing images captured by the Camera. Colored images are then transformed into grey image through Python language and Open CV. Then through Gaussian Blur, the noises were removed. Then, we searches for the highest gray level pixels, which are the brightest spot in sky image. Therefore, it is logical to assume the location of brightest point as the location of sun. Finally, the location information was sent to two servo motors that are capable of moving both horizontally and vertically to track the sun. This article has successfully captured the brightest spot of the sun for tracking. In comparison with the existing methods of tracking the sun, such as Hough Transform, our method based on the brightest point in sky image remains accurate under various conditions such as sunny day, cloudy day and building shelter. In summary, this article shows the advantages of our method over traditional methods.