Abstract
This paper presents the design and implementation of an autonomous sunspot detection and transmission system developed at the observatory of the Geophysical Institute of Peru, in the province of Chupaca. Given the need for real-time solar monitoring systems at national observatories, the first stage involved developing an artificial vision model based on YOLOv7 together with the ODROID H4 Ultra processor. This computational model provides 70% efficiency compared to manual systems, calculated using performance metrics. In the second stage, the solar telescope was equipped with updated solar filters to enhance image recording. The overall operational performance of the system was largely positive, due to the accuracy of detection and ease of data transfer provided by the current processors. Validations between national or international observatories are recommended. Finally, the continuous improvement of the system developed for astronomical and research purposes is considered promising.
| Original language | American English |
|---|---|
| Pages (from-to) | 172-181 |
| Number of pages | 10 |
| Journal | SSRG International Journal of Electrical and Electronics Engineering |
| Volume | 13 |
| Issue number | 2 |
| DOIs | |
| State | Indexed - Feb 2026 |
Bibliographical note
Publisher Copyright:© 2026 Seventh Sense Research Group®. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Keywords
- Astronomical Observatory
- Automation
- Machine Vision
- Real-Time Monitoring
- Sunspot Detection
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