Project demonstrates aquaponic greenhouse effectively blends STEM education with sustainable practices, suggesting the potential for smart autonomy.
Sustainable and efficient agricultural production methodologies are essential for the future, relying neither on land area nor manual labour. This project presents an aquaponic greenhouse model designed for STEM education, particularly in physics, chemistry, and ecology. A computer vision module developed via deep learning serves as a proof of concept for automating the data collection and monitoring of ecological variables relevant to fish and plant health within the greenhouse. The system can be extended to accurately control these variables using an artificially intelligent model. Future development will include the non-invasive measurement of microorganism and ion concentrations using spectroscopy, and the application of more rigorous data collection and data analytics.
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Hoang et al. (2024) studied this question.
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