Automated Black Soldier Fly Incubator using Internet-of-Things and Computer Vision

Black Soldier Fly Larvae (BSFL), Hermetia illucens, have proven to convert organic waste into cheap and high-quality animal protein feed and residue frass fertilizer (a mixture of digested biowaste, larval feces, and chitin-rich exuviae) for soil enrichment while addressing the dual problem of mismanagement of organic waste and climate change. People have already discovered the benefits of these flies and are using traditional approaches to rear them. However, BSFL is challenging to breed due to its sensitivity to external conditions such as temperature, humidity, lighting, and rearing medium. Rearing them in a natural environment may lengthen their lifecycle as well as affect the by-products of each stage. This paper, therefore, presents a design of a system that automates the regulation and control of ambiance in a Black Soldier Fly (BSF) farm using Internet-of-Things (IoT) and monitors the health of produced larvae using Computer Vision. Results after testing the proposed system support the viability of the automated system in Black Soldier Fly rearing, with the mechanical subsystem showing structural integrity, the system effectively maintaining optimal environmental conditions (temperature: 27-32°C, humidity: 60-70%, light intensity: 100400 lux and organic waste moisture: 60-70%) and the system demonstrating energy reliability by its ability to changeover promptly between power from the grid and solar.