IoT-based Closed Algal Cultivation System with Vision System for Cell Count through ImageJ via Raspberry Pi

Spirulina platensis and other microalgae are now being considered in the different fields of research. It is due to the former’s endless potential let alone, its high protein content. That is why, a stable demand of microalga production is now necessary. To achieve a high-protein spirulina, its cultivation using closed algal cultivation requires monitoring and maintenance of the bio-environmental factors and parameters affecting its growth to provide a stable and efficient production of microalgae. Meanwhile, laboratories that culture spirulina determine its cell count through manually counting the cells under a microscope – a tedious work. This establishes the need to construct a device that cultivates spirulina with maintaining and cell counting capabilities. Thus, the proponents developed a culturing device that has three main systems. The first system is tasked to maintain the bio-environmental parameters, such as the pH level, temperature, and light. The second system on the other hand speaks of the cell counting system through ImageJ’s Image Processing. This system verifies the cell count and growth through counting the filaments of the spirulina. Lastly, a corresponding Android application, which was developed using Firebase and Android Studio, displays real-time values of the culture’s parameter. Results show that the device was able to stabilize its parameters. Also, red LEDs exhibited 28.43% higher approximate cell count than red-blue LEDs. With this, the quality of the Spirulina that was produced throughout the study was improved. Lastly, the use of ImageJ’s image processing feature showed no significant difference with manual counting. It also releases the results multiple times faster than the manual counting. Thus, being a better alternative to manual cell counting.

@article{Tolentino2021,
  title     = {IoT-based Closed Algal Cultivation System with Vision System for Cell Count through ImageJ via Raspberry Pi},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {12},
  number    = {7},
  year      = {2021},
  publisher = {The Science and Information Organization},
  author    = {Lean Karlo S. Tolentino and Sheila O. Belarmino and Justin Gio N. Chan and Oliver D. Cleofas Jr and Jethro Gringo M. Creencia and Meryll Eve L. Cruz and JC Glenn B. Geronimo and John Peter M. Ramos and Lejan Alfred C. Enriquez and Jay Fel C. Quijano and Edmon O. Fernandez and Maria Victoria C. Padilla},
  doi       = {10.14569/IJACSA.2021.0120732},
  url       = {https://doi.org/10.14569/IJACSA.2021.0120732}
}