A Compact Smart Greenhouse for STEM Education: Proof of Concept For Sustainable Food Provision
DOI:
https://doi.org/10.47611/jsrhs.v13i3.7505Keywords:
Automated greenhouse, Aquaponics, Internet of Things (IoT), Raspberry Pi, Computer Vision (CV), Artificial Intelligence (AI), Deep Neural Network (DNN), SpectroscopyAbstract
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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Al-Kodmany, K. (2018). The Vertical Farm: A Review of developments and Implications for the Vertical City. Buildings, 8(2), 24. https://doi.org/10.3390/buildings8020024
Anthonisen, A. C. A., Loehr, R. C. L., Prakasam, T. B. S. P., & Srinath, E. G. S. (1976). Inhibition of nitrification by ammonia and nitrous acid on JSTOR. JSTOR, 48(5). https://www.jstor.org/stable/pdf/25038971.pdf?refreqid=fastly-default%3Aa760285af512ee072914dd1caf204574&ab_segments=&origin=&initiator=&acceptTC=1
Bamsey, M., Graham, T., Thompson, C., Berinstain, A., Scott, A. B., & Dixon, M. A. (2012). Ion-Specific nutrient management in closed systems: The necessity for Ion-Selective sensors in terrestrial and Space-Based agriculture and water management systems. Sensors, 12(10), 13349–13392. https://doi.org/10.3390/s121013349
Bates, R. G., & Pinching, G. D. (1949). Acidic dissociation constant of ammonium ion at 0 to 50 C, and the base strength of ammonia. J. Res. Natl. Bur. Stand, 42(5), 419-430.
Bregliani, M. M., Temminghoff, E. J. M., Van Riemsdijk, W. H., & Haggi, E. S. (n.d.). Nitrogen Fractions in Arable Soils in Relation to Nitrogen Mineralization and Plant Uptake. Communications in Soil Science and Plant Analysis, 37(11–12), 1571–1586. https://doi.org/10.1080/00103620600710124
Carneiro, P. C. F., Swarofsky, E. C., Souza, D. P. E., César, T. M. R., Baglioli, B., & Baldisserotto, B. (2009). Ammonia-, Sodium Chloride-, and Calcium Sulfate-induced Changes in the Stress Responses of Jundiá, Rhamdia quelen, Juveniles. Journal of the World Aquaculture Society, 40(6), 810–817. https://doi.org/10.1111/j.1749-7345.2009.00302.x
DeepFish. (n.d.). https://alzayats.github.io/DeepFish
Dexter Industries. (2016, October 20). Python Library Documentation - Dexter Industries. Retrieved May 30, 2024, from https://www.dexterindustries.com/GrovePi/programming/python-library-documentation/
Estim, A., Shaleh, S. R. M., Shapawi, R., Saufie, S., & Mustafa, S. (2020). Maximizing Efficiency and Sustainability of Aquatic Food Production from Aquaponics Systems - A Critical Review of Challenges and Solution Options. Aquaculture Studies, 20(1). https://doi.org/10.4194/2618-6381-v20_1_08
Isaza, D. F. G., Cramp, R. L., & Franklin, C. E. (2021). Exposure to nitrate increases susceptibility to hypoxia in fish. Physiological and Biochemical Zoology, 94(2), 124–142. https://doi.org/10.1086/713252
Khan, S., Purohit, A., & Vadsaria, N. (2020). Hydroponics: current and future state of the art in farming. Journal of Plant Nutrition, 44(10), 1515–1538. https://doi.org/10.1080/01904167.2020.1860217
Kholis, A., Maipita, I., Sagala, G. H., & Prayogo, R. R. (2022, January). Feasibility study of hydroponics as a home industry. In 2nd International Conference of Strategic Issues on Economics, Business and, Education (ICoSIEBE 2021) (pp. 109-112). Atlantis Press.
Näsholm, T., Kielland, K., & Ganeteg, U. (2009). Uptake of organic nitrogen by plants. New Phytologist, 182(1), 31–48. https://doi.org/10.1111/j.1469-8137.2008.02751.x
National Institute of Standards and Technology [NIST]. (n.d.). NIST Chemistry WebBook. Retrieved May 28, 2024, from https://webbook.nist.gov/chemistry/
NumPy. (2024, February 6). Array objects. Retrieved May 27, 2024, from https://numpy.org/doc/stable/reference/arrays.html
OpenCV. (2024, May 1). OpenCV - Open Computer Vision Library. https://opencv.org/
Perrin, D. D. P. (1982). Ionisation constants of inorganic acids and bases in aqueous solution. In Elsevier eBooks (pp. 1–138). https://doi.org/10.1016/c2013-0-13276-x
Polakof, S., Panserat, S., Soengas, J. L., & Moon, T. W. (2012). Glucose metabolism in fish: a review. Journal of Comparative Physiology. B, Biochemical, Systemic, and Environmental Physiology, 182(8), 1015–1045. https://doi.org/10.1007/s00360-012-0658-7
Politiek, R. (n.d.). Deep learning with Raspberry Pi and alternatives in 2024. Q-engineering. Retrieved May 25, 2024, from https://qengineering.eu/deep-learning-with-raspberry-pi-and-alternatives.html
Raspberry Pi. (n.d.). raspberrypi.com. Retrieved May 25, 2024, from https://www.raspberrypi.com/products/raspberry-pi-4-model-b/
Roboflow. (n.d.). RoboFlow Universe: Open Source Computer Vision Community. https://universe.roboflow.com/
Roboflow. (2023, March 30). Fall Detection Object Detection Dataset. https://universe.roboflow.com/roboflow-universe-projects/fall-detection-ca3o8/dataset/4
Sadoul, B., & Geffroy, B. (2019). Measuring cortisol, the major stress hormone in fishes. Journal of Fish Biology, 94(4), 540–555. https://doi.org/10.1111/jfb.13904
Sardare, M. D., & Admane, S. V. (2013). A review on plant without soil-hydroponics. International Journal of Research in Engineering and Technology, 2(3), 299–304.
Seeed Studio. (2023a, May 15). Grove - Temperature & Humidity Sensor (DHT11). Retrieved June 1, 2024, from https://www.seeedstudio.com/Grove-Temperature-Humidity-Sensor-DHT11.html
Seeed Studio. (2023b, September 7). Grove - Soil moisture sensor. Retrieved June 1, 2024, from https://www.seeedstudio.com/Grove-Moisture-Sensor.html
Seeed Studio. (2024a, May 2). Grove - Relay High current 5V/10A small 1-way mechanical relay switch Arduino. Retrieved June 1, 2024, from https://www.seeedstudio.com/Grove-Relay.html
Seeed Studio. (2024b, May 15). Grove - Light Sensor v1.2 - LS06-S Phototransistor Compatible with Arduino. Retrieved June 1, 2024, from https://www.seeedstudio.com/Grove-Light-Sensor-v1-2-LS06-S-phototransistor.html
Sharma, N., Acharya, S. K., Kumar, K., Singh, N. N., & Chaurasia, O. P. (2018). Hydroponics as an advanced technique for vegetable production: An overview. Journal of Soil and Water Conservation in India, 17(4), 364. https://doi.org/10.5958/2455-7145.2018.00056.5
Somerville, C. S., Cohen, M. C., Pantanella, E. P., Stankus, A. S., & Lovatelli, A. L. (2014). Small-scale aquaponic food production. Food and Agriculture Organization of the United Nations. Retrieved May 25, 2024, from https://openknowledge.fao.org/server/api/core/bitstreams/2ca21047-390f-42cd-bd1d-0c2ebc9c1df2/content
Thingsboard. (n.d.). ThingsBoard — Open-source IoT (Internet of Things) Platform. ThingsBoard. https://thingsboard.io/
Ultralytics. (n.d.). Ultralytics YOLO. Retrieved May 27, 2024, from https://ultralytics.com/yolo
Yamori, W. (2020). Photosynthesis and respiration. In Elsevier eBooks (pp. 197–206). https://doi.org/10.1016/b978-0-12-816691-8.00012-1
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