Temperature Measurement and Light Intensity Monitoring in Mini Greenhouses for Microgreen Plants Using the Tsukamoto Fuzzy Logic Method

Authors

  • Dea Suryaningsih Universitas Ahmad Dahlan
  • Riky Dwi Puriyanto Universitas Ahmad Dahlan

Keywords:

Tsukamoto Fuzzy Logic, Greenhouse, Microgreen, DHT 11, Grow Light

Abstract

Microgreens are tender young plants that can be harvested as seeds and are a type of vegetable that can be harvested in about 7-14 days. Microgreen growth is influenced by several factors, including ambient temperature and light intensity. Microgreen plants require temperatures between 24°C – 30°C at all times during growth. These microgreen plants were grown on cocopeat growing media and given in a special room called a mini greenhouse with a size of 60 × 50 cm. The research method used is Tsukamoto's Fuzzy Logic. This research aims to make a tool to detect the temperature in a mini greenhouse. The research method used is Tsukamoto's Fuzzy Logic. Increasing temperature stability to keep the temperature in the mini greenhouse room at the ideal temperature. In this study, the sensors used were DHT 11 and grow light lamps. The results of this study indicate that the temperature and light intensity in this mini greenhouse are very stable and are at a temperature of 24°C-30°C with the accuracy of the sensor in this tool showing an error value of 5.39%.

References

A. Alcorta, A. Porta, A. Tárrega, M. D. Alvarez, and M. P. Vaquero, "Foods for plant-based diets: Challenges and innovations," Foods, vol. 10, no. 2, p. 293, 2021, https://doi.org/10.3390/foods10020293.

A. Ghandar, A. Ahmed, S. Zulfiqar, Z. Hua, M. Hanai and G. Theodoropoulos, "A Decision Support System for Urban Agriculture Using Digital Twin: A Case Study With Aquaponics," in IEEE Access, vol. 9, pp. 35691-35708, 2021, https://doi.org/10.1109/ACCESS.2021.3061722.

K. Sun, Y. Song, F. He, M. Jing, J. Tang, and R. Liu, "A review of human and animals exposure to polycyclic aromatic hydrocarbons: Health risk and adverse effects, photo-induced toxicity and regulating effect of microplastics," Science of The Total Environment, vol. 773, p. 145403, 2021, https://doi.org/10.1016/j.scitotenv.2021.145403.

D. A. N. Wulandari, T. Prihatin, A. Prasetyo and N. Merlina, "A Comparison Tsukamoto and Mamdani Methods in Fuzzy Inference System for Determining Nutritional Toddlers," 2018 6th International Conference on Cyber and IT Service Management (CITSM), pp. 1-7, 2018, https://doi.org/10.1109/CITSM.2018.8674248.

U. Jha, L. Tyagi, D. Kansal, S. Chakraborty and A. Singhal, "A Review of Sentiment Analysis Techniques using Soft Computing Approaches," 2021 11th International Conference on Cloud Computing, Data Science & Engineering (Confluence), pp. 119-124, 2021, https://doi.org/10.1109/Confluence51648.2021.9377031.

W. Robson, I. Ernawati, and C. Nugrahaeni, "Design of multisensor automatic fan control system using Sugeno fuzzy method. Journal of Robotics and Control (JRC), vol. 2, no. 4, pp. 302-306, 2021, https://doi.org/10.18196/jrc.2496.

R. Bulgari, M. Negri, P. Santoro, and A. Ferrante, "Quality evaluation of indoor-grown microgreens cultivated on three different substrates," Horticulturae, vol. 7, no. 5, p. 96, 2021, https://doi.org/10.3390/horticulturae7050096.

S. I. Cosman, C. A. Bilatiu and C. S. Marţiş, "Development of an Automated System to Monitor and Control a Greenhouse," 2019 15th International Conference on Engineering of Modern Electric Systems (EMES), pp. 1-4, 2019, https://doi.org/10.1109/EMES.2019.8795186.

C. J. H. Pornillos et al., "Smart Irrigation Control System Using Wireless Sensor Network Via Internet-of-Things," 2020 IEEE 12th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM), pp. 1-6, 2020, https://doi.org/10.1109/HNICEM51456.2020.9399995.

Y. Achour, A. Ouammi, and D. Zejli, "Technological progresses in modern sustainable greenhouses cultivation as the path towards precision agriculture," Renewable and Sustainable Energy Reviews, 147, 111251, 2021, https://doi.org/10.1016/j.rser.2021.111251.

M. Silvana, R. Akbar, Derisma, M. Audina and Firdaus, "Development of Classification Features of Mental Disorder Characteristics Using The Fuzzy Logic Mamdani Method," 2018 International Conference on Information Technology Systems and Innovation (ICITSI), pp. 410-414, 2018, https://doi.org/10.1109/ICITSI.2018.8696043.

D. Gao, G. -G. Wang and W. Pedrycz, "Solving Fuzzy Job-Shop Scheduling Problem Using DE Algorithm Improved by a Selection Mechanism," in IEEE Transactions on Fuzzy Systems, vol. 28, no. 12, pp. 3265-3275, 2020, https://doi.org/10.1109/TFUZZ.2020.3003506.

Y. A. Ahmad, T. Surya Gunawan, H. Mansor, B. A. Hamida, A. Fikri Hishamudin and F. Arifin, "On the Evaluation of DHT22 Temperature Sensor for IoT Application," 2021 8th International Conference on Computer and Communication Engineering (ICCCE), pp. 131-134, 2021, https://doi.org/10.1109/ICCCE50029.2021.9467147.

R. F. Rahmat, T. Z. Lini, Pujiarti and A. Hizriadi, "Implementation of Real-Time Monitoring on Agricultural Land of Rice Plants Using Smart Sensor," 2019 3rd International Conference on Electrical, Telecommunication and Computer Engineering (ELTICOM), pp. 40-43, 2019, https://doi.org/10.1109/ELTICOM47379.2019.8943912.

B. Yimwadsana, P. Chanthapeth, C. Lertthanyaphan and A. Pornvechamnuay, "An IoT Controlled System for Plant Growth," 2018 Seventh ICT International Student Project Conference (ICT-ISPC), pp. 1-6, 2018, https://doi.org/10.1109/ICT-ISPC.2018.8523886.

H. Hashim, S. F. B. Salihudin and P. S. M. Saad, "Development of IoT Based Healthcare Monitoring System," 2022 IEEE International Conference in Power Engineering Application (ICPEA), pp. 1-5, 2022, https://doi.org/10.1109/ICPEA53519.2022.9744712.

N. Z. Malika, R. Ramli, M. H. Alkawaz, M. G. Md Johar and A. I. Hajamydeen, "IoT based Poultry Farm Temperature and Humidity Monitoring Systems: A Case Study," 2021 IEEE 9th Conference on Systems, Process and Control (ICSPC 2021), pp. 64-69, 2021, https://doi.org/10.1109/ICSPC53359.2021.9689101.

Sunardi, A. Yudhana and Furizal, "Tsukamoto Fuzzy Inference System on Internet of Things-Based for Room Temperature and Humidity Control," in IEEE Access, vol. 11, pp. 6209-6227, 2023, https://doi.org/10.1109/ACCESS.2023.3236183.

U. Ghani, I. S. Bajwa, and A. Ashfaq, "A fuzzy logic based intelligent system for measuring customer loyalty and decision making," Symmetry, vol. 10, no. 12, p. 761, 2018, https://doi.org/10.3390/sym10120761.

D M. S. Hadi, S. Bhima Satria Rizki, M. A. As-Shidiqi, M. L. Arrohman, D. Lestari and M. Irvan, "Smart Greenhouse Control System For Orchid Growing Media Based On IoT And Fuzzy Logic Technology," 2021 1st International Conference on Electronic and Electrical Engineering and Intelligent System (ICE3IS), pp. 165-169, 2021, https://doi.org/10.1109/ICE3IS54102.2021.9649684.

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Published

2023-08-15

How to Cite

[1]
D. Suryaningsih and R. D. Puriyanto, “Temperature Measurement and Light Intensity Monitoring in Mini Greenhouses for Microgreen Plants Using the Tsukamoto Fuzzy Logic Method”, Buletin Ilmiah Sarjana Teknik Elektro, vol. 5, no. 3, pp. 336–350, Aug. 2023.

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