DOI : https://doi.org/10.18517/ijaseit.11.2.13638

Application of Internet of Things in Smart Greenhouse Microclimate Management for Tomato Growth

Nurpilihan Bafdal (1), Irfan Ardiansah (2)
(1) Department of Agriculture Engineering and Biosystem, Faculty of Agro-Industrial Technology, Universitas Padjadjaran, Bandung, Indonesia
(2) Department of Agro-Industrial Technology, Faculty of Agro-Industrial Technology, Universitas Padjadjaran, Bandung, Indonesia
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How to cite (IJASEIT) :
Bafdal, Nurpilihan, and Irfan Ardiansah. “Application of Internet of Things in Smart Greenhouse Microclimate Management for Tomato Growth”. International Journal on Advanced Science, Engineering and Information Technology, vol. 11, no. 2, Apr. 2021, pp. 427-32, doi:10.18517/ijaseit.11.2.13638.
Citation Format :
Microclimate control is very important for the cultivation of plants in greenhouses. Some microclimate variables are temperature and humidity, these variables can be controlled using several methods, one of which is the misting of the cooling system, but this process is still done manually. This research aims to create an internet-of-things-based system to automatically control the greenhouse microclimate, controlled and controlled through a website. The results showed that the system could automatically activate the cooling system misting when the temperature is above 30 ℃ and the humidity is below 80%. The greenhouse microclimate data can be controlled and controlled via the website. The automation system works better in maintaining the greenhouse's microclimate conditions than before using the automation system with a difference of 6.25 ËšC temperature and 28.06% higher humidity. Microclimate data can be displayed and accessed via the website, and minimum and maximum temperatures can be set via the website. The factor that affects the greenhouse temperature is the UV index. The higher the UV index, the higher the temperature. When the UV index reaches < 10, the greenhouse temperature can still be reduced to ± 3 ℃. If the UV index > 10, the temperature can still be reduced to a smaller value. The automation system's microclimate data processing is more effective, accurate, and the performance of the automation system reaches 115.22% but will decrease to 80.40% when the light intensity is high.

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