Advance an Automated Indoor Hydroponic Unit for Plant Growth Detection with Compatible for Two Different Plant Varieties


  • R.M.U.I. Rathnayake Department of Engineering Technology, University of Ruhuna, Sri Lanka
  • D.N. Liyanage Department of Engineering Technology, University of Ruhuna, Sri Lanka
  • H.C. Ganege Department of Engineering Technology, University of Ruhuna, Sri Lanka
  • E.U.U. Rathnathunga Department of Urban Bioresources, University of Sri Jayewardenepura, Sri Lanka



Arduino, Automated, Hydroponic, Plant Growth, Sensors


The study aimed to design and fabricate an automated indoor hydroponic plant growth chamber, by comparing the manual system to determine plant growth and development and the sub-objective was to send data to the IoT platform. The sensor-based automated system incorporated pH, TDS, temperature, and humidity sensors, controlled by solenoid valves using Arduino. Tomato and lettuce plants were grown in both systems and growth parameters were measured. The results showed that the automated system maintained consistent temperature, humidity, pH, and EC levels similar to the outdoor system (vary in 30-32, 52-79, 5.5-6.5, and 1.5-2.5 dS/m ranges respectively). Furthermore, the automated indoor system significantly enhanced the plant growth of tomato and lettuce plants compared to the manual system. Significantly higher plant heights of 27.9±1.9 cm and 27.4±4.9 cm, the leaf lengths of 3.2±0.1 cm and 3.9±0.1 cm were observed for the tomatoes and the lettuces respectively in the automated indoor system. A significant difference was observed between the SPAD reading of the automated indoor tomato of 30±0.9 and the outdoor tomato of 26±0.4. Similarly, SPAD readings for the automated indoor lettuce of 23±0.3 and outdoor lettuce of 17±0.5 were significantly different (Pr=<0.0001, Pr≤0.05). These findings highlight the effectiveness of the automated hydroponic system in accommodating plant preferences and its potential for improving agricultural practices. By integrating IoT platforms for data analysis, this technology can optimize plant growth, enhance yields, and facilitate informed decision-making in hydroponic farming.


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How to Cite

Rathnayake, . R., Liyanage, D., Ganege, H., & Rathnathunga, E. (2023). Advance an Automated Indoor Hydroponic Unit for Plant Growth Detection with Compatible for Two Different Plant Varieties. Indonesian Journal of Innovation and Applied Sciences (IJIAS), 3(2), 118-132.