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18-25 

18 

 

 

 

Article 

Design and develop an IoT automated nutrient 

control in a hydroponic system 
Shim Lih Ching, Tay Fei Siang*, Almon Chai, Chai Pui Ching  

Faculty of Engineering, Computing and Science, Swinburne University of Technology, Sarawak Campus, Kuching, Sarawak 

               A R T I C L E   I N F O 
 

Article history: 
Received 10 March 2025  
Received in revised form 
18 April 2025 
Accepted 30 April 2025 
 
Keywords:  
Automated system, Nutrient Control, IoT,  
Bak Choy, Hydroponics 
 
*Corresponding author 
Email address: 
fstay@swinburne.edu.my 
 
 
DOI: 10.55670/fpll.fusus.3.3.3 
 

A B S T R A C T 
 

Hydroponics farming is becoming increasingly popular due to its consistent 

ability to produce healthier plants in a controlled environment and nutrient 

solution. However, precise and frequent monitoring of the pH, temperature, and 

nutrient level is required in traditional hydroponic systems, which makes the 

labor monitoring process more complex and time-consuming. The aim of this 

study is to present the prototype of an automated nutrient control system that 

is applied in Nutrient Film Technique (NFT) hydroponic systems. The control 

system combines different sensors to monitor pH and EC levels continuously 

with the assistance of an Arduino Uno R3 microcontroller to process real-time 

monitoring data to adjust nutrient ratios dynamically. Meanwhile, the 

observation of lighting duration on indoor plant growth was recorded to justify 

the usage of indoor lighting for growing commercial crops.  In this study, we 

used Dwarf Bak Choy (Brassica rapa chinensis) to evaluate the effects of various 

nutrient solution concentrations and lighting on plant growth.   

 

1. Introduction 

Hydroponic farming is becoming more popular in 

farming industries, and it is commonly integrated with 

sensors for remote monitoring of important nutrient solution 

parameters, such as pH and EC, which are critical for the 

growth of the targeted crop. This project aims to develop an 

automated nutrient control system to eliminate the need for 

labor-intensive manual intervention and provide long-term 

solutions to manage these variables in an NFT hydroponic 

system. By addressing the limitations of traditional 

hydroponics farming during the farmer's manual operations, 

such as managing large plant populations, nutritional inputs, 

and controlling NFT hydroponic environmental parameters.  

The proposed IoT device collects sensor data and transfers it 

to a cloud server for analysis and storage. The growing 

parameters of dwarf Bak Choy (Brassica rapa chinensis) will 

be used to verify the effectiveness of the proposed automated 

control system. The proposed approach aims to enhance the 

growing efficiency and reliability of the Bak Choy by 

observing the adjusted environmental and nutrition data. 

Compared with traditional soil farming, hydroponic farming 

has mitigated challenges of conventional farming, such as soil 

fertility and climate dependencies. However, it still faces 

issues in controlling precise pH and nutrient concentrations 

for promoting plant growth. Two common issues related to 

nutrient concentrations in hydroponic farming are 

insufficient nutrients and excessive concentrations. 

Insufficient nutrients can hinder the growth of the plant, in 

which targeted plant parts such as flowers, the plant body, or 

roots will not grow in time as expected. In contrast, excessive 

concentrations might induce stress and toxicity to plant 

growth, which is applied to sensitive crops such as tomatoes, 

spinach, wasabi, cucumbers, and lettuce [1]. From the result 

observations in Ref [2], for specific tomato species such as 

Rapsodie, moderate increased conductivity increased the 

maximum photosynthetic rate during the vegetative stage 

compared with low and high EC treatment. From the study 

conducted in Ref [3], the article found that excessive alkalinity 

can elevate substrate pH and reduce micronutrient 

availability to plants. The deployed automating systems for 

monitoring nutrient concentrations, pH levels, and water 

regulation offer significant benefits to growers, saving time 

and effort while providing accurate data during plant growth. 

The proposed automation enhances hydroponic systems by 

overcoming the disadvantages of manual nutrient 

management, thereby contributing to the cultivation of 

healthier crops. For many developing countries, an effective 

agricultural system is crucial for their economies to ensure 

targeted yield productivity. The traditional soil farming 

methods often require extensive resources such as land, 

water, and fertilizers, which lead to soil depletion and 

environmental challenges. Food production needs to double 

Future Sustainability 

Open Access Journal 

https://doi.org/10.55670/fpll.fusus.3.3.3 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

August 2025| Volume 03 | Issue 03 | Pages 18-25 

Journal homepage: https://fupubco.com/fusus 

 
ISSN 2995-0473 

mailto:fstay@swinburne.edu.my
https://doi.org/10.55670/fpll.fusus.3.3.3
https://fupubco.com/fusus


SL. Ching et al. /Future Sustainability                                                                                       August 2025| Volume 03 | Issue 03 | Pages 18-25 

19 

 

to meet the high demand from the increasing growth of the 

global population [4]. This necessitates exploring resilient 

food production solutions, especially amidst increasing 

climate instability. Hydroponics farming offers a promising 

solution to these challenges, minimizing land and water usage 

while maintaining high yields compared to traditional soil 

farming. From the recent trend, governments are increasingly 

adopting hydroponic farming in urban areas to enhance food 

accessibility. For example, Singapore has transformed flat 

house residential and commercial building rooftops into Sky 

farms, which leverage advanced hydroponic farming 

technologies to strengthen local food production.  

Among hydroponic methods such as Wick System, Deep 

Water Culture, and Ebb & Flow, Nutrient Film Technique 

(NFT) stands out for its efficiency and common 

implementation. In NFT, a continuous circulated flow of 

shallow and oxygen-rich nutrient solution across the roots 

supports the growth of plants on racks. However, due to the 

cycling flow of the nutrient solution, monitoring and 

controlling water temperature, oxygen contents, pH levels, 

and EC become crucial for optimizing plant growth. Adjusting 

nutrient concentrations and pH levels can ensure targeted 

crops receive adequate nutrition, with verification of the EC 

sensors, which can indicate nutrient concentration levels 

necessary for plant health. This experimental methodology 

can help to propose appropriate adjustments for optimizing 

hydroponic yields and sustainability.  

Deep knowledge of plant nutrition is crucial to justify the 

ratio of nutrients and lighting duration for effective 

automated system implementation. Meanwhile, integrating 

sensor technology for farming automation will help establish 

a proper system for analyzing crop-specific needs and 

environmental impacts.  This project aims to provide insight 

into environmental impacts for plant growth by utilizing a 

proposed IoT monitoring system and developing an 

automated control system for controlling lighting and 

nutrient distribution. Deploying the automation prototype 

addresses the challenges of implementing precise nutrient 

management. The system will ensure controllable nutrient 

distribution during NFT hydroponics, which helps to fill 

current knowledge gaps and offer practical solutions to 

farmers, empowering them with valuable technological tools 

and insights. 

2. Background literature 

Researchers have made significant contributions to 

automation in hydroponics, particularly through adopting IoT 

technologies aimed at enhancing productivity, sustainability, 

and crop yields. IoT systems facilitate precise monitoring and 

regulation of critical environmental factors such as pH levels, 

fertilizer concentrations, humidity, and temperature in 

hydroponic setups. This capability enables more consistent 

control overgrowth conditions, potentially boosting crop 

yields while reducing labor demands. Several studies have 

explored the integration of IoT in hydroponic systems to 

optimize plant growth efficiency. For instance, Mapari [5] 

developed a vertical hydroponic farming system utilizing IoT 

for automated irrigation and real-time pH, TDS, temperature, 

and humidity monitoring. The system, controlled by a Node 

MCU microcontroller, transmits sensor data to a server and a 

mobile app via Wi-Fi. It notifies users of anomalies via email, 

showcasing its novel feature of automated irrigation 

management and remote monitoring capabilities. Similarly, 

Asawari et al. [6] proposed an automated hydroponic system 

leveraging IoT to collect real-time temperature, humidity, and 

pH data for optimal basil plant growth. Their ATMEGA2560 

microcontroller-based system demonstrated a significant 

58% increase in plant growth height over a 10-day period 

compared to traditional outdoor cultivation. In another 

approach, Sisyanyo et al. explored hydroponic smart farming 

using a cyber-physical-social system integrated with 

Telegram Messenger [7]. Their Raspberry Pi-based system 

monitored parameters like light intensity, room temperature, 

humidity, pH, nutrient temperature, and EC in real-time, 

enabling farmers to access instantaneous updates on plant 

conditions. In summary, these studies highlight the recent 

trend of IoT implementation for advancing hydroponic 

farming, adapting in practical usage through enhanced 

automation, real-time monitoring, and improvement of 

agricultural outcomes. In Ref [8], the author suggested that 

the integration of IoT with the automated hydroponic 

systems offers numerous advantages and poses certain 

limitations, such as the setup cost, which can be unaffordable 

for small-scale farming, and reliable internet connections are 

needed to ensure proper monitoring and control in place. In 

addition, the integration of traditional farming with 

technology will cause more technological dependencies, 

which increase vulnerability to technical failures and 

potentially affect crop yields. Specialized knowledge and 

training may pose challenges for some users in system 

operation and maintenance. Moreover, indoor hydroponic 

farming demands significant energy resources for 24-hour 

operation, which could be restricted in areas with limited or 

costly energy supplies.   

Sisyanto et al. [7] mentioned several limitations of IoT 

hydroponic farming, including the accuracy of nutrient 

monitoring, which could be potentially compromised due to 

the installation of multiple sensors for nutrient monitoring. 

The fault of the pH or EC sensors could affect crop growth. 

Additionally, the monthly subscribed internet connection 

requirement for IoT systems could be impractical or costly in 

certain regions or applications for continuous monitoring 

purposes. The study doesn’t integrate output relays for 

electronics devices like humidifiers to regulate moisture 

levels. It excludes camera modules for visual plant growth 

monitoring, which could offer valuable insights into plant 

growth monitoring.  The EC sensor measurement is crucial in 

hydroponics implementation, as it indicates the 

concentration of electrolytes in nutrient solutions [9]. These 

solutions, typically divided into A and B formulations, contain 

essential macronutrients and micronutrients necessary for 

plant growth. Maintaining optimal nutrient levels is crucial; 

insufficient nutrients can lead to plant diseases, while 

excessive levels can foster algae and bacterial growth 

detrimental to plants [10]. Ding et al. conducted studies on 

Bak Choy, determining that an EC range of 1.8 to 2.4 in 

greenhouse conditions resulted in higher photosynthesis 

rates, productivity, and superior yield compared to other 

treatments [9]. The pH levels in hydroponic systems, affecting 

hydrogen ion concentrations, are adjustable using specific 

chemicals like phosphoric acid for lowering pH and potassium 

bicarbonate for raising it [11]. Optimal pH typically falls 



SL. Ching et al. /Future Sustainability                                                                                       August 2025| Volume 03 | Issue 03 | Pages 18-25 

20 

 

within the range of 5.5 to 6.5, as highlighted in various studies 

[12]. Maintaining a slightly acidic pH is preferred to prevent 

the precipitation of essential nutrients like Fe, Mn, Ca, and Mg, 

which occurs at higher pH levels [13]. Higher pH levels also 

reduce the availability of potassium (K) and phosphorus (P) 

in nutrient solutions.  

Light, consisting of seven different colors, profoundly 

influences plant growth along with water, air, space, and 

nutrients. Kui et al. emphasize the roles of red and blue light 

in promoting callus production, assimilate movement, 

biomass accumulation, phototropism regulation, chloroplast 

migration, stomatal opening, leaf expansion, and 

photosynthetic protection [14]. Their research demonstrated 

that lettuce illuminated with RGB (6:2:2) LED light at 150 

μmol.m−2·s−1 PPFD produced healthier, higher-quality yields 

compared to plants under singular or mixed blue and red-

light conditions. Similar studies by Li et al. [15] corroborated 

these findings. Additionally, Mickens et al. studied red Bak 

Choy growth under various LED lighting ratios [16], 

concluding that a 3:1 ratio of red to blue LEDs yielded the 

highest biomass and nutrient content over 28 days of growth.  

3. Methodology 

The prototype's design involves two key aspects: 

hardware and software. The hardware design involves 

installing the NFT hydroponic system and selecting 

appropriate electrical components. On the other hand, the 

software design focuses on developing an Arduino code 

algorithm to enable automated control of the system. Both 

aspects are critical in ensuring the project's successful 

implementation and operation. The NFT hydroponic system 

is designed with three shelves, each featuring four 

rectangular PVC pipes dedicated to plant cultivation. Each 

PVC pipe is equipped with five precisely cut planting holes, 

totaling 20 holes per shelf and 60 across the entire system. 

The dimensions of the rack measure 1.83 meters in length, 

92.5 cm in width, and 92.5 cm in height. 

To ensure optimal root oxygenation, the planting holes 

are precisely 42mm in diameter, accommodating net pots that 

suspend the upper roots above the nutrient solution. The 

proposed design promotes efficient nutrient uptake and 

oxygen absorption from the surrounding air, which is crucial 

for plant growth. For artificial indoor lighting, 14W LED tube 

lights were installed, emitting red, blue, and white light in a 

ratio of 3:2:1, which enhances photosynthesis and supports 

robust plant development by referring to the approach in 

[17]. The proposed hydroponic system shown in Figure 1 

includes three separate 20-liter water reservoir tanks, one for 

each shelf level, allowing separate nutrient solution 

management and experimentation with different growing 

conditions. Each reservoir is equipped with a motor pump to 

deliver mixed nutrient water to the targeted plants on 

shelves. Additionally, air pumps with air stones in each 

reservoir were installed to enhance oxygen content within the 

nutrient solution, promoting plant yield and health. The well-

integrated sensor module for the NFT hydroponic system 

includes several essential parts. The integrated system 

included pH sensors, which measure solution acidity or 

alkalinity based on potential differences detected by the pH 

meter probe, with proper room temperature control ensuring 

precise readings.  

 
Figure 1. Front and back views of the NFT hydroponic setup 

Moreover, an EC sensor supports Arduino integration, 

measuring the nutrition concentration in the flowing nutrient 

solution. To monitor reservoir water temperature, we 

deployed the DS18B20 water temperature sensor, known for 

its waterproof design and high accuracy (±0.5⁰C). These 

sensors can be embedded into an Arduino Mega, and the 

microcontroller will act as the central processing unit to 

receive data and control nutrient distribution. For IoT 

monitoring, data visualization, and management, ThingSpeak 

was utilized as a cloud platform that enables real-time 

streaming, data storage, and visualization of sensor data. This 

solution offers robust integration with Arduino for 

monitoring hydroponic parameters remotely. The integrated 

Arduino Mega system consists of an ESP8266 Wi-Fi module, 

which can provide internet connectivity to support IoT 

applications. The actuator module will control electronics 

components such as a relay for triggering pumps to adjust the 

nutrient solution ratio in reservoirs. Meanwhile, the EC levels 

can be managed with common nutrient solutions A and B 

from Lotus Farm Agritech. The three-level NFT hydroponic 

rack was equipped with 14W LED lights, as mentioned earlier. 

The experiment was conducted in controlled environmental 

conditions with air conditioning to test the growth responses 

of Bak Choy under different lighting durations and nutrition 

ratio setups. The proposed setup method offers various 

advantages, including real-time remote monitoring via 

sensors, streamlined data management with ThingSpeak, and 

precise control through the actuator module. However, due to 

the centralized HVAC, environmental temperature control is 

limited. The proposed experiment will evaluate sensor 

accuracy, IoT integration, standardized experimental 

conditions, and the impact of the environmental conditions 

on plant growth. The proposed control system in Figure 2 is 

designed to align with its objective of enhancing plant growth 

through IoT monitoring and controlling key parameters in the 

nutrient solution. Multiple sensors, such as water flow rate, 

EC, temperature, humidity, and pH, are integrated into the 

embedded electronic system. These sensors were attached to 

an Arduino Mega controller, which enables real-time 

monitoring and control. DHT11 was installed to capture room 

temperature and humidity, YF-S201 is used to measure the 

water flow rate, and DS18B20 waterproof probes were used 

to measure the water temperature.  



SL. Ching et al. /Future Sustainability                                                                                       August 2025| Volume 03 | Issue 03 | Pages 18-25 

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Figure 2. Block diagram of an automated system 

This environmental data is crucial for monitoring 

environmental conditions during plant growth. The data 

collected from these sensors will be uploaded to the online 

server via ThingSpeak for data aggregation, visualization, and 

analysis across six dedicated channels for different lighting 

and nutrient mix growing monitoring purposes. A part of the 

approach of monitoring and regulating the nutrient solution 

will be controlling pH levels in the nutrient solution to 

maintain between 5.5 and 6.5, which is recommended in Ref 

[12].  The system will trigger a pH down dozer pump using 

30% concentrated phosphoric acid to lower the nutrient 

solution pH back into the optimal range if the pH level exceeds 

6.5. This approach controls precise pH control for nutrient 

availability and plant health. The analog EC sensor is 

employed to monitor the concentration of electrolytes in the 

nutrient solution for assessing nutrient concentrations. The 

proposed automated system manages three water reservoir 

tanks, which are tested for optimal EC values through 

controlled mixed A and B solutions as needed. Water 

temperature fluctuations will impact pH and EC values. 

Therefore, the water temperature will be monitored and 

calibrated using data from the DS19B20 temperature probe 

every three days, following the manufacturer's guidelines for 

better pH and EC measurement accuracy.  Due to the 

laboratory sensors being adopted for the automated system 

implementation, the system requires adjustment to address 

sensor immersion limitations and ensure the reliability of 

ongoing operation. The calibration routines were set to 

ensure the sensor system can maintain accurate parameter 

readings, which ensure the targeted commitment to 

optimizing hydroponic conditions for robust plant growth 

and health. As part of the system design, the automated 

system will regulate light duration parameters within the pre-

experimental setup, as shown in Figure 3. The Arduino Mega 

microcontroller is functioning as the principal controller to 

facilitate precise time management for controlling LED tube 

lights based on the predetermined timer settings. For time 

duration monitoring, the system employs a DS3231 RTC time 

stamping module, which will help to enable the activation and 

deactivation of a 5V relay responsible for managing the 

lighting system’s operation. In addition, the RTC module will 

display the current time on an LCD interface connected to the 

Arduino Mega. This feature will provide real-time feedback to 

users and ensure that lighting schedules are maintained 

accurately according to the specified setup. With the 

integration of these components, the automated system can 

improve the efficiency of light regulation in the hydroponic 

system, which can consistently support the optimal growth 

and verification of various lighting durations. There are 

several experimental setups that were conducted to compare 

and verify the performance of different hydroponic systems, 

which mainly focus on plant growth index parameters such as 

height and number of leaves over the growth period. The 

experiments used seeds of the dwarf Bak Choy (Brassica rapa 

chinensis) cultivar, germinated uniformly under controlled 

conditions for 10 days. Afterward, 36 seedlings with 

consistently sized initial leaves were carefully chosen and 

transplanted into the setup. 

 
Figure 3. Circuit diagram of a light control system 

The hydroponic system consisted of three shelves and 

was divided into six sections as shown in Figure 4, with two 

sections per shelf separated by a cardboard divider. Each 

section accommodated six sets of dwarf Bak Choy plants. The 

left side of the shelves was exposed to a 12-hour light cycle 

with alternating 4-hour light and 4-hour dark periods, while 

the right side experienced continuous 24-hour lighting. All 

plants were subjected to identical environmental conditions 

within the same growth room. From Day 7 to Day 25 of the 

experiment, leaf number and plant height measurements 

were taken every three days. 

Figure 5 shows that three different treatments were applied 

to the racks: 

i) Level 1 rack underwent an EC of 0.8 mS/cm for the first 

eight days, followed by 1.7 mS/cm for the subsequent 18 

days. 

ii) Level 2 rack maintained a constant EC of 1.6 mS/cm 

throughout the 25-day experiment. 

iii) Level 3 rack started with an initial EC of 2.1 mS/cm for 

the first eight days, followed by 1.1 mS/cm for the 

remaining 18 days. 

On the 8th day of observation, adjustments were made to the 

water reservoirs of the Level 3 rack to address a sudden drop 

in EC value. Water pumps operated continuously, and pH 

levels were maintained within the range of pH 5.5 – 6.5 

throughout the experiment. All data were collected 

concurrently to ensure consistency and comparability across 

different growth conditions. 



SL. Ching et al. /Future Sustainability                                                                                       August 2025| Volume 03 | Issue 03 | Pages 18-25 

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Figure 4. Three-level rack divided into six sections for each group of 

dwarf Bak Choy 

 

 

 
Figure 5. NFT hydroponic setup 

 

4. Results and discussion 

The growth of dwarf Bak Choy was thoroughly assessed 

using plant height and leaf count as key parameters, with 

significant differences observed across different lighting 

settings. On the Level 1 rack, plants subjected to 12-hour LED 

lighting showed average heights ranging from 1.46 cm to 2.48 

cm over 25 days, while those under 24-hour lighting exhibited 

growth ranging from 3.23 cm to 5.4 cm. Similarly, on the Level 

2 rack, plants under 12-hour lighting grew from 1.54 cm to 

3.12 cm, whereas those under 24-hour lighting grew from 

4.37 cm to 8.23 cm. At Level 3, plants under 12-hour lighting 

grew from 1.34 cm to 3.02 cm, compared to 4.25 cm to 6.68 

cm under 24-hour lighting. Leaf count variations were minor 

initially but became significant from day 16 onwards, with 

plants under 24-hour lighting generally showing greater leaf 

production by day 25. Specifically, plants on 24-hour lighting 

had an average leaf count of 10 to 12 across all levels, while 

those under 12-hour lighting averaged 7 to 9 leaves as shown 

in Figure 6. 

The automated control system effectively managed pH 

and EC values throughout the experiment, as depicted in 

Figure 7. Each rack maintained different EC levels: Level 1 

started at 0.8 mS/cm for eight days, then increased to 1.7 

mS/cm; Level 2 maintained a steady 1.6 mS/cm; and Level 3 

began at 2.1 mS/cm for eight days, then reduced to 1.1 

mS/cm. The system generally maintained EC within the 

specified range, although occasional pH drops below 5.5 

indicated overuse of the pH down doser solution. To address 

this, adjustments in dosing frequency are recommended, 

possibly incorporating a pH up solution for more balanced pH 

management. Overall, while demonstrating effective 

regulation of nutrient solution parameters, the system 

requires fine-tuning to optimize pH control and ensure 

consistent performance across varied experimental 

conditions. 

When comparing the findings of this study to other 

relevant research in automated control systems for nutrient 

distribution in hydroponics, it becomes evident that the 

proposed system demonstrates promising results. In a study 

by Prasetia et al. [18] focusing on IoT-based grow light 

automation, they found that dwarf Bak Choy grown under 

LED lights showed superior performance in terms of fresh 

weight, number of leaves, and plant height compared to those 

grown under sunlight. Especially on the 30th day, the result 

showed the improvement of plant growth, which under LED 

lights averaged 23.6 grams, 11.2 leaves, and 18.1 cm in height, 

compared to that under sunlight, which averaged 20.2 grams, 

9.3 leaves, and 17.1cm. From experimental observation, this 

underscores the positive impact of an automated hydroponic 

system on plant growth and its productivity through the 

controlled environment.  

The result agreed with the LED illumination and IoT 

technology with Zigbee in Ref [19], which explored a smart 

hydroponic system implementation. The article's findings 

discovered improvements over traditional farming methods 

with a 17.2% increase in leaf yield, 29.85% taller plants, and 

14.55% higher in terms of produced weight, which means 

that harvesting can be earlier by two weeks compared to 

conventional farming.  The outcomes showed that the 

duration of LED lighting can promote plant growth, yield, and 

efficiency in agriculture.  

The data collected from the present study aligns with the 

findings from previous studies, which demonstrate 

significant differences in plant height and leaf count across 

different lighting duration settings. Moreover, the automated 

system effectively maintained pH and EC within optimal 

ranges, which offers optimized growth conditions. With the 

controlled environment and nutrient management, the 

automated system not only supports increased yields but also 

promotes sustainable resource use. For different nutrient 

settings, the result showed that there is no significant 

difference between growth in Level 1,2, and 3 racks with 

controlled EC settings.  



SL. Ching et al. /Future Sustainability                                                                                       August 2025| Volume 03 | Issue 03 | Pages 18-25 

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Figure 6. Graphical analysis of plant height and number of leaves of different growth conditions from DAP (Day After Planting) 7 to 25 

Figure 7. Records of pH and EC readings from DAP 1 to 25 for three different levels 



SL. Ching et al. /Future Sustainability                                                                                       August 2025| Volume 03 | Issue 03 | Pages 18-25 

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It is observed that a high nutrient setting at the beginning 

of the growth stage will promote the growth of the Bak Choy, 

as shown in Figure 6, with levels 2 and 3 racks set to have 

more nutrients mixed in the NFT system compared to the 

level 1 rack. Results observed from the level 3 rack showed 

that high conductivity values in nutrient solutions do not 

promote significant plant growth. The result agrees with the 

observation in [2], in which moderate EC treatment increased 

the conductivity, which in turn increased the maximum 

photosynthetic rate compared to high and low EC treatments.  

From the experimental result, this study contributes 

compelling evidence for the effectiveness of automated 

control systems in hydroponic farming. With the integration 

of IoT systems and sensor monitoring, the proposed 

prototype offers pathways to enhance agricultural 

productivity and sustainability.  The findings underscore the 

potential for future improvements in hydroponics practices 

for different target crops, which emphasizes the role of 

technology in driving agricultural innovation and addressing 

sustainable development goals regarding food security 

issues. Several technological aspects were previously 

developed by the authors to monitor the growth rate of the 

plants and their relevant parameters [20- 23]. 

5. Conclusions 

This paper demonstrated the impact of the different 

lightning settings on the Bak Choy growth through an 

automated IoT control system for nutrient and pH control in 

NFT hydroponic systems. The findings indicated that plants 

exposed to 24 hours of lighting showed a significant increase 

in plant growth indices, such as height and leaves, compared 

to those under 12 hours of lighting duration, with variations 

in nutrition distributed across different rack levels. The 

automated system successfully maintained the pH and EC 

levels within the suggested ranges through minor fluctuations 

in pH, which emphasized the need for fine-tuning in dosing 

adjustments or earlier predictions in the pH rising trend. The 

experimental results aligned with the previous studies, which 

support the moderate increase of EC value and will help 

promote higher plant yields, improved growth rates, and 

efficient resource utilization. With the integration of IoT 

monitoring and control, the study suggests the potential of 

automation implementation in enhancing hydroponic 

farming approaches in terms of efficiency. The future work of 

this project should focus on refining pH stability, optimizing 

nutrient dosing strategies, and expanding the automated 

system's adaptability to diverse targeted plants. In the past, 

the team had developed various technological solutions for 

supporting and monitoring plant growth. Eventually, these 

automation implementations contribute to sustainable 

agricultural practices, supporting the Sustainable 

Development Goals and innovation in smart farming 

technologies.  

Ethical issue 
The authors are aware of and comply with best practices in 
publication ethics, specifically with regard to authorship 
(avoidance of guest authorship), dual submission, 
manipulation of figures, competing interests, and compliance 
with policies on research ethics. The authors adhere to 
publication requirements that the submitted work is original 
and has not been published elsewhere. 

Data availability statement 
The manuscript contains all the data. However, more data will 

be available upon request from the authors. 

Conflict of interest 

The authors declare no potential conflict of interest. 

 

 

 

 

 

 

 

 

 

 

 

 

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Abbreviations  
DHT22  Temperature & Humidity Sensor 
DS18B20 Water Temperature Sensor 
EC  Electrical Conductivity 
HAVC  Heating, Ventilation, and Air Conditioning 
IoT   Internet of Things 
LCD  Liquid Crystal Display 
LED  Light-Emitting Diode 
MCU  Micro-Controller Unit 
NFT  Nutrient Film Technique 
pH  Potential of Hydrogen 
PVC  Polyvinyl Chloride 
TDS  Total Dissolved Solids 
PPM  Parts Per Million 
PPFD  Photosynthetic Photon Flux Density 
RTC  Real-Time Clock 



SL. Ching et al. /Future Sustainability                                                                                       August 2025| Volume 03 | Issue 03 | Pages 18-25 

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