TELKOMNIKA Telecommunication Computing Electronics and Control Vol.
No.
April 2026, pp.
ISSN: 1693-6930.
DOI: 10.
12928/TELKOMNIKA.
Smart hydroponic greenhouse with solar energy for urban Zeluyvenca Avista.
Muhammad Asep Rizkiawan.
Yudha Witanto Department of Mechatronics.
Takumi Polytechnic.
Bekasi.
Indonesia
Article Info
ABSTRACT
Article history:
Increased industrial activity in South Cikarang has limited the availability of agricultural land, encouraging the adoption of controlled environment agriculture systems.
This study describes the design and implementation of a smart hydroponic greenhouse that is fully supported by a 600 Wp solar photovoltaic (PV) system and controlled using an industrial-grade programmable logic controller (PLC).
This system automatically regulates temperature and humidity through exhaust fans and sprayers based on realtime sensor feedback.
Experimental results show that when the internal temperature exceeds 31 AC, the control system recovers to 29.
7 AC within 15 minutes and maintains a temperature range of 24Ae30 AC.
Relative humidity is maintained within the optimal range of 75Ae90%.
The PV system produces an average daily energy output of approximately 2.
0 kWh, resulting in an energy self-sufficiency ratio (ESR) of 138%, which indicates excess energy production compared to system demand.
These results prove that the integration of industrial automation with renewable energy provides reliable environmental control, high energy efficiency, and operational stability for hydroponic greenhouse applications in urban industrial areas.
Received Oct 27, 2025 Revised Jan 14, 2026 Accepted Jan 30, 2026 Keywords:
Food security Hydroponics Industrial areas Programmable logic controller Smart greenhouse Solar photovoltaic Urban agriculture This is an open access article under the CC BY-SA license.
Corresponding Author:
Muhammad Asep Rizkiawan Department of Mechatronics.
Takumi Polytechnic Bekasi Regency.
West Java 17530 Indonesia Email: asep.
mar@takumi.
INTRODUCTION
The rapid growth of urbanization and industrial development has intensified land-use competition and environmental degradation in developing countries .
In particular, the South Cikarang region in West Java.
Indonesia, has transformed into a densely industrialized zone, leading to the conversion of agricultural land into factories and infrastructure .
This phenomenon has triggered two critical issues: the diminishing availability of fertile land for food production and the decline of soil quality due to industrial pollutants .
Ae.
These factors, in turn, threaten local food security and increase the communityAos dependency on external food distribution networks, which are often vulnerable to logistical and economic disruptions .
To address these challenges, urban agriculture has gained momentum as a viable alternative to conventional farming, especially in land-constrained areas.
One of the most promising approaches is hydroponics, a soilless cultivation system that allows plants to grow in nutrient-rich water solutions .
Ae.
Hydroponic systems, when integrated into greenhouses, can provide a controlled microclimate environment that optimizes plant growth, conserves water, and maximizes land efficiency .
Ae.
The application of automation and internet of things (IoT)-based monitoring has further enhanced the efficiency and productivity of hydroponic greenhouses .
Ae.
Despite these advances, several limitations remain.
Many existing smart farming solutions are based on microcontroller platforms such as Arduino and ESP32 .
Ae.
While suitable for prototyping and Journal homepage: http://journal.
id/index.
php/TELKOMNIKA A ISSN: 1693-6930 academic studies, these devices often lack the robustness, processing capability, and scalability required for long-term .
deployment in industrial or semi-urban contexts.
Furthermore, many of these systems implement only partial automation such as temperature control or irrigation timing rather than comprehensive, multi-variable environmental management.
Additionally, the reliance on grid electricity makes them vulnerable to power interruptions, which can be frequent in semi-urban industrial zones.
Many studies on greenhouses, smart farming, and hydroponics have not yet integrated programmable logic controller (PLC) control with assisted or partial energy sources from solar power plants .
Ae.
Renewable energy, particularly solar photovoltaic (PV) technology, offers a compelling solution for enhancing the autonomy and resilience of smart agricultural systems .
, .
Solar energy can be harnessed to power critical greenhouse operations such as pumps, lighting, sensors, and control units, thereby reducing dependency on fossil fuels and central grid infrastructure .
However, the integration of solar PV systems with robust, industrial-grade automation in hydroponic greenhouses remains limited in existing studies.
This research presents a smart hydroponic greenhouse that integrates renewable energy with PLC-based automation to control key environmental parameters, including temperature, humidity, potential of hydrogen .
H), and light intensity, within a modular structure.
A small-scale solar PV system is utilized as backup power to ensure operational continuity during grid outages.
Compared to microcontroller-based approaches, the use of PLCs provides superior signal stability, environmental robustness, programming flexibility, and compatibility with industrial sensors and actuators .
, .
The objectives of this study are fourfold: .
to design a scalable hydroponic greenhouse system that is suitable for limited urban land, .
to integrate a solar-assisted backup power source, .
to implement precise automation of key climate parameters using PLCs, and .
to demonstrate the feasibility of the system as a replicable model for food production in industrial urban zones.
A prototype unit will be built on a university campus in South Cikarang, serving both as a research model and a community empowerment center.
The novelty of this research lies in three main aspects: .
the integration of multi variable environmental control using PLC in a hydroponic system, .
the combination of renewable energy through a solar power plant system .
embangkit listrik tenaga surya.
PLTS) with industrial grade automation in a low-cost, replicable model, and .
the real-world deployment of the system to empower communities in regions facing urban agricultural METHOD Site and system overview This study was conducted in South Cikarang.
West Java, an industrial area with limited agricultural A modular hydroponic greenhouse prototype was developed on a campus site, integrating an nutrient film technique (NFT) hydroponic system, a fully solar-powered energy supply, and PLC-based automation.
The system consists of a modular greenhouse structure.
PV unit with battery storage, environmental sensors, and automatically controlled actuators.
The overall system configuration is shown in Figure 1.
Figure 1.
Integrated greenhouse system scheme TELKOMNIKA Telecommun Comput El Control.
Vol.
No.
April 2026: 727-736 TELKOMNIKA Telecommun Comput El Control System design and implementation Greenhouse hydroponic modular design The greenhouse was designed as a compact modular structure for efficient space utilization in industrial urban areas.
An NFT hydroponic system was implemented to optimize water and nutrient use, supported by integrated lighting, ventilation, sensors, and actuators for environmental control.
The system consists of a modular greenhouse frame, hydroponic growing bed, nutrient tank.
PLC control cabinet, and a PV power unit, as shown in Figures 2 and 3.
Environmental parameters including temperature, humidity, light intensity, and pH are monitored in real time, while the PLC automatically controls pumps, exhaust fans, and All electrical loads are fully supplied by a solar PV system with battery storage, enabling autonomous and scalable greenhouse operation.
Figure 2.
The dimensions of the greenhouse plan Figure 3.
Three-dimensional design of the proposed PLC-based smart greenhouse powered by PV solar energy System block diagram description All greenhouse energy demands including sensors, pumps.
PLC, lighting, and ventilation are fully supplied by a standalone off-grid PLTS.
The system uses 600 Wp monocrystalline PV modules, a 24 V / 100 Ah deep-cycle battery for 24-hour operation, and a hybrid inverter 2000 W and 30 A with MPPT charge controller for stable power conversion.
The total daily energy consumption .
aycycuycycayco ) was estimated based on the connected electrical loads.
yaycycuycycayco = Ocycuycn=1 ycEycn ycu ycycn ycEycn is the rated power of each load .
PLC, fan, light-emitting diode (LED)) ycycn is the operational time .
ours/da.
The overall configuration of the PV-powered smart greenhouse is shown in Figures 4.
The system consists of two main subsystems: a renewable energy subsystem and a PLC-based automation and control The PV subsystem supplies off-grid electrical power through PV modules, battery storage, and an The automation subsystem integrates a PLC, humanAemachine interface (HMI), sensors, and actuators to regulate temperature, humidity, and nutrient levels.
Based on sensor feedback, the PLC automatically controls exhaust fans, sprayers, and pumps, while the HMI enables real-time monitoring and manual control.
This integrated architecture ensures stable and autonomous greenhouse operation.
Figure 4.
Block diagram of the integrated PLC-based smart greenhouse system powered entirely by PV solar Smart hydroponic greenhouse with solar energy for urban agriculture (Zeluyvenca Avist.
A ISSN: 1693-6930 Data acquisition, logging process and system integration Data acquisition and logging are handled by the PLC as the central controller.
Environmental parameters and actuator status are periodically collected, processed, and displayed in real time on the HMI.
All data are logged as time-series records for performance evaluation and control optimization, supporting both real-time monitoring and offline analysis.
The system integrates a PV power subsystem with a PLC-based control and monitoring interface for fully off-grid operation.
The PLC processes sensor inputs and regulates actuators based on predefined temperature (<30 AC) and humidity .
Ae90%) setpoints.
System components communicate through standard industrial interfaces, while the HMI provides real-time visualization and manual control.
This architecture ensures reliable, energy-autonomous, and scalable greenhouse operation.
The interface can be seen in Figure 5.
Figure 5.
HMI system Experimental setup and measurement procedure The experimental setup was designed to evaluate a PLC-controlled smart greenhouse powered by a standalone PV system.
The prototype was installed at Politeknik Takumi.
South Cikarang, under semi-urban conditions with high solar exposure.
The greenhouse features a modular polycarbonate structure and an NFT hydroponic system.
Automation is handled by a Haiwell PLC interfaced with temperature humidity, pH, and total dissolved solids (TDS) sensors, and actuators including exhaust fans, sprayer pumps, and solenoid valves.
A 600 Wp PV array with a 24 V/100 Ah battery, maximum power point tracking (MPPT) controller, and inverter supplies full off-grid power.
System performance was tested for one week under varying weather conditions to evaluate control stability, energy self-sufficiency, and system reliability.
Figure 6 is a real-world Figure 6.
The implemented smart greenhouse powered by PV system
RESULTS AND DISCUSSION
System performance overview The implemented solar-powered PLC-based greenhouse automation system was tested continuously for one week under varying solar radiation and ambient temperature conditions.
The results show that the system maintained stable environmental parameters within the predefined setpoints, with all electrical loads TELKOMNIKA Telecommun Comput El Control.
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No.
April 2026: 727-736 TELKOMNIKA Telecommun Comput El Control fully supplied by the PV system.
Average daily solar energy production ranged from 1.
86 to 2.
03 kWh/day, with an overall system efficiency of approximately 75%, including inverter and battery losses.
The greenhouseAos total daily energy consumption was about 1.
45 kWh/day, as detailed in Table 1.
yaycycuycycayco = Ocycuycn=1 ycEycn ycu ycycn Table 1.
Total load consumption Load Water pump Lamp PLC device Water pump Simizu Motor spray Exhaust Load total Total Watts 432 Watt Time .
Energy (Wh/da.
1449 Wh/day Environmental control performance The PLC control system maintained stable greenhouse conditions during testing.
As shown in Figure 7, internal temperature remained below 30 AC despite ambient temperatures above 33 AC, while relative humidity was controlled within 75Ae90%.
Control actions were automatically executed through exhaust fan and sprayer activation based on real-time sensor feedback.
These results confirm that PLC-based automation ensures stable and reliable microclimate regulation suitable for industrial urban environments.
Environmental control rules are summarized in Table 2.
The system can generally reduce the temperature from peak .
AC) to below 30 AC within 30-40 minutes with the systemAos blower.
For humidity, improvement from 70-75% to the target of 82-85% was achieved more quickly about 15-25 minutes when the sprayer was turned on with the prototype design spray The blower sprayer combination .
imultaneous actio.
gave the shortest stabilization time .
, as both variables were controlled simultaneously and did not work against each other.
For excessive humidity conditions .
, the short blower pulse strategy .
minutes every 30 minute.
was effective in holding RH O 90% while saving battery energy.
Furthermore, the time-series graph .
emperature and RH vs tim.
can be seen in Figure 7.
The Figure 7 presents the temperature and humidity response of the PLC-controlled, solar-powered greenhouse under varying daily conditions.
At 08:00, stable conditions were observed .
8 AC, 75% RH).
When temperature rose to 34.
7 AC at 14:00, the PLC activated the exhaust fan, stabilizing temperature at 5 AC.
During nighttime .
:30Ae22:.
, humidity exceeded 90%, triggering the sprayer system and restoring humidity to 88Ae89%.
On average, the system returned environmental conditions to target ranges within 5Ae10 minutes after deviation, confirming effective microclimate regulation using PLC-based control powered entirely by solar energy.
Figure 7.
The time-series graph .
emperature and RH vs tim.
Smart hydroponic greenhouse with solar energy for urban agriculture (Zeluyvenca Avist.
A ISSN: 1693-6930 Table 2.
Environmental control testing Time
Measured Temp
(AC)
08:00
Measured (RH, %) Activation .
Time to .
Sprayer Stabilized .
AC / RH, %) 0/82 11:30 Temp > 27 AC .
igh Exhaust blower ON 8/70 14:00 Temp > 27 AC and RH < 80% .
oth Blower ON sprayer Blower 30 / 5/83 Temperature slightly >30 and RH > 90% .
igh Blower ON .
sprayer OFF
7/88
RH > 90%
xcess humidity at Blower .
eriodic 3 min every 30 min .
N/A .
5/89Ae90 Trigger Actuator.
RH < 80% .
ow 18:30 22:00 Remarks Sprayer cycle 20 min.
reached 82% after 20 min, stabilized at 25 min due to Blower airflow RH rises slightly after cooling but remains < 80% Blower reduces temp while sprayer restores RH.
stabilizes after 38 min Blower reduces temp and lowers RH by sprayer kept off to avoid overhumidity Night strategy:
short blower
pulses to keep
RH O 90%
without cooling below crop Energy flow and autonomy analysis Figure 7 shows the energy flow profile between the PV array, battery, and load throughout a typical testing day.
During peak solar hours .
:00Ae14:.
, the PV array generated surplus energy that simultaneously powered all greenhouse loads and recharged the battery bank.
At night or during low-irradiance periods, the stored energy supplied the automation system through the inverter.
The battery discharge depth remained below 35%, ensuring long-term sustainability and minimizing degradation.
The energy self-sufficiency ratio (ESR) was calculated as .
yaycIycI = yaycIycI = yaycEycO ycu100% .
ycu100% = 138% .
yayaycuycaycc This result indicates that the system can operate autonomously without any external grid support while maintaining energy reserve capacity.
Reliability and system response analysis The PLC executed sensor scanning and actuator response cycles with a scan time of approximately 50 ms, ensuring a near real-time response.
No communication delay or actuation failure was observed during Table 3 shows a series of performance parameters for the system.
The high stability index (>95%) indicates that the PLC control system and the solar power source worked in synchrony to maintain optimal operational parameters throughout the observation period.
TELKOMNIKA Telecommun Comput El Control.
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April 2026: 727-736 TELKOMNIKA Telecommun Comput El Control Table 3 summarizes the overall system performance indicators obtained during the experiments Parameter Temperature (AC) Humidity (%) ESR (%) PLC response time .
Uptime (%) Target
O 30
75Ae90
O100
Measured average Stability index (%) Comparative discussion and summary discussion Compared to previous studies .
, .
that implemented Arduino or ESP32-based greenhouse automation systems powered by power grid.
Previous research used PLC system control .
Ae.
but still not integrated with renewable energy, namely solar energy using solar panels with a solar power generation system.
this study introduces a fully autonomous industrial-grade control system powered entirely by solar energy.
The PLC-based approach offers higher reliability for continuous operation, faster and deterministic control responses, and improved scalability for multi-greenhouse deployment.
Its compliance with industrial automation standards makes it suitable for large-scale applications.
Combined with PLTS as a renewable energy source, the system provides a practical and sustainable solution for smart agriculture in industrial and semi-urban areas with limited land and grid power availability.
The experimental results confirm the feasibility and reliability of the proposed solar-powered PLCbased greenhouse system.
All operational processes were fully supported by the PV system, enabling complete off-grid operation with stable energy supply under typical weather conditions.
The PLC control algorithm effectively maintained the greenhouse microclimate, keeping temperature below 30 AC and humidity within 75Ae90%, with stabilization achieved within 7Ae10 minutes after deviations occurred.
Real-time monitoring and manual override through the HMI enhanced operational flexibility, while the use of an industrial PLC ensured reliable, deterministic, and scalable control compared to microcontroller-based systems.
Battery-supported energy management also provided resilience under variable solar irradiance.
Overall, the integration of PV energy and PLC automation offers a robust and sustainable solution for greenhouse operation in energyconstrained and industrial urban environments, with future potential for cloud-based monitoring and predictive control enhancements.
CONCLUSION
Based on experimental evaluation, the PV-powered PLC-based greenhouse system successfully maintained optimal microclimate conditions in an autonomous and energy-independent manner.
The integrated control system effectively regulated temperature below 30 AC and relative humidity within 75Ae90%, restoring stable conditions within 5Ae10 minutes after deviations through automatic activation of exhaust fans and These results confirm that the research objectives outlined in the Introduction have been achieved.
The full utilization of solar energy ensures sustainable operation, while the integration of PLC and HMI enables reliable automation, real-time monitoring, and manual override when required.
The proposed system demonstrates a scalable and robust solution for smart greenhouse applications in urban and industrial areas with limited land and energy access.
Future development will focus on integrating IoT connectivity for remote monitoring and cloud-based data analytics, as well as implementing adaptive control strategies to further enhance system efficiency and intelligence.
Overall, the proposed system contributes to the advancement of sustainable and resilient agricultural technology suitable for industrial regions such as South Cikarang.
ACKNOWLEDGMENTS
This research was funded by the Ministry of Education.
Science, and Technology of the Republic of Indonesia (KEMENDIKTI SAINTEK RI) under the Beginner Lecturer Research Program (Penelitian Dosen Pemula.
PDP) scheme for the fiscal year 2025.
The authors acknowledge Politeknik Takumi for providing research facilities and laboratory support, and the Mechatronics Laboratory team for their assistance during system implementation and testing.
FUNDING INFORMATION
This research was funded by the Ministry of Education.
Science, and Technology of the Republic of Indonesia (KEMENDIKTI SAINTEK RI) under the Beginner Lecturer Research Program (Penelitian Dosen Pemula.
PDP) scheme for the fiscal year 2025.
Smart hydroponic greenhouse with solar energy for urban agriculture (Zeluyvenca Avist.
A ISSN: 1693-6930
AUTHOR CONTRIBUTIONS STATEMENT
This journal uses the Contributor Roles Taxonomy (CRediT) to recognize individual author contributions, reduce authorship disputes, and facilitate collaboration.
Name of Author Zeluyvenca Avista Muhammad Asep Rizkiawan Yudha Witanto C : Conceptualization M : Methodology So : Software Va : Validation Fo : Formal analysis ue ue ue ue ue ue ue ue ue ue ue ue ue ue I : Investigation R : Resources D : Data Curation O : Writing - Original Draft E : Writing - Review & Editing ue ue ue ue ue ue ue ue ue ue ue ue ue Vi : Visualization Su : Supervision P : Project administration Fu : Funding acquisition CONFLICT OF INTEREST STATEMENT The authors declare that there is no conflict of interest regarding the publication of this paper.
DATA AVAILABILITY
The data supporting the findings of this study will be available at researchgate https://w.
net/publication/401156746_Human_Machine_Interface_data after a waiting period of 6 months from the date of publication to allow for the commercialization of research findings.
REFERENCES