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Design and Implementation of a Smart Sensing IoT System for Cost-Effective Greenhouse Environmental Monitoring and Control Cover

Design and Implementation of a Smart Sensing IoT System for Cost-Effective Greenhouse Environmental Monitoring and Control

Open Access
|May 2026

Figures & Tables

Figure 1:

Research locations: (A) the red circle on the map of Thailand indicates Songkhla Province, (B) the red pin on the map shows Songkhla Rajabhat University, and (C) experimental greenhouse.

Figure 2:

Low-cost sensor connection architecture for environmental measurement.

Figure 3:

Schematic diagram revealing the monitoring and control system for the greenhouse.

Figure 4:

The electronic circuit presents the integration of the sensor with the ESP32 microcontroller. Here DAT = Data Line, GND = Ground, SCL = Serial Clock Line, and SDA = Serial Data Line.

Figure 5:

FL flow diagram for greenhouse environmental control. FL, fuzzy logic.

Figure 6:

Fuzzy input variable membership functions.

Figure 7:

Web application system architecture that allows monitoring in real time.

Figure 8:

Web application interface displaying greenhouse environmental data.

Figure 9:

Control system interface of the web application for manual and automatic operations.

Figure 10:

Sensor installation inside the greenhouse: (A) SHT30 Sensor to measure temperature and humidity, (B) Moisture & pH Sensor, (C) BH1750FVI Ambient Light Sensor, (D) misting device for temperature and humidity control, and (E) watering system for soil moisture regulation.

Figure 11:

Hourly error distribution.

Figure 12:

Average% error of each sensor compared to standard equipment.

Figure 13:

Temperature response and fuzzy membership regions.

Figure 14:

Soil moisture response and fuzzy membership regions.

The costs required to develop the prototype

No.Sensors/devicePrice/unit (US$)
1SHT30 sensor8.67
2Moisture & pH sensor11.96
3BH1750FVI ambient light module sensor4.49
4ESP32 board5.38
5LCD3.29
6Power breaker1.50
7Relay 2 channel1.20
8Terminal wires1.35
9Power adapter1.79
10Plastic box7.47

Total price 47.10

Input membership function thresholds

ParameterLowMediumHigh
Soil moisture (%)0–3530–7570–100
Temperature (°C)20–2524–3230–40
Humidity (%)50–7060–8580–100

Results of testing the operation of the control system

Working styleNumber of tests (times)Accuracy of work orders and controls (times)Accuracy (%)
1. Manual operation mode
1.1 Turn on the water pump with the push button9090100
1.2 Turn off the water pump with the push button9090100
1.3 Turn on the fogger pump with the push button9090100
1.4 Turn off the fogger pump with the push button9090100

2. Automatic operating mode
2.1 If the moisture is higher than specified: Turn off the watering pump9090100
2.2 If the moisture is lower than specified: Turn on the watering pump9090100
2.3 If the temperature is higher than specified: Turn on the fogger pump9090100
2.4 If the temperature is lower than specified: Turn off the fogger pump9090100

Average light intensity comparison between sensors and standard measuring devices

Sensors/deviceNSDMultiple comparisons Sig.FANOVA Sig.
BH1750FVI ambient light5041,448.081,797.700.5970.2940.747
TSL2561 luminosity5041,556.421,875.930.460
Standard device5041,177.251,613.67

Average soil pH comparison between sensors and standard measuring devices

Sensors/deviceNSDMultiple comparisons Sig.FANOVA Sig.
NPK & pH5046.130.0470.0721.8300.168
Moisture & pH5046.140.0560.164
Standard device5046.160.049

Proposed action for greenhouse environmental management

Soil moisture (%)Temperature (°C)Humidity (%)Action
Low (0–35)Low (20–25)Low (50–70)Increase watering, increase temperature, increase humidity
Medium (30–75)Medium (24–32)Medium (60–85)Maintain watering, maintain temperature, maintain humidity
High (70–100)High (30–40)High (80–100)Decrease watering, decrease temperature, decrease humidity

Fuzzy input variables and their membership function characteristics

VariablesRangeMembership functionsShape
Soil moisture (%)0–100Low, medium, highTriangular
Temperature (°C)15–45Low, medium, highTriangular
Humidity (% RH)30–100Low, medium, highTriangular
Light intensity (lx)0–5000Very low, low, medium, highTrapezoidal

Selected low-cost sensors and validation results compared with standard devices

ParameterSelected sensorReference deviceANOVA p-valueValidation result
Temperature (°C)SHT30Digital thermometer (Ref)0.49 > 0.05Validated
Humidity (%)SHT30Hygrometer (Ref)0.88 > 0.05Validated
Soil moisture (%)Moisture & pH sensorStandard soil moisture meter0.77 > 0.05Validated
Soil pHMoisture & pH sensorLaboratory pH meter0.16 > 0.05Validated
Light intensity (lx)BH1750FVILux meter0.59 > 0.05Validated

Comparison of average temperature between the standard device and the sensors

Sensors/deviceNSDMultiple comparisons Sig.FANOVA Sig.
DHT2167228.160.9960.0831.1970.315
DHT2267228.051.0130.173
SHT3067227.851.0130.494
Standard device67227.651.013

Average soil moisture comparison between sensors and standard measuring devices

Sensors/deviceNSDMultiple comparisons Sig.FANOVA Sig.
Soil moisture detection67284.584.530.5790.1260.944
Soil moisture sensor Module v267284.664.450.620
Moisture & pH67284.295.330.770
Standard device67283.875.30

Cost-level comparison between previous studies and the proposed system

StudyHardware architectureSensor typeSystem complexityApprox. cost/evidenceCost level
Ting et al. (2015)Industrial ZigBee (JN5139), WSN nodes, GPRS serverIndustrial sensors (0–5 V, 4–20 mA), LI-6400XT CO2 analyzerMulti-node industrial WSN + cloudLab-grade instruments (CO2 analyzer alone > US$10,000)High
Wang & Wang (2020)CC2530 ZigBee network, GPRS module, host PCDS18B20, DHT11, BH1750Multi-node WSN + fuzzy-PID + PC platformMultiple ZigBee nodes + base station (higher than low-cost MCUs)High–medium
Simo et al. (2022)ATmega328P + ESP8266 + multi-sensor platformSHT31, BH1750, CCS811, pH sensorEnvironmental + electrical monitoring178 € + 147 € ≈ US$340Medium
Kayadibi (2025)ESP32 + multi-sensorsAHT10, CJMCU-811, MQ135, capacitive soil sensorIoT monitoring + basic actuator controlEstimated US$60–90Medium
Naeem & Aly (2024)Raspberry Pi 3 + Arduino + cameraDHT11, soil moisture, pH, CO2Multi-sensor monitoring~70–80US$Medium–low
This study (2025)ESP32 microcontrollerValidated low-cost sensors (SHT30, soil moisture, BH1750)IoT monitoring + fuzzy automationUS$47.10 (actual prototype cost)Low

Proposed FL rules for greenhouse environmental management

Rule No.TemperatureHumiditySoil moistureWateringSpray mist
R1HighLowMediumOFFON
R2HighHighMediumOFFOFF
R3MediumLowMediumOFFON
R4MediumHighMediumOFFOFF
R5LowLowMediumOFFON
R6LowHighMediumOFFOFF
R7--LowONOFF
R8--MediumOFFOFF
R9--HighOFFOFF

Average relative humidity comparison between the standard device and the sensors

Sensors/deviceNSDMultiple comparisons Sig.FANOVA Sig.
DHT2167284.754.420.6830.0670.977
DHT2267284.624.570.748
SHT3067284.375.350.884
Standard device67284.165.27

Output membership function parameters (normalized 0–1)

Output variableMembership levelRangeParameters (a, b, c)
Pump (fogger)Low0.0–0.3(0.0, 0.0, 0.3)
Medium0.2–0.7(0.2, 0.5, 0.7)
High0.6–1.0(0.6, 1.0, 1.0)
Pump (watering)Low0.0–0.4(0.0, 0.0, 0.4)
Medium0.3–0.7(0.3, 0.5, 0.7)
High0.6–1.0(0.6, 1.0, 1.0)
Language: English
Submitted on: Oct 18, 2025
Published on: May 27, 2026
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year

© 2026 Ekkarin Wayo, Somporn Ruang-on, Kritaphat Songsri-in, Fahmida Wazed Tina, Prawit Nuengmatcha, published by Macquarie University, Australia
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.