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2026 Vol.8, Issue 1 Preview Page

Research Article

Greenhouse environment monitoring using a smartphone application with hybrid ANN-Kalman prediction
Emmanuel Bicamumakuba1
,
Md Nasim Reza12
,
Hongbin Jin2
,
Md Aminur Rahman1
,
Atulinda Cholet Nyangoma1
,
Hyeunseok Choi3
,
Sun-Ok Chung12*
1Department of Agricultural Machinery Engineering, Graduate School, Chungnam National University, Daejeon 34134, Republic of Korea
2Department of Smart Agricultural Systems, Graduate School, Chungnam National University, Daejeon 34134, Republic of Korea
3Korea Institute of Industrial Technology, Cheonan 31056, Republic of Korea
*Corresponding Author
31 March 2026. pp. 34-55
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Abstract

Environmental monitoring and actuator performance validation are critical for developing greenhouse management strategies. The objective of this study was to develop and validate a smartphone application for monitoring and actuator control, implemented in a greenhouse simulator. The simulator comprised eight distributed sensor nodes measuring air temperature and relative humidity, a gateway, and a real-time visualization interface, with data exchange enabled via message queuing telemetry transport (MQTT). To quantify environmental responses and confirm actuator execution, ON–OFF control experiments were performed using a ventilation fan. Fan activation produced consistent temperature decreases of approximately 1.0-2.0°C and relative humidity changes of 4-8% across the sensor nodes, indicating stable and repeatable responses. Power monitoring further verified reliable actuator behavior: power consumption increased to 20-45 W during operation, while current remained below 1.0 A. For short-term environmental prediction, an artificial neural network (ANN) coupled with a Kalman filtering model was implemented. The hybrid (ANN-Kalman) model achieved strong predictive performance, with temperature RMSE values below 0.02 on the normalized scale and coefficients of determination (R2) exceeding 0.99 for all nodes; humidity prediction errors remained below 0.05 on the normalized scale. The results demonstrated that the proposed platform provided a robust pre-deployment testbed for greenhouse monitoring, actuator validation, and high-accuracy environmental prediction to support future closed-loop control development.

Keywords
Smart greenhouse
Greenhouse environment
Sensor node
Remote monitoring
Actuator control
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Information
  • Publisher :Korean Society of Precision Agriculture
  • Publisher(Ko) :한국정밀농업학회
  • Journal Title :Precision Agriculture Science and Technology
  • Journal Title(Ko) :정밀농업과학기술
  • Volume : 8
  • No :1
  • Pages :34-55
  • Received Date : 2026-02-27
  • Revised Date : 2026-03-17
  • Accepted Date : 2026-03-17
  • DOI :https://doi.org/10.22765/pastj.20260004
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