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2025 Vol.7, Issue 2 Preview Page

Review Article

Remote monitoring and components abnormality detection in smart vertical farming systems: A review
Gusti Ayu Putri Mei Ulianti1
,
Md Nasim Reza12
,
Hongbin Jin2
,
Bicamumakuba Emmanuel2
,
Kyu-Ho Lee12
,
Sun-Ok Chung12*
1Department of Agricultural Machinery Engineering, Graduate School, Chungnam National University, Daejeon 34134, Korea
2Department of Smart Agricultural Systems, Graduate School, Chungnam National University, Daejeon 34134, Korea
*Corresponding Author
30 June 2025. pp. 150-169
PDF XML Citation
Abstract

The challenges of global food security have been increased by rapid urbanization, climate change, and the decrease of land for agriculture, particularly in urban areas with high populations. Smart vertical farming systems have emerged as a promising solution to address food security challenges associated with rapid urbanization, climate change, and land scarcity. These systems support controlled environment agriculture (CEA) technologies and automation to maximize crop yield in limited urban spaces. However, the complexity of their operation requires efficient remote monitoring and rapid detection of component abnormalities to ensure reliability, reduce operational downtime, and optimize resource use. This review survey the current status in remote sensing, data acquisition, and monitoring solution using internet of thing (IoT) deployed in smart vertical farms. Advanced technologies allow for precise control over the microclimate within vertical farms. Moreover, sensor data are processed to ensure accuracy and then analyzed using machine learning techniques for both data classification and anomaly detection. The integration of IoT and machine learning is further facilitating predictive maintenance and early detection of abnormalities, including equipment failures or pest infestations. The used of remote monitoring to control farm conditions via mobile apps, can enhances growing conditions and increase productivity and crop quality. Despite the effectiveness of the smart farm technology in monitoring environmental conditions, it does not explicitly address potential challenges such as the initial setup costs, power consumption, and maintenance of the IoT systems. Nonetheless, the applications of remote monitoring and abnormal detection in smart vertical farming systems offering enhanced productivity and sustainability of future farming operations. Further studies can be conducted to enhance the methods and deal with these limitations.

Keywords
Precision agriculture
Remote monitoring
Signal processing
Machine learning
Vertical farm
Smart agriculture
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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 : 7
  • No :2
  • Pages :150-169
  • Received Date : 2025-06-20
  • Revised Date : 2025-06-27
  • Accepted Date : 2025-06-28
  • DOI :https://doi.org/10.22765/pastj.20250012
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