Design and implementation of an IoT-based system for intelligent crop health monitoring
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Дата
2025
Назва журналу
Номер ISSN
Назва тому
Видавець
SPIE
Анотація
This paper presents the development of an intelligent IoT device for automated, real-time monitoring of crop conditions
in agriculture. The proposed solution involves Raspberry Pi Zero 2 W hardware, multi-sensor modules for environmental
data collection, NB-IoT for long-range wireless communication, and the YOLOv8 convolutional neural network for plant
image analysis. The objective is to create a compact, low-cost, and energy-efficient solution that enables early detection
of plant diseases and environmental stress in remote or infrastructure-poor agricultural areas. The developed system
enables accurate identification of disease symptoms and damage on crop leaves based on visual and environmental input,
facilitating timely intervention and reducing yield loss. The YOLOv8 model was adapted for resource-constrained edge
deployment, trained on a custom dataset of strawberry leaf diseases, and integrated into the embedded device with high
accuracy and low latency. System testing confirmed reliable performance under field conditions, with successful image
classification and robust NB-IoT communication. The proposed solution is scalable and applicable to various crops and
contributes to the practical implementation of precision agriculture and intelligent farming systems.
Опис
Ключові слова
Internet of Things (IoT), precision agriculture, deep learning, neural networks, YOLOv8, plant disease detection, edge computing, environmental monitoring
Бібліографічний опис
Lavrik, V., Alieksieieva, H., Kovalska, O., Lebedenko, Y., Sukalo, M., Kudinov, M., & Mezhuyev, V. (2025). Design and implementation of an IoT-based system for intelligent crop health monitoring. In Second International Conference on Communication, Information, and Digital Technologies (CIDT 2025) (Telok Blangah, Singapore), edited by Sos S. Agaian, Xiangjie Kong, Proc. of SPIE, Vol. 14064, pp. 402–411.