DEVELOPMENT OF AN EMBEDDED SYSTEM FOR MONITORING ELECTROPHYSIOLOGICAL SIGNALS FROM TOMATO PLANTS IN SMART AGRICULTURE | Khoa | TNU Journal of Science and Technology

DEVELOPMENT OF AN EMBEDDED SYSTEM FOR MONITORING ELECTROPHYSIOLOGICAL SIGNALS FROM TOMATO PLANTS IN SMART AGRICULTURE

About this article

Received: 05/02/25                Revised: 13/04/25                Published: 15/04/25

Authors

1. Pham Van Khoa Email to author, Ho Chi Minh City University of Technology and Education, Vietnam
2. Dinh Tien Dung, Ho Chi Minh City University of Technology and Education, Vietnam
3. Nguyen Ngo Lam, Trường Đại học Sư phạm Kỹ thuật Thành phố Hồ Chí Minh, Việt Nam
4. Chi Chia Sun, National Taipei University, Taiwan

Abstract


This study was conducted to address the increasing issue of environmental pollution, which negatively impacts agricultural crops, particularly tomatoes - a high-value crop widely cultivated in Vietnam. The objective of this research is to develop an intelligent embedded system that utilizes a microcontroller integrated with electronic circuits and electrodes to monitor the physiological responses of tomato plants to environmental factors such as light, temperature, and humidity. This system incorporates amplifiers and advanced signal processing algorithms, enabling the accurate, stable, and reliable collection and analysis of data. The research findings demonstrate that the system can accurately detect and analyze the electrophysiological signals of tomato plants, assisting in the assessment of their responses to varying environmental conditions. With its flexible design, cost-effectiveness, and scalability, the system can be applied to a wide range of crops, contributing to improved agricultural productivity. This study presents significant potential in smart agriculture, supporting early detection of adverse environmental impacts, optimizing cultivation, and promoting sustainable resource management in the context of climate change.

Keywords


Terms— IoT; Phytosensing; Tomato plant electrophysiology; Sensors; Embedded system

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References


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DOI: https://doi.org/10.34238/tnu-jst.11967

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