Article Details

Abstract

The limitations of traditional livestock farming in terms of precise equipment regulation and energy consumption management have become increasingly prominent. To address this issue, an AI-based intelligent environmental monitoring system for livestock farming has been designed. The system, centered around the STM32F407VET6 processor, incorporates environmental detection sensors such as temperature and humidity sensors, as well as peripherals like fans and water curtains. It uploads environmental parameters to the server via a 4G module and intelligently regulates these parameters in real-time using AI algorithms. This not only creates a favorable growth environment for livestock but also achieves energy conservation, consumption reduction, and equipment fault detection, thereby promoting the upgrading of the livestock farming industry from a “manual experience management” to a “data-driven regulation” model.

Keywords

livestock breeding; AI technology; 4G; fault detection; energy saving and consumption reduction; intelligent parameter adjustment

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About the authors

Lan Wei (April 2004-), male, She ethnic group, from Fuzhou, Jiangxi Province, is currently pursuing a bachelor's degree with a research focus on embedded system development; Xin Wei (August 1997-), male, Han ethnicity, from Ganzhou, Jiangxi Province, teaching assistant, master's student, research direction: Internet of Things technology, signal processing; Zhang Shiwei (January 2003-), male, Han ethnicity, from Zhengzhou, Henan Province, is currently pursuing a bachelor's degree with a research focus on embedded system development; Wang Bin (January 2003-), male, Han ethnicity, born in Jiujiang, Jiangxi Province, is currently pursuing a bachelor's degree with a research focus on embedded system development; Yan Huihui (October 2001-), born in Ganzhou, Jiangxi Province, Han ethnicity, is currently pursuing a bachelor's degree in embedded system development.