Author(s)

AnQi Zhang

Affiliation(s)

School of Information Electronic Technology, Jiamusi University, Jiamusi 154007, Heilongjiang, China.

Corresponding Author

AnQi Zhang

ABSTRACT

Traditional temperature regulation methods in rural Large White pig farming in China suffer from low efficiency and insufficient precision, alongside a lack of intelligent solutions adapted to rural environments. To address these issues, this paper presents the design and implementation of a temperature control system integrating Artificial Intelligence (AI) and the Internet of Things (IoT). The system employs the YOLOv8 object detection algorithm as its core, combined with keypoint detection, Region of Interest (ROI) filtering, and abnormal posture detection to achieve contactless and precise collection of the pigs' body dimension parameters. A mapping model correlating "body dimensions - weight - age - optimal temperature" is established using a fuzzy algorithm, and a Kalman filter is introduced for dynamic optimization and regulation of the ambient temperature. The system utilizes an IoT cloud platform for real-time data transmission and intelligent analysis, while solar power is adopted to suit rural energy scenarios. This system effectively fills a technical gap in contactless detection and integrated temperature control within the field of smart rural farming. It offers a low-cost, highly adaptable intelligent solution for small and medium-sized farms, holding significant value for advancing livestock industry modernization and promoting rural development.

KEYWORDS

Large white pig farming; YOLOv8 algorithm; Fuzzy control; Kalman filter

CITE THIS PAPER

AnQi Zhang. A temperature control system for rural free-range pig farming using artificial intelligence and the internet of things. Journal of Computer Science and Electrical Engineering. 2025, 7(7): 60-65. DOI: https://doi.org/10.61784/jcsee3102.

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