Turkish Journal of Agriculture and Forestry




The Internet of Things (IoT) is a development trend in modern industry and life. It can not only reduce the cost of industry and agriculture, but also improve the quality of products and the quality of people’s lives. Therefore, IoT breeding is the embodiment of modern intelligent agriculture. For example, in the estrus detection of beef cattle, the quality of video images when tracking beef cattle is reduced due to changes in external climate conditions and the difference between daytime and nighttime illumination. This paper introduces a visual target tracking algorithm based on saliency, so that it has better applicability and robustness. The algorithm realizes the image enhancement of beef cattle in different periods of time and under different weather conditions. It provides high-quality samples for the automatic recognition of beef cattle estrus and realizes the all-day contactless real-time monitoring of beef cattle estrus. Wireless communication, embedded technology, video monitoring, a database, and other technologies are used to combine the fan, water curtain, side window, feeder, camera, various sensors, and other equipment to form a breeding tracking system based on the IoT. The front-end device sent the command to the lower computer through the control key. After receiving the command, the terminal connected to the designated feeding facility and controlled the feeding device cutoff through the relay startup and relay cutoff process. The administrator used a PC or mobile phone for remote control. During estrus, the body temperature of cattle increased significantly, by about 0.26 °C. The scheme in the article can reflect the environment and estrus in the cowshed in real time and provide more intuitive data for the manager.


Agricultural Internet of Things, aquaculture tracking, saliency visual target tracking algorithm, image enhancement

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