Precision Livestock Farming Applications (PLF) for Grazing Animals

Abstract

Over the past four decades the dietary needs of the global population have been elevated, with increased consumption of animal products predominately due to the advancing economies of South America and Asia. As a result, livestock production systems have expanded in size, with considerable changes to the animals’ management. As grazing animals are commonly grown in herds, economic and labour constraints limit the ability of the producer to individually assess every animal. Precision Livestock Farming refers to the real-time continuous monitoring and control systems using sensors and computer algorithms for early problem detection, while simultaneously increasing producer awareness concerning individual animal needs. These technologies include automatic weighing systems, Radio Frequency Identification (RFID) sensors for individual animal detection and behaviour monitoring, body temperature monitoring, geographic information systems (GIS) for pasture evaluation and optimization, unmanned aerial vehicles (UAVs) for herd management, and virtual fencing for herd and grazing management. Although some commercial products are available, mainly for cattle, the adoption of these systems is limited due to economic and cultural constraints and poor technological infrastructure. This review presents and discusses PLF applications and systems for grazing animals and proposes future research and strategies to improve PLF adoption and utilization in today’s extensive livestock systems.

Animal hair based triboelectric generators and sensors

“…In this paper, a new triboelectric harvester architecture is proposed, based on the paired electrode architecture, and inherent positive charge affinity of animal hair/skin. This harvester architecture is investigated with the intention of developing new kinetic energy harvesters for animal wearables like collars or leg straps [4] usually employed in the precision livestock farming agricultural concept [5]. Four different types of the harvesters are built based on this architecture and tested on a novel experimental test bed with three different animal hair types.…”

Artificial Intelligence and Sensor Technologies in Dairy Livestock Export: Charting a Digital Transformation

“…Systems typically employing RFID tags or smart collars can automate this process, offering real-time data [ 20 ]. These systems track proximity to feeding troughs, feeding frequency [ 21 ], and duration. Analyzing these data can alert farmers of anomalies, enabling early health issue detection [ 22 , 23 ], and aid in optimizing feed management, thereby enhancing productivity and sustainability.…”

Mid-Infrared Sheep Segmentation in Highland Pastures Using Multi-Level Region Fusion OTSU Algorithm

“…However, due to the complex terrain and harsh climate in highland areas, coupled with the stray herders and inconvenient transportation, the traditional artificial supervision can no longer meet the demand for monitoring livestock. Precision livestock technology has shown great potential in addressing this issue, enabling the transformation of livestock management from artificial to automatic or semi-automatic regulation, which can significantly reduce labor costs and improve environmental and economic sustainability [1]. Existing technologies use a combination of low-cost time-delay cameras together with a machine learning method to monitor the position information of sheep with high accuracy and sensitivity; however, it requires that there is no background confused with the color of animals in the camera's field of view, and the camera also cannot face to the sun [2].…”