A RFID-Based Monitoring System for Characterization of Perching Behaviors of Individual Poultry

Wang, Kailao; Liu, Kai; Xin, Hongwei; Chai, Lilong; Wang, Yu; Tao, Fei; Oliveira, Jofran Luiz de; Pan, Jinming

doi:10.13031/iles.18-024

Cited by 3 publications

(2 citation statements)

References 11 publications

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“…Sensor-based data collection has proven effective at recording accurate information regarding animal social behaviour for both the targeted groups and individuals in the group. Sensor-based data collection efficiency is based on the capturing contact frequency and type of the sensor technology used [22]. Recording rate (example: fast moving chickens vs. slow moving cows) and context of animal intercommunications (example: licking vs. tail biting) is a crucial impetus behind refining livestock management processes and maximizing resource distribution and production [5].…”

Section: Sensor-based Data Analysis In Animal Behavioural Studiesmentioning

confidence: 99%

Social Network Analysis in Farm Animals: Sensor-Based Approaches

Neethirajan

Kemp

2021

Animals

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Natural social systems within animal groups are an essential aspect of agricultural optimization and livestock management strategy. Assessing elements of animal behaviour under domesticated conditions in comparison to natural behaviours found in wild settings has the potential to address issues of animal welfare effectively, such as focusing on reproduction and production success. This review discusses and evaluates to what extent social network analysis (SNA) can be incorporated with sensor-based data collection methods, and what impact the results may have concerning welfare assessment and future farm management processes. The effectiveness and critical features of automated sensor-based technologies deployed in farms include tools for measuring animal social group interactions and the monitoring and recording of farm animal behaviour using SNA. Comparative analyses between the quality of sensor-collected data and traditional observational methods provide an enhanced understanding of the behavioural dynamics of farm animals. The effectiveness of sensor-based approaches in data collection for farm animal behaviour measurement offers unique opportunities for social network research. Sensor-enabled data in livestock SNA addresses the biological aspects of animal behaviour via remote real-time data collection, and the results both directly and indirectly influence welfare assessments, and farm management processes. Finally, we conclude with potential implications of SNA on modern animal farming for improvement of animal welfare.

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Section: Sensor-based Data Analysis In Animal Behavioural Studiesmentioning

confidence: 99%

Social Network Analysis in Farm Animals: Sensor-Based Approaches

Neethirajan

Kemp

2021

Animals

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“…With these types of systems, it will increasingly become possible to identify specific behaviors of animals and make assessments in terms of how hens respond to specific events. For instance, using RFID in combination with load cells on perches, it is possible to describe frequency, duration, and circadian patterns of perch use by individual laying hens [95], though, with such a system it is not currently possible to determine whether these hens are sitting, standing, resting, or sleeping soundly while on the perches. In other cases, RFID antenna at key resources such as food and water can assess proximity of birds to these resources [96]; however, without additional measurements, it is not possible to determine if the birds, and which birds, are actually using the resources they are near and how much food or water they might be ingesting.…”

Section: Use Of Sensor Technologies In Different Applicationsmentioning

confidence: 99%

Review of Sensor Technologies in Animal Breeding: Phenotyping Behaviors of Laying Hens to Select Against Feather Pecking

Ellen

Sluis

Siegford

et al. 2019

Animals

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Damaging behaviors, like feather pecking (FP), have large economic and welfare consequences in the commercial laying hen industry. Selective breeding can be used to obtain animals that are less likely to perform damaging behavior on their pen-mates. However, with the growing tendency to keep birds in large groups, identifying specific birds that are performing or receiving FP is difficult. With current developments in sensor technologies, it may now be possible to identify laying hens in large groups that show less FP behavior and select them for breeding. We propose using a combination of sensor technology and genomic methods to identify feather peckers and victims in groups. In this review, we will describe the use of “-omics” approaches to understand FP and give an overview of sensor technologies that can be used for animal monitoring, such as ultra-wideband, radio frequency identification, and computer vision. We will then discuss the identification of indicator traits from both sensor technologies and genomics approaches that can be used to select animals for breeding against damaging behavior.

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A Review of Passive Radio Frequency Identification Systems for Animal Monitoring in Livestock Facilities

Brown–Brandl¹,

Adrion²,

Maselyne³

et al. 2019

Applied Engineering in Agriculture

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Abstract. Animal facilities are increasing in size, while the availability of skilled workers is decreasing, thus, making it difficult for the farm laborers to ensure the health and well-being of all animals under their care. Passive Radio Frequency Identification (RFID) systems have been successfully used in animal facilities and research has identified potential applications in behavior monitoring for automated illness detection. While RFID signals range in frequency from 9 kHz to 5.8 GHz, the three most common frequencies are Low Frequency (LF, 125 kHz or 134.2 kHz), High Frequency (HF, 13.56 MHz), and Ultra-High Frequency (UHF, 865-868 MHz or 902-928 MHz). The objective of this article is to compare and evaluate the application of these three different RFID systems within large research facilities for livestock and poultry in terms of hardware characteristics, system design, and data processing and usage. Differences in tag construction, availability and cost are evident, but also basic differences in reader and antenna function, such as physics of communication, speed of detection, and anti-collision procedures exist. The systems have significant differences in reading ranges and are known to have varying influence of materials, especially water and metal, on the performance of the systems. However, the data streams, as well as methods of data processing and the creation of events (e.g., visits to a feeder), are similar for all systems. The characteristics mentioned do not necessarily identify an ideal RFID technology but reveal positive and negative aspects of each system. The three different RFID systems have been successfully applied in livestock and poultry facilities. Current research is focused on the utilization of the RFID data in prediction and decision models for illness, animal welfare, and management actions. Keywords: Behavior, Cattle, Frequency ranges, Health and welfare, Poultry, Swine, Transponder.

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A RFID-Based Monitoring System for Characterization of Perching Behaviors of Individual Poultry

Cited by 3 publications

References 11 publications

Social Network Analysis in Farm Animals: Sensor-Based Approaches

Social Network Analysis in Farm Animals: Sensor-Based Approaches

Review of Sensor Technologies in Animal Breeding: Phenotyping Behaviors of Laying Hens to Select Against Feather Pecking

A Review of Passive Radio Frequency Identification Systems for Animal Monitoring in Livestock Facilities

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