Belfast University: A Case Study on Chickens
Download Case Study PDF- Implemented By:
- Locatify
- Implemented In:
- 2022-2023
- Customer Website:
- qub.ac.uk/
- Use Cases:
Livestock Monitoring
Welfare Optimization
Locatify partnered with Queen’s University Belfast to revolutionize animal welfare monitoring using Ultra-Wideband (UWB) technology. The innovative solution equipped broiler chickens with lightweight backpacks containing UWB tags, while 12 anchors installed across a 500-square-meter facility provided precise location tracking.
This groundbreaking system enabled researchers to capture individual chicken movement patterns in commercial housing environments for the first time. The project successfully automated data collection, minimized human intervention, and delivered valuable behavioral insights without disrupting natural animal behavior.
The technology demonstrated significant potential for enhancing poultry welfare by providing unprecedented visibility into individual movement patterns, offering a scalable solution for livestock monitoring with applications across animal welfare research and commercial farming operations.
Background
The Poultry Welfare Research Project aimed to enhance animal welfare and behavioral monitoring in commercial poultry farming. The customer, a leading research institution focused on livestock welfare, sought innovative ways to collect precise, real-time data on the movement and behavior of chickens. Traditional methods of monitoring were inefficient, time-consuming, and often intrusive. To address this, they partnered with Locatify to deploy an advanced
Ultra-Wideband (UWB) tracking system from Sewio and develop a solution to read the data from the research.
Mary Baxter and Niamh O’Connel were the researchers for the broiler movement project at the Queen’s University Belfast in Ireland.
Goals
The primary objective was to develop a high-precision monitoring system capable of tracking individual chickens in real time. The project aimed to:
● Improve poultry welfare by understanding movement patterns.
● Detect and prevent potential health issues based on behavioral insights.
● Automate data collection for more efficient research and analysis.
● Reduce human intervention, minimizing stress on the animals.
Challenges
Implementing UWB technology in a poultry farm presented several challenges:
● Ensuring accurate tracking in a dynamic and densely populated environment.
● Developing a solution that was non-intrusive and did not disrupt animal behavior.
● Maintaining seamless connectivity and data collection in an indoor farm setting.
● Overcoming potential interference from farm equipment and structures.
● Managing the vast amount of data gathered from tracking numerous chickens in real time.
Solution
Locatify provided a UWB-based real-time tracking system from Sewo for livestock monitoring and developed a program to read the movement data. Researchers designed a “backpack” for the chickens with tags.
The solution involved:
● Installation of UWB anchors throughout the research facility to provide precise location data.
● Equipping chickens with lightweight, non-intrusive UWB tags (Piccolino) to track movement patterns.
● Integrating the tracking system, allowing researchers to analyze real-time and historical movement data.
● Developing a data management solution to process the enormous amount of location data collected.
● Melding and accumulating data from the farm’s database and transferring it to a central computer at the university.
● Utilizing SAGE Analytics tools to analyze the refined data, ensuring a manageable dataset for behavioral scientists to study.
● Treating and aggregating the database to reduce the dataset size, making it more efficient for analysis.
The entire deployment of the project was completed within two years but each cycle of experiment took 38 days.
Results
The UWB tracking system provided significant improvements in poultry welfare monitoring:
● Increased accuracy in detecting movement patterns, enabling more precise welfare assessments.
● Automated data collection reduced manual labor and human error.
● Improved efficiency in poultry behavior research, with faster data analysis.
Key criteria for choosing Sewio
● High precision tracking for real-time behavior monitoring
● Seamless integration with existing research methodologies
● Non-intrusive technology suitable for animal welfare studies
● Automated data collection for improved efficiency
● Scalability to accommodate future research expansions