To address the pain point of preventing airborne diseases in poultry processing, the University of Michigan, in collaboration with Taza Aya, has developed a wearable air curtain device that revolutionizes proactive protection using non-thermal plasma technology. This device integrates an air purification system and an air curtain generation system into a portable backpack weighing less than 10 pounds (approximately 4.5 kg). The battery provides up to 4 hours of runtime and supports hot-swap replacement, ensuring continuous operation needs are met.
Compared to traditional face masks, this integrated helmet-mask device requires no facial contact—it avoids discomfort and breathing resistance while keeping employees’ faces clearly visible to facilitate smooth communication. Its core principle is to treat air with non-thermal plasma, forming a directed curtain of clean air that effectively blocks harmful microorganisms such as viruses and bacteria, providing round-the-clock protection for processing workers.
Currently, manual and automated deboning lines for white meat process is up to 70 birds per minute, while automated dark meat lines exceed 90 birds per minute. However, real-time process monitoring technology has long been lacking. A visual monitoring system designed under the leadership of Dr. Wa-yne Daley, CEO of WDDLY Associates, fills this industry gap.
The system combines 2D imaging, 3D depth data technology, traditional detection methods, and machine learning algorithms to accurately assess the amount of meat remaining on products such as chicken legs and breasts after deboning. It supports flexible sensor expansion to adapt to different production scenarios. By continuously monitoring production performance and providing high-resolution real-time feedback, this technology effectively improves protein yield, reduces material waste, and drives the automation and refinement of the deboning process.
The "Sustainable Poultry Industry 4.0 (SPI 4.0)" framework, proposed by Dr. Amit Morey, Associate Professor in the Department of Poultry Science at Auburn University, integrates artificial intelligence (AI), machine learning, the Internet of Things (IoT), robotics, and cloud platforms to address long-standing industry pain points such as inefficient supply chains and data silos.
Centered on a range of cutting-edge sensing technologies, the framework includes microwave-based meat quality assessment, multi-modal sorting systems, hyperspectral imaging for biofilm detection, and Raman spectroscopy for rapid pathogen detection across the entire farm-to-table supply chain. Through real-time AI analysis and interactive data dashboards, these technologies achieve deep synergy, empowering processing enterprises to make timely, informed decisions in quality control, safety traceability, and production scheduling—driving the comprehensive transformation of the poultry industry toward intelligence and sustainability.
(Note: This article is compiled and published based on content from the feature report in International Poultry Sep/Oct 2025 Issue (No. 125), and the copyright belongs to the original author.)
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