UTIA and Enterprise Sensor Systems work together to identify diseases in infectious cattle using AI and hyperspectral imaging.
The funding was awarded through the AI TechX Seed Fund and collaborates on the project “Rapid Identification of Infectious Disease Cattle Using AI and Hyperspectral Imaging.”
AI TechX is an initiative of AI Tennessee, aimed at accelerating the development and real-world application of artificial intelligence through collaboration in the academic industry.
The AI TechX Seed Fund supports our efforts to build impactful, interdisciplinary research teams that tackle industry challenges through innovative technology solutions.
Why should cow disease be detected so quickly?
Cattle disease poses a significant risk to both animal health and human livelihoods. Outbreaks can spread rapidly within herds and can cause serious economic losses to farmers due to reduced productivity, increased veterinary costs, and sometimes large culculture of affected animals.
In developing regions, cattle disease can undermine food security as many communities rely on livestock for milk, meat and labor. Even a few animals can destroy the family’s income if lost.
Unidentified cow disease can also disrupt trade. Countries with known outbreaks may face bans or restrictions on livestock exports. Preventing and controlling cattle disease requires coordinated veterinary services, strict biosecurity measures, and public awareness.
These factors make it essential that advanced technologies such as AI and hyperspectral imaging can be used to quickly detect diseases in infectious cattle, enabling rapid treatment and reducing the chances of spreading across the population.
Rapid, non-invasive screening to detect infectious cattle disease
This funding allows enterprise sensor systems to expand ESS Protected Technology, originally developed to detect virus signatures in human respiration, to detect virus signatures in animals.
Ess Protect – Animal provides rapid, non-invasive, contactless screening for infectious cattle diseases such as Hivine respiratory disease using hyperspectral imaging and advanced machine learning.
The award also marks Ensis’ entry into the AI TechX Consortium, expanding access to research and collaboration opportunities.
“This project strengthens our commitment to providing groundbreaking biosensing tools to protect animal health and food safety,” said John Castellaw, CEO of Ensensys.
“It also highlights the importance of university industry collaboration in transforming AI research into scalable and deployable solutions.”
Training AI models to detect changes in animal health
Drawing on hyperspectral data from the 2024 field survey at the UTIA Middle Middle Tennessee Agresearch and Education Center in Spring Hill, Tennessee, as well as other collaborations with UT and private industries, researchers will train AI models that can detect disease-specific spectral signatures from Ubain Bless.
Benefits of this technology include preliminary design of field-deployable hyperspectral sensing units, machine learning models for assessing cattle health, and strategies for expanding the technology to other livestock and agricultural environments.
The long-term partnership also aims to support the establishment of the Agriai Center of Excellence at UTIA, an innovation hub that integrates AI and data-driven tools into modern agricultural practices.
The center features predictive analytics, automation and precision technology for producers to improve productivity, sustainability and economic resilience across Tennessee agriculture.
Source link
