Computer Vision Applied to Detect Lethargy through Animal Motion Monitoring: A Trial on African Swine Fever in Wild...

Area of Science:

• Veterinary epidemiology
• Artificial Intelligence in Animal Health
• Disease Surveillance Technologies

Background:

• Early detection of infectious diseases is crucial for effective disease surveillance and outbreak prevention.
• Advancements in deep learning and computer vision offer new tools for epidemiological research and disease control.
• African Swine Fever (ASF) poses a significant threat to the global pig industry, necessitating improved detection methods.

Purpose of the Study:

• To develop and evaluate an artificial vision-based algorithm for real-time tracking and computation of animal motion.
• To assess the correlation between animal motion patterns and the progression of African Swine Fever (ASF) infection in Eurasian wild boar.
• To explore the potential of motion monitoring systems for early detection of infectious diseases in livestock.

Main Methods:

• Development of a deep learning and computer vision algorithm for real-time animal motion analysis.
• Experimental trials involving Eurasian wild boar experimentally infected with African Swine Fever (ASF).
• Quantitative analysis of animal movement data to correlate with infection status and fever development.

Main Results:

• A significant negative correlation was observed between reduced animal motion and the presence of fever caused by ASF infection.
• Infected wild boar exhibited significantly lower movement levels compared to uninfected control animals.
• The algorithm successfully tracked and computed animal motion in real time during experimental trials.

Conclusions:

• Motion monitoring systems utilizing artificial vision can serve as an effective tool for detecting early clinical signs of fever in livestock, particularly in indoor settings.
• This technology provides a promising non-intrusive, economical, and real-time solution for disease surveillance in the livestock industry.
• The system holds particular promise for the early detection of African Swine Fever (ASF), addressing a critical concern in the global swine industry.