Early Intervention Tool
Detect Early Signs of Disease Faster.
Act Immediately.
Give Your Farm a Critical Head Start!
Detect Issues Up to 4 Weeks Before Clinical Signs Appear.
Cloudfarms’ Early Intervention Tool gives pork producers in Asia and beyond the ability to act before it’s too late. The ability to foresee the outbreak of PRRS and act accordingly. Developed in partnership with Iowa State University in the US, this tool tracks abnormalities in farm performance data to identify disease risks – before the traditional methods will make you aware.
Cloudfarms’ customers can register various activities on the farm seamlessly with our app. The data can then be analysed to discover hidden patterns that indicate the changing health status of the herd. PRRS outbreaks can have a massive negative impact on the farm. But there are models that use a few indicators that can point to the upcoming problems.
How It Works?
Tracked Indicators:
- Abortion Rates
- Pre-weaning Mortality
- Prenatal Losses
- Sow Mortality
Our predictive tool continuously monitors key reproductive and health indicators to ensure proactive farm management. It sets a baseline for each farm and flags deviations that could signal an early-stage outbreak.
- Uses 15-week rolling averages
- Alarms are triggered when weekly data exceeds 2 standard deviations from the average
- 2+ alarms in 1 week signals a high risk of PRRS
Built to Spot Problems Before They Cost You.
Early disease outbreak detection is a long-awaited feature of pig production management systems. While there are tools out there to predict future production levels, predicting disease outbreaks at your farm is tricky.
Forecasting models can help you plan ahead and suggest numbers of gilts to buy, pigs to sell to slaughter, etc. But disease outbreaks come unexpectedly and seem difficult to prepare for.
Contact us to get a free demo
Stay one step ahead of PRRS and emerging threats with our early intervention tool – detect issues before symptoms even appear.
Give us a call or text us for more information.
