Since the launch of PigWatch system in 2009, Ro-Main has combined artificial intelligence and pig farming.

October 31, 2018

1 Min Read
Ro-Main rolls out new suite of pig behavior software
Ro-Main

Source: Ro-Main
Ro-Main is launching a new range of products incorporating artificial intelligence to help producers analyze their herds in a non-invasive way. The 20-year-old company based in Quebec City, Canada, is releasing the Ro-Main smaRt suite, which includes three software modules for pigs and two for sows.

By means of a network of cameras adapted for pig farms, deep learning algorithms analyze the video streams and translate them into individual behavioral metrics. The analysis of these metrics provides a better understanding of each animal’s specific needs, automates certain tasks and ensures better decision-making.

Since the launch of PigWatch system in 2009, Ro-Main has combined artificial intelligence and pig farming.

“The combination of technology and animal science deserves to be exploited to better manage our farms. We believe that the Ro-Main smaRt suite will simplify the life of producers by allowing them to continuously, in a non-invasive way, analyze the behavior of their herd,” says Jacquelin Labrecque, director of research and development and artificial intelligence product manager.

The Ro-Main smaRt suite for pigs includes the smaRt Pig Counting module that automatically counts pigs in a corridor, eliminating the need to manually count animals for receptions and shipments. The smaRt Pig Inventory module takes real-time inventory by pen, while the smaRt Pig Tracking module tracks and analyzes each animal’s behavior 24 hours a day, seven days a week. 

The Ro-Main smaRt suite for sows includes the smaRt Sow Breeding module that determines the optimal moment to inseminate; thus resulting in an accurate single-dose insemination. Finally, the smaRt Sow Health module uses the behavior of sows to detect health problems early.

Ro-Main smaRt suite sales start February 2019. Pre-orders start on Dec. 10.

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