"Behind precision agriculture is the idea that we should bring only what is strictly necessary."
Two years ago, engineers from the Orange Labs site in Lannion, Côtes-d’Armor, decided to take a look at smart agriculture. A new field in which to experiment with data recovery solutions while helping a sector that sometimes struggles to embrace new technology. Brittany’s chamber of agriculture gave them a set of pig farming data from three experimental stations in its area. It also gave them an expert with whom to discuss the needs of pig farmers and the specificities of zootechnical data. You’ve heard of Big Data – now here’s Pig Data!
Lannion researchers then began working on the “Pig Data Solution” project, in collaboration with their colleagues at Orange Labs Sophia Antipolis who specialize in data analysis and processing. They firstly discovered that pig data cannot be exploited by data processing software. So they decided to develop a mobile app. Its aim? To enable pig farmers to enter data using their smartphones which can now be directly exploited by IT tools.
“And then we wanted to go further,” says Yvan Picaud, research and development engineer at Orange Labs Lannion. “We thought it was important to simplify the actual use of this app with contextualization. In a porcine maternity unit, for example, when a producer puts the phone over the light that illuminates the animal’s compartment, the file is automatically retrieved and the relevant information can be entered.
It’s made possible by Li-Fi, a wireless communication technology that uses light. As Internet connection problems are frequent on farms, Li-Fi particularly interests the Lannion laboratory. “The advantage is that the connectivity is where the light is,” says Yvan Picaud. “With Pig Data, we are continuing to work on the new connectivity technologies which are our core business.”
Data for sustainable agriculture
But what do you do with all the zootechnical data that is collected? How can it be exploited, that is made intelligible and useful, by farmers? In Lannion and Sophia Antipolis, the two teams of researchers have developed visualization tools – tables, dynamic graphics, etc. – in order to “translate” the raw data into legible information for the pig farmers. In addition, statistical algorithms give them information about the conditions that improve their production.
Researchers have been working on data with an impact on the consumption index. This is an essential indicator for pig farmers because it measures the efficiency of the conversion of food into production.
“Today, one of the major problems producers have is that only get to know the livestock performance indicators once they are in the slaughterhouse,” explains Yvan Picaud. The final component of the Pig Data Solution is therefore to enable farmers to track the consumption index as closely as possible and allow them to access the information further upstream than is currently the case, and so quickly identify any fall in productivity – or even anticipate it and be proactive.
The challenge? More controlled and reasonable agriculture. “Data analysis provides a far more global view and, thereby makes it possible to improve processes,” he adds. Yvan Picaud is thinking for example about the use of inputs “since behind precision agriculture is the idea that you bring in only what is strictly necessary”.
Still at the prototype stage, the Pig Data Solution has enabled the engineers at Lannion and Sophia Antipolis to demonstrate in a very practical way how experiments carried out in Orange laboratories can help farmers. A prizewinner at Space 2016, the International Exhibition for Animal Production held annually in Rennes, the solution could be extended to other areas.
