The agriculture and livestock sector has new data-driven and artificial intelligence-based digital solutions developed as part of the high-impact projects run by the Centre of Innovation for Data tech and Artificial Intelligence (CIDAI) to optimise management in the industry by harnessing tools to spot patterns in the use of antibiotics on livestock farms and analyse the lifecycle of pigs to enhance animal welfare.
This is the case of the ‘AI Applications in the Agricultural Sector’ project which has been undertaken with funding from the Government of Catalonia through Catalonia’s Artificial Intelligence Strategy, Catalonia.AI, and the CIDAI’s high impact projects strand.
Eurecat’s Lleida-based Applied AI Unit, the Computer Vision Center (CVC), the data science and AI research centre at the Polytechnic University of Catalonia (IDEAI-UPC), the Barcelona Supercomputing Center (BSC) and the technical team in the Government of Catalonia’s Ministry of Climate Action, Food and Rural Agenda have all played a part in its implementation. It has also been supported by the University of Lleida (UdL), the Centre for Pig Studies (CEP) and input from industry experts.
The new solutions rolled out in the project were presented at an event held at the Agrobiotech Park in Lleida which was opened by Lluís Juncà, Director General of Innovation, Digital Economy and Entrepreneurship in the Government of Catalonia, Glòria Cugat, Deputy Director General of Agri-Food Transfer and Innovation, and Joan Mas, Director of CIDAI and head of Eurecat’s Digital Area.
“With these high-impact projects and across CIDAI as a whole, we are fostering the uptake of artificial intelligence in Catalan businesses and public authorities,” said Lluís Juncà in his speech. “However, most of all we are laying the groundwork to enable new ideas, new possibilities, new projects and new proofs-of-concept to emerge which are the basis for continuing our efforts to address the problems and challenges we face as a country.”
“The Ministry of Climate Action, Food and Rural Agenda has backed this project because it helps to unlock and fast-track uptake of artificial intelligence in the agri-food and forestry sector,” added Glòria Cugat. “It is one of the challenges which, alongside sustainability, healthy eating, Industry 4.0 and generational handover, make up our Pla Innova 2030 innovation strategy for this sector which has been drawn up and is led by the Ministry.”
“We had to present the results of this technological project for the agricultural sector in Lleida because many of its implementers operate here,” pointed out Joan Mas. “So we need to ensure that the impact of the technological developments achieved gets to the local primary sector and can then be built on.”
AI applications in the agricultural sector
CIDAI’s high-impact project taps artificial intelligence for the agricultural sector in two use cases tackling specific challenges shared by government, businesses and farms operating in the industry.
Firstly, tools have been devised to support decision-making in the application of antibiotics in livestock farms to meet the need for greater knowledge in this area posed by the Catalan Government’s Animal Feed and Livestock Production Safety Service. The new solutions make it possible to spot patterns which will help to optimise the application of antibiotics in order to minimise their use.
The second use case was identified after a number of meetings with industry stakeholders in Lleida, in partnership with the Centre for Pig Studies and the University of Lleida and with the input of the Catalan Federation of Agricultural Cooperatives, to develop artificial intelligence and computer vision algorithms for monitoring the lifecycle of pigs to enhance animal welfare and thus ramp up farm efficiency and profitability.
Anchored in these data gleaned from individualised monitoring, digital solutions can be leveraged to yield behavioural indicators to optimise animal welfare on pig farms and make the fattening process more efficient through precise and individualised tracking of each animal.
