THE DAIRY CATTLE SECTOR IS FACING DIFFICULTIES DUE TO THE REDUCTION IN MILK PRICES, THE INCREASE IN THE COST OF FEEDING AND THE UPCOMING ABOLITION OF THE QUOTA SYSTEM IN THE EU (ABRIL-2015). THE NEED TO IMPROVE THE COMPETITIVENESS OF THE DAIRY ENTERPRISE REQUIRES DECISIONS THAT ARE OFTEN DIFFICULT TO EVALUATE BECAUSE THEY ARE HIGHLY DEPENDENT ON MANY ECONOMICAL AND TECHNICAL FACTORS AND THEIR INTERACTIONS. THE OBJETIVE OF THIS PROJECT IS TO INTEGRATE ANIMAL KNOWLEDGE, ON-FARM AVAILABLE DATA FROM MILKING MACHINES, MANAGEMENT SOFTWARE AND SENSORS TOGETHER WITH ARTIFICIAL INTELLIGENCE TECHNIQUES TO DEVELOPO AN APLICATION TO PRODUCE ADDITIONAL KNOWLEDGE AND RECOMENDS ACTIONS AT FARM LEVEL. THE PROJECT IS STRUCUTRED IN FOUR MAIN TASKS: 1) DATA COLLECTION FROM THE DIFFERENT PLATFORMS AND ITS CONSOLIDATION IN A UNIQUE DATABASE. IN THIS TASK WE WILL PRODUCE A SOFTWARE THAT WILL ALLOW THIS PROCES TO BE PERFORMED AUTOMATICALLY TO FACILITATE ITS USE AT FARM LEVEL; 2) THE APPLICACION OF ARTIFICIAL INTELIGENCE TECHNIQUES TO DEVELOP A KNOWLEEDGE-BASED SYSTEM THAT NOT ONLY INTERPRETES FARM DATA BUT ALSO LEARNS IN THE PROCESS, ALLOWING THE ADAPTATION OF THE SYSTEM TO THE SPECIFIC CONDITIONS OF EACH INDIVIDUAL FARM. WE PROPOSE TO USE DIFFERENT METHODOLOGIES AS NEURAL NETWORS, MACHINE LEARNING, DATA MINING Y KNOWLEDGE DISCOVERY. THE SYSTEM WILL PROVIDE RECOMMENDATIONS FOR ACTIONS THAT WILL BE EVALUATED BASED ON UNCERTANTY, RISK AND ECONOMIC RETURN; 3) THE VALIDATION OF THE SYSTEM IN FIELD CONDITIONS THORUGH THE IMPLEMENTATION OF THE KNOWLEDGE SYSTEM IN THREE FARMS WITH DIFFERENT CONDITIONS, AND CAREFUL ATTENTION WILL BE GIVEN TO THE OUTPUTS OF PRECISSION, ACCURACY AND LEARNING CAPACITY OF THE SYSTEM; 4) FINALLY, A SOFTWARE APPLICATION WILL BE DEVELOPED TO WORK IN A WEB-ENVIRONMAENT TO ALLOW EASY ACCESS AND USE FOR PROFESSIONALS. IN THIS LAST STEP OF TH EPROJECT, THE PROGRAM WILL INTEGRATE THE KNOLWDGE-BASED MODEL WITH THE SIMULATION PROGRAM DEVELOPED IN THE PREVIOUS PROJECT (AGL-2012-39888-CO2-01). THE HIPOTHESIS IS THAT: 1) THE INTEGRATION OF DATA FROM DIFFERENT MONITORIZATION PLATFORMS WILL PROVIDE A BETTER CAPACITY TO GENERATE KNOWLEDGE AND IMPROVE PRECISSION AND ACCURACY OF THE RECOMMENDATIONS, AND; 2) THE APPLICATION OF ARTIFICIAL INTELLIGENCE METHODOLOGIES WILL PROMOTE THE USE OF DATA TO TAKE DECISSIONS THAT WILL HELP IMPROVE THE COMPETITIVENESS OF THE DAIRY BUSSINESS. THE IMPLEMENTATION OF THE MODEL IN A WEB-ACCESSIBLE CONTEXT WILL FACILITATE ITS USE AT FARM LEVEL. THIS STRATEGY HAS BEEN SUCCESSFULLY USED IN OUR PREVIOUS PROJECT.