ClearFarm project
ClearPharm
Co-designed Welfare Monitoring Platform for Pig and Dairy Cattle
Description
Animal welfare has become a fundamental aspect of livestock production. Current animal welfare assessment tools usually rely on momentary recordings and on awkward integration of various indicators with different units. Besides, existing tools to assess farm animal welfare are time consuming and costly. Precision livestock farming (PLF)-technology allows to monitor and optimize farming processes. PLF systems generate large volumes of onfarm data that can be used to monitor welfare in pigs and dairy cattle.
ClearFarm proposes to use PLF technology to integrate animal-based data, through a blockchain approach, thus enabling improved animal welfare across the entire production chain. This will contribute to improved sustainable pig and dairy cattle production, the two livestock production systems with the highest shares in Europe.
Participants
The project is coordinated by the Universitat Autònoma de Barcelona, and the rest of consortium is composed of: the University of Murcia, ELPOZO Alimentación SA and Cooperativa Ganadera del Valle de los Pedroches (Spain), Syntesa Partners and Associates A/S, Skov As Glyngore - Dol Sensors, Aarhus Universitet (Denmark), CONNECTERRA BV, Eshuis BV and Wageningen University (Netherlands), Università degli Studi di Milano (Italy), Lluonnonvarakeskus and Hämeenlinnan Osuusmeijeri (Finland) and Cattle Watch Ltd (Israel).
Activities
ClearFarm aims to co-design, develop and validate a software platform powered by an algorithm integrating PLF data to provide animal welfare information, as well as other environmental and economic sustainability information that will assist production chain stakeholders and consumers on decision making within the pig and dairy cattle value chains. Regulators, consumers and producers, policy makers, among other stakeholders, will get involved in the design of the new solution, seeking thus a multi-actor approach in most of the stages of the project.
Period
2012 - 2022
Funding
The project has received 6 M€ from the European Union’s Horizon 2020 research and innovation programme.
Animal welfare has become a fundamental aspect of livestock production. Current animal welfare assessment tools usually rely on momentary recordings and on awkward integration of various indicators with different units. Besides, existing tools to assess farm animal welfare are time consuming and costly. Precision livestock farming (PLF)-technology allows to monitor and optimize farming processes. PLF systems generate large volumes of onfarm data that can be used to monitor welfare in pigs and dairy cattle.
ClearFarm proposes to use PLF technology to integrate animal-based data, through a blockchain approach, thus enabling improved animal welfare across the entire production chain. This will contribute to improved sustainable pig and dairy cattle production, the two livestock production systems with the highest shares in Europe.
Participants
The project is coordinated by the Universitat Autònoma de Barcelona, and the rest of consortium is composed of: the University of Murcia, ELPOZO Alimentación SA and Cooperativa Ganadera del Valle de los Pedroches (Spain), Syntesa Partners and Associates A/S, Skov As Glyngore - Dol Sensors, Aarhus Universitet (Denmark), CONNECTERRA BV, Eshuis BV and Wageningen University (Netherlands), Università degli Studi di Milano (Italy), Lluonnonvarakeskus and Hämeenlinnan Osuusmeijeri (Finland) and Cattle Watch Ltd (Israel).
Activities
ClearFarm aims to co-design, develop and validate a software platform powered by an algorithm integrating PLF data to provide animal welfare information, as well as other environmental and economic sustainability information that will assist production chain stakeholders and consumers on decision making within the pig and dairy cattle value chains. Regulators, consumers and producers, policy makers, among other stakeholders, will get involved in the design of the new solution, seeking thus a multi-actor approach in most of the stages of the project.
Period
2012 - 2022
Funding
The project has received 6 M€ from the European Union’s Horizon 2020 research and innovation programme.