A data-architecture to monitor and collect cow-individual methane emissions real-timefrom commercial dairy farms

Resúmen

Real-time monitoring and collecting cow-individual methane emissions will help individual farmers in identifying which management interventions affect methane emissions, and the dairy sector in developing strategies to reduce methane emissions. To achieve this real-time monitoring and collecting of cowindividual methane data, an architecture was developed that automates both aspects in a commercial setting. The first step in the data architecture was to collect the analogue signal of sniffers real-time, and transform this signal into methane concentrations. Because these sniffers do not record cow identification, the second step was to combine the methane concentration data with real-time cow identification. The cow identification is retrieved by automatically detecting the ear tag in a live-stream video footage, to subsequently ‘read’ the 4-digit number of that ear tag. With the deployed architecture, we developed a universal, low-tech, and scalable method to collect cow-individual sensor data real-time for technologies that do not record cow identification by default.