P.PSH.2201 - Algorithm hosting platform use and proof of concept

Summary

The project demonstrated how a combination of technologies can facilitate user-controlled data sharing and assigned data ownership to produce data driven insights between red meat supply chain partners. The project showcased to producers the potential for automated data flows to feed directly through to research algorithms to help producers make data driven decisions.

Objectives

The aim of the project was to deliver a working example of how an integrated digital data platform that connects producers' data directly with data analytics researchers, can lead to better adoption of research and development outcomes.

Key findings

The project showcased to producers the potential for automated data flows to feed directly through to research algorithms to help producers make data driven decisions.

The ‘AgriTrakka’ product now provides project participants with the ability to access automated in-paddock data weighing plus uploaded spreadsheet data from yard weights and direct these weights through to the project data storage warehouse. Algorithms developed within the project are now hosted on Shaipup (as a component of AgriTrakka) and are undergoing continued refinement.

Reports were prepared for the producers who contributed to the project, providing them feedback and insight on their data using the algorithms developed. A model for market prediction tool based on linear growth rates has been developed and it is expected this base model will be delivered to Shaipup soon. It has been identified that more data will be required across more years to refine this model for non-linear cattle live weight gain for individual farms.

Benefits to industry

These technologies (data sharing infrastructure and algorithm hosting platform) will drive new business opportunities for the red meat industry. The project showcased to producers the potential for automated data flows to feed directly through to research algorithms, to help them make data driven decisions.

MLA action

MLA/ISC will share with producers the algorithm once available on the platform.

Future research

The technology explored in this project is relatively new and producers are still exploring how accurate the data they are receiving is and how they can apply it within their production system.