P.PSH.1293 - Using devices & data to generate ROIs in a mixed farming enterprise

Summary

This project was comprised of five independent, but connected, activities which define and contribute to the overall project objective of identifying Return On Investments (ROI’s) derived from the installation and deployment of IoT devices and utilising device generated data in a commercial mixed farming enterprise. These five activities represent the areas identified by the producer themselves as potentially having a ROI greater than expected due to being utilised further than the manufacturers prescribed application for the device.

Objectives

The key objective of this project is the creation of ROl’s derived from devices and data relating to loT devices in operation on a commercial mixed farming enterprise, to support producer adoption of software and hardware that will enhance animal productivity and improved animal welfare.
The below five subject areas were identified as being valuable to further investigate, to increase the knowledge in these subject areas through the analysis of data from the IoT devices used to assess the productivity and management of these areas and to derive their associated ROI’s.

• animal cropping interactions
• summer joining
• supply chain data transfer
• water management
• soil amelioration."

Key findings

• Activities undertaken have demonstrated the multiple uses and applications of data where the ability to reuse data has provided additional outcomes with varying ROI’s. Therefore, suggesting that data following the FAIR data principles (Wilkinson, et al., 2016) can provide higher returns on investment than data that doesn’t.

• IoT devices can provide powerful operational insights to producers and enable them to generate their own ROI’s. The more data producers have the ability to access and analyse the more potential ROI’s emerge.

• The automation pathway offers a breakdown of the specific elements involved with on farm processes, assisting both producers and AgTech providers in identifying areas which may provide better returns on investment.

• Producers can be empowered to undertake targeted research activities that enhance their own production systems.

Benefits to industry

AgTech adoption can be driven from the ground up rather than the top down this will utilise the peer-to-peer learning that is known to exist at a grass roots level and the processes undertaken will be developed in a manner that minimises impact on already time poor producers.

Producer driven research has the potential to accelerate grass roots changes to production systems. Benefits to industry that are specific to the individual activities undertaken can be found within the respective activities conclusion section.

MLA action

The learnings from this project have contributed to the direction of the Digital Agriculture business plan.

Future research

Key recommendations arising from this project include:

• A feeper analysis into the aspects of the water efficiency calculation such as evaporation.

• Trialing the use of collar data patterns as the trigger for supplement feeding of sheep.

• The extension of crop grazing analysis to include respective enterprise input costs.