Joining forces to tap into data

Joining forces to tap into data

Agribusiness
Esperance grower Belinda Lay has embraced agtech in her farm business and has enjoyed seeing benefit of data-driven solutions.

Esperance grower Belinda Lay has embraced agtech in her farm business and has enjoyed seeing benefit of data-driven solutions.

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"Unless you cover each of these steps properly, the technology won't work or farmers won't be able to get the full benefit of what they're putting in."

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A FARMER and agtech expert have joined forces to develop a framework to help growers understand how to adequately utilise their on-farm data, which will in turn enable them to make informed decisions with precision.

Esperance sheep and grain farmer Belinda Lay is fascinated by data and the solutions it can provide and by implementing the framework that she helped develop with AxisTech managing director Wes Lawrence, she has experienced first-hand how efficient her farming operating can be - and she's only just scratched the surface.

The pair call it the eight-pillar framework, which deconstructs data or agtech-driven solutions into their fundamental elements, or pillars.

"These eight pillars are necessary for agtech application," Ms Lay said.

"It's vital because there is different information circulating about how to implement agtech; many people think there are only four steps to success, but there are eight.

"Unless you cover each of these steps properly, the technology won't work or farmers won't be able to get the full benefit of what they're putting in."

The framework is generic so can be applied to any agtech device and works across all types of enterprises.

It also doesn't promote any individual products or software.

"Once farmers have the overall understanding of the framework, it will help them navigate agtech and this digital revolution that the industry is experiencing," Ms Lay said.

1. Installation:

It begins with understanding identifying the problem that needs solving - where it is physically located and assessing the physical environment in which the agtech device needs to be.

Terrain, ease of access, soil type, infrastructure requirements, mounting brackets, environmental exposure, exposure to livestock and other animals, correctly placing things like solar panels and wind direction sensors are some of the many factors to consider.

Installation also includes any software programs or app to install on devices.

2. Sensors:

This step is about understanding the sensors in the device and how they work.

Sensors undertake key measurements and devices may have one or multiple sensors and could be internal or external.

The data output and the nature of the solution is dependent on the sensors that exist within a device.

Sensor quality and function are part of data quality and reliability.

3. Devices:

Understanding how the device manages, powers and controls itself, but also how it manages sensor readings and packages them into messages and transmits them within its programmed format.

Devices can also receive commands and perform functions within their physical, technological and power constraints.

4. Connectivity:

There is a plethora of connectivity options and terminology, which fit together differently depending on where the installation is relative to the existing or deployed infrastructure, and is usually multiple technologies.

It includes Bluetooth/BLE, WiFi, 3G/4G/5G cellular/LTE/Cat-M1/NB-IOT, LoRaWAN, Sigfox, ISM radio frequency, UHF, satellite, nbn, fibre, base stations, gateways, modems, last mile and backhaul.

5. Data ingestion:

Separating data ingestion from data storage (pillar six) enables a focus on device messages and how data flows are handled and then becomes meaningful data.

This step provides a framework for understanding how batch and historical data can be handled, how farm records can be digitised and covers the importance of attributes, units of measurements and the importance of data principles and data standardisation.

6. Data storage:

Terminology such as servers, cloud, AWS, Azure, SQL, databases and data historians fall within this pillar.

Here attention is given to how data is stored - where it is, who holds it, who owns it, who has access to it and what it's being used for.

7. On-farm data consumption:

This step is about utilising data via applications, dashboards and apps to help form farm solutions.

It also covers consumption of third party data such as satellite imagery and vision from drones and cameras.

Understanding the layers of data can deliver farmer benefit, but the way the data has been ingested and stored is essential for this to happen.

This pillar is currently where Ms Lay is at in her farm business.

"I have put in collar data, paddock data, tank level data, historical stock data etc, so now I am able to start drawing things out of this data that mean something to me," she said.

"But it's the way that I have put it in and stored it that allows me to do that.

"This is where I am able to consume the data I have put in and use it in my business in a way that was not previously available."

In just a couple of years the level of precision that Ms Lay has achieved on her farm by following this framework of data integration has been eye-opening.

After putting electronic collars on some of her flock for her 2019 AgriFutures research project, which saw her win WA Rural Woman of the Year last year, she has gained significant data on the behaviour of her sheep.

"My ability to correlate data from the collars and the sheep's impact on my crops from crop grazing, has enabled me to find out what that means to my bottom line by a dollar per hectare analysis on that one particular paddock," she said.

"In a 26 hectare paddock, for example, I found the sheep only utilised 6ha, so I did a mid-year assessment on production.

"For the 20ha that were unaffected, I left the value of the crop at three tonnes per hectare and put a dollar value on that; on the 6ha the sheep impacted I reduced the crop yield to 2t/ha and put a dollar on that.

"I was also able to calculate the number of kilograms of lamb that was born and produced from that 6ha and add the value of that lamb production back to those 6ha and work out which on a per hectare basis was the most productive for me."

As this analysis was only a prediction Ms Lay said it could be taken further once the yield data was available, then she'd be about to know the actual impact of crop grazing on her crop and sheep production.

"Those are the sort of insights farmers can get from following the framework and I don't know of anyone else that can do that," she said.

"That is precision agriculture or as I call it 'decision agriculture' because the data allows me to make informed decisions."

8. Aggregated consumption:

Ms Lay and Mr Lawrence claim 'aggregated consumption' is emerging as a new frontier with developing data sharing, data hubs, grouped displays, grouped machine learning and third party consumption of data for purposes such as traceability and benchmarking.

Within this pillar growers will be able to choose to share their data with other farmers who have databases.

"Here we move from being able to assess on-farm production to regional production, or State production or even national production, because everyone has data stored in the same format we are able to take those insights and amalgamate it with other farms," Ms Lay said.

"The ability to use multiple datasets from across the region to track particular things - for example regarding water - drought deficiency, environmental and seasonal change is impacting on water issues."

Referring to the Esperance region as an example, Ms Lay said it's common for organisations to have disparity in data with datasets on water in different places and formats, which are not joined and are controlled differently, including by government, grower groups, farmers, companies, and industry organisations.

But if farmers and organisations aggregated their data, they would be able to gain a broader, more accurate picture of the region and its issues.

Originally from a farm at Cranbrook, AxisTech managing director Wes Lawrence has been in the tech industry for more than 10 years.

Originally from a farm at Cranbrook, AxisTech managing director Wes Lawrence has been in the tech industry for more than 10 years.

By adopting this eight-pillar framework, Mr Lawrence hopes farmers will be able to better understand how they can utilise and control their farm data to assist in the discussion, confidence and adoption of agtech as the industry continues into the next phase of on-farm efficiency, production, profitability and addressing social and ecological impact.

"The framework will help farmers know where the gaps are in their own knowledge and in the solution they are trying to achieve," Mr Lawrence said.

"It helps give a framework where the desired measurement can drive the desired solution."

Mr Lawrence and Ms Lay aim to share the framework with growers through one-day workshops next year.

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