CSIRO's Data61

CSIRO's Data61, the data and digital specialist arm of Australia's national science agency is hosting an online event on Wednesday 2nd December 2020 showcasing our latest technology advances in the area of Supply Chain Integrity. Join us on the day to hear from researchers and industry.

Save the date now!


  • Free


Dana Sanchez

Event date: 02Dec 2020

Wednesday 2 Dec 2020

Online virtual event

  • 9.30am to 12.40pm AEDT

Webinar details will be emailed to registrants

More information

The showcase will feature CSIRO technologies developed to address emerging challenges including:

  • How do you trust data collected on the farm so it can reliably validate provenance?
  • Can we automate the monitoring of animal health and welfare?
  • Can we reduce regulatory burden through automated compliance?
  • What advances have been made in using biological origin to verify authenticity?
  • How do we maintain visibility of products moving through the supply chain and detect fraud in an affordable way?

We will also host a panel session discussing key findings from a recent report released by MLA including “The industry views on the need for investment in enhanced supply chain integrity systems are at odds with those of researchers and technology/service providers”.

We look forward to hearing from you on the day to help inform the future direction of our research.

Contact: Dana.Sanchez@data61.csiro.au.


Time Activity
9.30am Welcome
Dana Sanchez, Project Manager, CSIRO Data61
9.35am Advancing Supply Chain Integrity
Beef exports are valued at more than $10 billion per year, so it is important that Australia delivers a premium, safe and healthy product to the world to maintain this market share. Australian producers are renowned for very high standards of animal health and welfare, and environmental stewardship. However, in a fragmented and complex supply chain this message is easily lost.
Aaron Ingham, Research Scientist and Group Leader, CSIRO Agriculture & Food
Ryan McAllister, Leader, Trusted Agrifood Exports, CSIRO
9.50am Demonstrating Automated Farm Provenance
Export value built on Australia’s brand will need data to validate the safety, production and origin of our products. But how can we trust the data and ensure it can’t be modified? And how can we fulfil government requirements without being overwhelmed by regulatory burden? Provenance, Trust and Automated Compliance are proposed and demonstrated as technologies towards achieving this.
Phil Valencia, Team Leader, Embedded Intelligence, CSIRO Data61
10.10am Panel Session
In September, MLA commissioned a report analysing product integrity systems in the Australian red meat industry. Our panel members will discuss a key finding from the report - The industry views on the need for investment in enhanced supply chain integrity systems are at odds with those of researchers and technology/service providers.
Panel members:
  • Lucinda Corrigan, Director, Rennylea Pastoral Company PL
  • Sonja Dominik, Group Leader, Sustainability & Welfare, CSIRO Agriculture & Food
  • Ian Jenson, Manager, Market Access Science and Technology, Meat & Livestock Australia
  • Skye Richmond, Business Development & Commercialisation, CSIRO
10.45am Short Break
From this point, feel free to switch from one weblink to another to join any session. You can enter and exit as many times as you like.
Stream 1
10.55am Advances in the use of biological origin to verify authenticity
Tagless verification of provenance and identification of product is possible through unique signatures, biogeochemical, isotopic, lipidomic and genomic. In an Australian context, we show two levels of granularity - biogeochemical and isotopic signatures enabling verification to a region and even to the property of origin; and genomic signatures enabling unique identification of individual animals. In addition, we demonstrate privacypreserving signature reporting for the accurate prediction of regional product provenance while providing confidentiality to primary producers.
Sonja Dominik, Group Leader, Sustainability & Welfare, CSIRO Agriculture & Food
David Smith, Principal Research Scientist, CSIRO Data61
Uta Stockmann, Team Leader, Proximal Sensing, CSIRO Agriculture & Food
11.25am Reducing regulatory burden through automated compliance checking
We present a regulatory technology for checking compliance with welfare guidelines and ensuring animal wellbeing. We show how to track animal behaviour and link that to the welfare guidelines and standards, so that potential issues are automatically detected and farmers are notified.
Regis Riveret, Senior Research Scientist, CSIRO Data61
Nick van Beest, Team leader, Senior Research Scientist, CSIRO Data61
11.45am Q&A Session: Re-thinking blockchain – hype or need?
Join us to discuss
12.05pm Low power cattle behaviour classification on an ear tag device
We present the data processing pipeline and machine-learning algorithms developed for classifying cattle behaviour on the embedded system of the ear tags. The behaviour classification results are utilized by the trust and regtech components.
Reza Arablouei, Research Scientist, CSIRO Data61
12.25pm Automated tracking of individual cuts of meat back to the source animal
How can we automatically track individual prime cuts of meat in the deboning room of an abattoir using AI based video analysis? We will present our methods and some initial results to address this problem.
Dadong Wang, Principal Research Scientist, CSIRO Data61
12.40pm Finish
Stream 2
10.55am Video-based identification and classification of cattle behaviours
We present our data annotation and classification pipeline to recognise individual cows and their behaviour (drinking, grazing and other) from on-farm videos. Annotations and/or classifications from videos are used as ground truth to label other synchronised sensor streams (from the embedded system of the ear tags) to train machine learning algorithms relying only on sensor streams to recognise cattle behaviour.
Chuong Nguyen, Senior Research Scientist, CSIRO Data61

High-resolution herd dynamics tracking for social and welfare metrics
We report on recent on-farm trials, where our refined GPS devices are able to record and report in real-time the herd dynamics of multiple sheep flocks. Machine learning techniques are designed to identify the leaders of the herds and understand the stability of the herds and the social needs of individual animals.
Wei Ni, Principal Research Scientist, CSIRO Data61
11.25am Ensuring data and devices on the farm are protected and trusted
We introduce the EnerID blockchain, which is accessible for everyone (individuals or agencies) to record any big or small information without cost. EnerID can process messages in different efficiency modes and has been patented by CSIRO. In addition, two lightweight encryption schemes are introduced, one of which can generate very short ciphertexts for short messages.
Dongxi Liu, Principal Research Scientist, CSIRO Data61
11.45am Treating cows badly: A high fidelity simulator for Automated Farm Provenance
We present a Multi-Agent Systems Simulator (MASS) engine for simulating large scale distributed IoT networks of animals with smart ear tags on smart farms and pushing synthetic data through the demonstrator. Simulation of the animals and the smart devices they interact with allows us to test our technologies without physical subjecting animals to unethical conditions or needing to deploy devices on the farm.
Karl von Richter, Technical Lead Embedded Systems Engineer, CSIRO Data61
12.05pm On-farm data trust and provenance
We present our on-farm data trust and data provenance architectures. Our data provenance architecture is built on IoT edge blockchain and distributed data storage technologies, while data trust is established by our novel trust and reputation mechanisms.
Volkan Dedeoglu, Postdoctoral Research Fellow, CSIRO Data61
12.25pm Maintaining visibility of products moving through the supply chain and detecting fraud in an affordable way
We report on our approach to tracking and anomaly detection in a boxed meat transport chain. We focus data collection from energy-harvesting sensors and analysing them with machine learning and rule-based methods.
Peter Baumgartner, Principal Research Scientist, CSIRO Data61
Sara Khalifa, Senior Research Scientist, CSIRO Data61
12.40pm Finish

Panel members

Lucinda Corrigan

Lucinda Corrigan

Chair at Sheep Sustainability Framework Governance Committee

Sonja Dominik

Sonja Dominik

Group Leader, Sustainability & Welfare, CSIRO Agriculture & Food

Ian Jenson

Ian Jenson

Manager, Market Access Science and Technology, Meat & Livestock Australia

Skye Richmond

Skye Richmond

Business Development & Commercialisation, CSIRO

Science areas:

Event type: Online