digital agriculture: an australian red meat industry ... · digital agriculture: an australian red...
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Digital Agriculture: An Australian Red Meat Industry Perspective
CSIRO AGRICULTURE & FOOD
Drewe Ferguson and Dave Henry Australian Red Meat Industries Digital Forum – October 2016
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Presentation title | Presenter name 2 |
“…….there has never been a more exciting time to
be an Australian.”
Malcolm Turnbull PM 15 September 2015
Source: buzzfeed.com
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We see it in our everyday lives already …
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Emerging technology trends
Energy technologies • Ultra-capacitors (high-density energy
storage) • Wireless energy transfer • Energy harvesting (MEMS devices,
organic solar cells)
Robotics technologies • Micro/nano-scale robots • Robot swarms
Information technologies • Artificial Intelligence, machine vision & learning • Fast or long-range wireless comms • Low-power, distributed systems -> “Internet of
Things”
Materials science • Programmable matter / quantum dots • Nanomaterials / carbon nanotubes
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The Future for Agriculture is Bright!
Annual Global Industry Growth 2013-33 Sectors of Australian Comparative Advantage
Deloitte Access Economics Projections
Agribusiness is 3rd fastest growing sector and 1st for Australian advantage
Global Growth Rate (%)
Sectors
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Some amazing things are emerging from the digital “revolution”
Many more to come and they will transform agriculture …..
What will be truly disruptive ?
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Googles Project Loon Facebooks Aquila drone CSIRO NGARA
NBN
Disruption – the issue of connectivity
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Disruption – the issue of connectivity
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What does it mean for the producer?
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Disruption – the issue of connectivity
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Use case: Connectivity across the farm
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Animal Sensors
Presentation title | Presenter name 10 |
Grazing management
Feed & resource
use efficiency
Strategic supplementation
Automated phenotyping
eg feed intake Welfare status
Disease prediction & early
intervention
Environmental benchmarking
Calving & lambing
alerts
Animal performance
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Disruption – the issue of connectivity
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• Data stream integration (sensors) • Local connectivity • Predictive analytics • Interpretation & visualisation
The Gap ? • Business model • Integration (prediction analytics) • Complex analytics on simple devices
Use case: Connectivity across the farm
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Disruption – the issue of connectivity
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Use case: Connectivity beyond the farm (the Internet of things)
Internet
Climate
Markets
Service Providers
Bench- marking
Inputs Connectivity is central to traceability and
guaranteeing provenance to the consumer
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Disruption – the issue of connectivity
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• Within-farm data • Service providers • Supply Chains • Markets • Benchmarking • Advice sources
The Gap ? • Predictive analytics • Integration of required parties/service providers • Business Model
Use case: Connectivity beyond the farm (the Internet of things)
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Disruption – the issue of connectivity
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What does it mean for the producer?
• Some use-cases enabled by local connectivity • Benefit greatly enhanced by broader connectivity
Connectivity is an enabler, but value capture will be driven by what we do with it
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Disruption – where farmers get their knowledge
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Picture this: • Farmer takes a picture in his crop of an
unknown disease symptom • Adds some of his own descriptive words • Automatically locates
• System trawls through extension material,
factsheets, research papers, media streams …
Could farmers get help from the most knowledgeable expert at a moment’s notice no matter where they were ?
“most probably cause (with probability %) is …..
…… without action, likelihood that you will get a YY% yield decrease …… remedial options:
A. 90% chance of 70% yield B. 75% chance of 90% yield
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• IBM Watson can read 40 million documents in 15 seconds. • Analyzes unstructured data
– 80% of all data today is unstructured (eg news articles, research reports, social media posts, enterprise system data).
– Volume of unstructured data is growing by 62 percent each year – Expected to reach nine times the volume of structured data by 2020.
• Uses natural language processing – means more data from more sources
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Disruption – where farmers get their knowledge Using Artificial Intelligence (AI) to answer semantic questions
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A farmers personalised google search
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Today, AI is used to for interactive Care Insights for Oncology and provides suggestions for treatment plans for lung cancer patients
Enabling farmers to receive help from the most knowledgeable expert at a moment’s notice.
Disruption – where farmers get their knowledge
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Disruption - Automation
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Disruption – Automation Use case: Autonomous control of livestock
• We know we can autonomously control livestock without the need
for an actual fence, using coordinates, wireless technologies and sensors
• Technology advances • Commercialisation pathway
(Agersens) • Industry ‘pull’
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Some things to consider………………….
• Problem definition – Does it need a technology solution?
• What’s the value proposition?
• Barriers to adoption – Technological (access, reliability, ease
of use, cost etc.) – Human (demographics, education,
value perception etc.)
Presentation title | Presenter name 20 |
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Data Decisions Actions
The Realm of “Big Data” • It not about the data, its about capturing value from the data! Data Access, Ownership and Security
Some things to consider………………….
Presentation title | Presenter name 21 |
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LIP – Livestock Information Platform| Bryce Little (CSIRO Agriculture & Food) & Cody Wilson (ABRI) 22 |
– ivestock nformation latform
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Some things to consider………………….
AgTech
– Realising the potential of the digital revolution in agriculture requires a vibrant AgTech sector.
– Closer engagement between R&D providers and AgTech Companies (engage early and often)
Presentation title | Presenter name 23 |
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• Digital technologies will transform the red meat industries • Its about how we connect • Its about how we utilise and capture value from data • Its how we automate and create efficiencies in the system
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Summary