총 658페이지
616페이지 본문시작
Interoperable systems and platforms that can combine and translate multiple data types
from across the country into useful evidence-based insights would be highly beneficial for
biosecurity decision?making. Systems in this class will likely make use of big data
technology to collate diverse data feeds, alongside artificial intelligence (AI) and machine
learning systems to automate data analysis and support decision-making. In the case of
systems that incorporate citizen science, AI-driven verification of data reported by users
could yield significant accuracy improvements with minimal additional resource strain.
The Technology Readiness Level (TRL)of this technology (see Appendix B)varies widely
depending on the level of system capability in question. R&Dpriorities for AIand Machine
Learning to enhance decision-making include auditing applicable datasets to build data
interrogation strategies; developing systems to synthesise intelligence from unstructured
datasets;designing and creating algorithms for sampling in specific targets contexts (e.g. in
airborne/satellite imaging); and developing core technology sensitivity to discern between
meaningful and negligible information.
Science and technology: Traceability systems
While Australia’s agricultural industry is an early user and developer of traceability
systems to demonstrate food safety, there is still significant room to develop technologies
that provide greater coverage and transparency of Australian product value chains.
Technology has the potential to provide improved export-orientated market access and
growth for the industry by building global trust in Australian regulatory processes.
There are many noteworthy Australian examples of supply chain provenance-based
technologies and systems, including the National Livestock Identification System (NLIS).
This system uses NLIS approved devices to allow identification and tracking of cattle,
sheep and goats,with movement recorded centrally on the NLISdatabase.
The Victorian Government’s Growing Food and Fibre Markets (GFFM)is another example,
which aims to support market access and supply chain traceability through uptake of new
diagnostic,verification and sensor technologies to assure export product integrity and meet
future expectations of trading partners. Benefits of enhancing Australia’s traceability
systems include improving marketability,market development and access,and strengthening
the ability to respond to biosecurity incidents. Traceability of Australia’s imports and
exports can provide confidence in the biosecurity status of the country of origin, thereby
reducing biosecurity risk and making supply chains more transparent.
Domesticandinternationalpartnerships
Mutually beneficial partnerships and co-developed strategies and activities will be key to
strong national biosecurity decision making and rapid, nationally coordinated responses to
emerging risks. For example, negotiating consistent domestic trade policies and processes
- 616 -
from across the country into useful evidence-based insights would be highly beneficial for
biosecurity decision?making. Systems in this class will likely make use of big data
technology to collate diverse data feeds, alongside artificial intelligence (AI) and machine
learning systems to automate data analysis and support decision-making. In the case of
systems that incorporate citizen science, AI-driven verification of data reported by users
could yield significant accuracy improvements with minimal additional resource strain.
The Technology Readiness Level (TRL)of this technology (see Appendix B)varies widely
depending on the level of system capability in question. R&Dpriorities for AIand Machine
Learning to enhance decision-making include auditing applicable datasets to build data
interrogation strategies; developing systems to synthesise intelligence from unstructured
datasets;designing and creating algorithms for sampling in specific targets contexts (e.g. in
airborne/satellite imaging); and developing core technology sensitivity to discern between
meaningful and negligible information.
Science and technology: Traceability systems
While Australia’s agricultural industry is an early user and developer of traceability
systems to demonstrate food safety, there is still significant room to develop technologies
that provide greater coverage and transparency of Australian product value chains.
Technology has the potential to provide improved export-orientated market access and
growth for the industry by building global trust in Australian regulatory processes.
There are many noteworthy Australian examples of supply chain provenance-based
technologies and systems, including the National Livestock Identification System (NLIS).
This system uses NLIS approved devices to allow identification and tracking of cattle,
sheep and goats,with movement recorded centrally on the NLISdatabase.
The Victorian Government’s Growing Food and Fibre Markets (GFFM)is another example,
which aims to support market access and supply chain traceability through uptake of new
diagnostic,verification and sensor technologies to assure export product integrity and meet
future expectations of trading partners. Benefits of enhancing Australia’s traceability
systems include improving marketability,market development and access,and strengthening
the ability to respond to biosecurity incidents. Traceability of Australia’s imports and
exports can provide confidence in the biosecurity status of the country of origin, thereby
reducing biosecurity risk and making supply chains more transparent.
Domesticandinternationalpartnerships
Mutually beneficial partnerships and co-developed strategies and activities will be key to
strong national biosecurity decision making and rapid, nationally coordinated responses to
emerging risks. For example, negotiating consistent domestic trade policies and processes
- 616 -
616페이지 본문끝
메뉴
현재 포커스의 아래내용들은 동일한 컨텐츠를 가지고 페이지넘김 효과및 시각적 효과를 제공하는 페이지이므로 스크린리더 사용자는 여기까지만 낭독하시고 위의 페이지이동 링크를 사용하여 다음페이지로 이동하시기 바랍니다.