Aerial Visual Perception in Smart Farming: Field Study of Wheat Yellow Rust Monitoring
- Submitting institution
-
The University of Essex
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 1424
- Type
- D - Journal article
- DOI
-
10.1109/TII.2020.2979237
- Title of journal
- IEEE Transactions on Industrial Informatics
- Article number
- -
- First page
- 2242
- Volume
- 17
- Issue
- 3
- ISSN
- 1551-3203
- Open access status
- Compliant
- Month of publication
- March
- Year of publication
- 2020
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
8
- Research group(s)
-
D - Robotics and Embedded Systems (RES)
- Citation count
- 3
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Crop diseases are a major challenge in modern agriculture (20-40% yield-losses worldwide), not only damaging crop yield/quality, posing serious threats to food security, but also exerting adverse environmental impacts. This joint work by six (UK/China) institutes, published in a leading industrial informatics journal, is the first to develop an automated yellow-rust disease mapping system; seamlessly leveraging UAV, multispectral imaging and deep-learning algorithms. This work is one of the key publications for the 1.2M STFC Newton fund (ST/N006852/1) https://gtr.ukri.org/projects?ref=ST%2FN006852%2F1, and also lays the basis for winning the follow-up STFC Newton fund (ST/V00137X/1) https://gtr.ukri.org/projects?ref=ST%2FV00137X%2F1, and InnovateUK grant on solar farm inspection (https://apply-for-innovation-funding.service.gov.uk/competition/754/overview).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -