Individualized Livestock Production

Photo: ATB

Project

Title
Entwicklung eines intelligenten UAV-gestützten Unkrautmonitoringsystems für den selektiven und teilflächenspezifischen Herbizideinsatz
Acronym
weed-AI-seek
Start
28.05.2021
End
27.05.2024
Coordinating Institute
Leibniz-Institut für Agrartechnik und Bioökonomie e.V. (ATB)
Partner
CiS-GmbH
Hochschule Harz - Hochschule für angewandte Wissenschaften

Allocated to research program
Summary
The objective of the weed-AI-seek project is to develop an intelligent real-time monitoring and mapping system for the detection of weed distribution in cereal stands. For this purpose, high-resolution aerial image data is captured at low flight altitude and classified directly on the drone using optimised onboard AI image recognition during the overflight. The innovative method enables species-specific recognition at the level of individual plants. With the help of derived application maps, the application of herbicides is to be more precisely localised and selectively adapted to the real and species-specific weed distribution in cereal stands. In this way, the project makes a significant contribution to reducing the use of plant protection products in arable farming and thus promotes sustainable agriculture. The Leibniz Institute of Agricultural Engineering and Bioeconomy e.V. (ATB) is involved in all aspects of the project. (ATB) is involved in all project modules. A major contribution will be the development of an annotation database for training and testing AI models for species-specific recognition of weeds. This database contains both the image data extracted from the UAV images and metadata generated by experts. This comprehensive database will represent the diversity of plant species and background in wheat stands and thus go beyond the characterisation of leading weeds alone. The ATB is also significantly involved in the creation of the image recognition model for an embedded system.

Funding
Bundesministerium für Ernährung und Landwirtschaft (BMEL)
Funding agency
Bundesanstalt für Landwirtschaft und Ernährung - Projektträger
Grant agreement number
28DK105A20

Cookies

We use cookies. Some are required to offer you the best possible content and functions while others help us to anonymously analyze access to our website. (Matomo) Privacy policy

Required required

Necessary cookies are absolutely essential for the proper functioning of the website. This category only includes cookies that ensure basic functionalities and security features of the website. These cookies do not store any personal information.

Cookie Duration Description
PHPSESSID Session Stores your current session with reference to PHP applications, ensuring that all features of the site can be displayed properly. The cookie is deleted when the browser is closed.
bakery 24 hours Stores your cookie preferences.
fe_typo_user Session Is used to identify a session ID when logging into the TYPO3 frontend.
__Secure-typo3nonce_xxx Session Security-related. For internal use by TYPO3.
Analytics

With cookies in this category, we learn from visitors' behavior on our website and can make relevant information even more accessible.

Cookie Duration Description
_pk_id.xxx 13 months Matomo - User ID (for anonymous statistical analysis of visitor traffic; determines which user is being tracked)
_pk_ses.xxx 30 minutes Matomo - Session ID (for anonymous statistical analysis of visitor traffic; determines which session is being tracked)