Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/33551
Title: Real‐World Deployment of a Dynamic Selective LASER Weeding System Using Multispectral Imagery
Authors: Wane, S
Wang, M
Butler, M
Cheein, FA
Keywords: edge computing;embedded system;field robotics
Issue Date: 27-Jun-2026
Publisher: Wiley on behalf of Zhejiang University Press
Citation: Wane,S. (2026) 'Real‐World Deployment of a Dynamic Selective LASER Weeding System Using Multispectral Imagery', IET Cyber-Systems and Robotics, 8 (1), e70059, pp. 1–8. doi: 10.1049/csy2.70059.
Abstract: The use of chemical treatments for weed control is increasingly challenged by weed resistance, regulatory restrictions on chemicals and the risk of soil and water contamination that can pose health hazards. Chemical weed treatments are unsustainable, prompting exploration of alternative methods such as boiling water, electrocution and directed fire. However, these approaches are limited: water-based treatments require a reliable water supply in the field, and electric or fire-based methods pose additional environmental risks. This work proposes a targeted light amplified stimulation of emission by radiation (LASER) treatment and selective spraying system integrated with automatic weed identification. The system, mounted on the rear of a tractor, utilises a bispectral imaging setup to distinguish weeds from crops. Close-to-crop weeds are automatically selected for LASER treatment, whereas a selective sprayer targets other weeds with a glyphosate globule. This integrated system approach is named ‘Hyperweeding’. The results demonstrate successful separation of row crops from weeds, achieving a contamination-free crop with a significant reduction in glyphosate usage, and effectively treating weeds at speeds of 0.1 m • s⁻¹.
Description: Data Availability Statement: All relevant data are included within the article.
URI: https://bura.brunel.ac.uk/handle/2438/33551
DOI: https://doi.org/10.1049/csy2.70059
ISSN: 2097-3608
Other Identifiers: ORCiD: Sam Wane https://orcid.org/0000-0003-3810-2902
ORCiD: Mingfeng Wang https://orcid.org/0000-0001-6551-0325
ORCiD: Fernando Auat Cheein https://orcid.org/0000-0002-6347-7696
Appears in Collections:Department of Mechanical and Aerospace Engineering Research Papers

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