Occupational Safety Research Needs in the Field of Robotics and Autonomous Machines in Agriculture
Public Domain
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2025/08/05
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File Language:
English
Details
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Journal Article:Journal of Agricultural Safety and Health
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Personal Author:
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Description:In 2022, the SAfety for Emerging Robotics and Autonomous AGriculture (SAFER AG) Workshop was held to discuss and understand emerging challenges related to safety, occupational safety research needs, workforce implications, and other issues associated with robotics and autonomous machines in agriculture. This paper presents the major findings from the occupational safety research track of the workshop. This track identified existing hurdles to conducting occupational safety research including logistical barriers, intellectual property concerns, long timelines, and lack of funding. Considerations for developing a tracking or surveillance system for adverse events as well as exposure related to these technologies were also discussed, emphasizing the need for a comprehensive system. Finally, the priority occupational safety research needs identified during the session were related to human and non-human machine interaction, adoption of automation in the work setting, and event tracking/surveillance. To overcome barriers to research, collaboration between occupational safety researchers and technology developers is crucial. Enhancements to existing surveillance systems can facilitate better understanding of captured events. Additionally, prioritizing research on worker risk from robotics and autonomous machines in agriculture is essential. The integration of robotics and autonomous machines in agriculture has revolutionized the industry but requires evidence-based safety research, outreach, and education to ensure worker safety and health.
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Source:J Agric Saf Health 2025 Aug; 31(3):217-230
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ISSN:1074-7583
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Pages in Document:14 pdf pages
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Volume:31
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Issue:3
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NIOSHTIC Number:nn:20071451
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Email:serapgorucu@ufl.edu
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Federal Fiscal Year:2025
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Peer Reviewed:True
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Main Document Checksum:urn:sha-512:dfaaf7540580dd6421e0035cc499cfc92612dbc06625e64b11224337e97d116b314b319e7652097206c2a073e4fde2821ead55362d54dc279c3d0d5e5aab31cc
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English
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