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AgriEngineering
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Innovations, Engineering, Technologies and Best Practices for Ensuring Work Safety...
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Innovations, Engineering, Technologies and Best Practices for Ensuring Work Safety in Agriculture

A special issue of AgriEngineering (ISSN 2624-7402). This special issue belongs to the section "Agricultural Mechanization and Machinery".

Deadline for manuscript submissions: 25 December 2025 | Viewed by 2913

Special Issue Editors

Dr. Marcello Biocca

E-Mail Website
Guest Editor
Consiglio per la Ricerca in Agricoltura e l’Analisi dell’Economia Agraria—CREA, Centro di Ricerca In-Gegneria e Trasformazioni Agroalimentari, Via della Pascolare 16, 00015 Monterotondo, Italy
Interests: agricultural engineering; safety, health and safety in agro-food systems; crop protection technology; mechanization in urban forestry
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Massimo Cecchini

E-Mail Website
Guest Editor
Department of Agricultural and Forestry sciences (DAFNE), University of Tuscia, Via S. Camillo de Lellis, SNC, 01100 Viterbo, Italy
Interests: agricultural machinery; occupational safety and health; ergonomics; agriculture; energy
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

We are pleased to announce a Special Issue (SI) of AgriEngineering, which collects the latest research in the agricultural engineering sector related to safety, health and welfare in agriculture. Agricultural workers are exposed to a number of specific risks that lead to accidents and professional diseases, particularly related (but not only) to the use of machinery and equipment. In recent years, many innovative technologies and solutions have become available, and they can be conveniently applied to reduce these risks, maintaining the economic and environmental sustainability of crops. The SI explores the most important challenges faced by the agricultural engineering sector and offer innovative solutions to promote efficient agricultural practices and social sustainability.

Potential topics include a wide area of subjects, such as assistive technologies, work related musculo-skeletal disorders, work organisation, exposure to physical agents, microclimate safety, and vehicles stability and navigation research.

In this SI, we seek to demonstrate that adopting the latest technologies will allow producers to increase safety, reducing health and social costs and maintaining the productivity.

The SI will be a valuable resource for researchers, policymakers and stakeholders, inspiring them to work together to create a more sustainable future for agriculture.

The SI focuses primarily on original research papers across its whole scope, but also welcomes state-of-the-art review papers and first-hand case histories.

Dr. Marcello Biocca
Prof. Dr. Massimo Cecchini
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. AgriEngineering is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • assistive technologies
  • safety for emerging robotics and autonomous agriculture
  • WMSDs work related musculo-skeletal disorders
  • work organisation
  • safety health and welfare in mechanization
  • innovative safe vehicles and machinery
  • noise, vibration, dust
  • environment and microclimate safety
  • ROPS and vehicles stability.

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Further information on MDPI's Special Issue polices can be found here.

Published Papers (2 papers)

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Research

19 pages, 5492 KiB  
Article
Effects of Noise and Vibration Changes from Agricultural Machinery on Brain Stress Using EEG Measurement
by Seok-Joon Hwang and Ju-Seok Nam
AgriEngineering 2024, 6(4), 4248-4266; https://doi.org/10.3390/agriengineering6040239 - 12 Nov 2024
Viewed by 775
Abstract
In this study, the agricultural work stress induced by the noise and vibration of some agricultural machinery was analyzed through electroencephalogram (EEG) measurements. The values of spectral edge frequency (SEF) 95%, relative gamma power (RGP), and EEG-based working index (EWI), utilized as stress [...] Read more.
In this study, the agricultural work stress induced by the noise and vibration of some agricultural machinery was analyzed through electroencephalogram (EEG) measurements. The values of spectral edge frequency (SEF) 95%, relative gamma power (RGP), and EEG-based working index (EWI), utilized as stress indicators, were derived by analyzing the EEG data collected. The EEG analysis revealed that agricultural work stress manifested when participants engaged in agricultural tasks following a period of rest. Additionally, the right prefrontal cortex was identified where the values of SEF95% and RGP increased concurrently with the rise in noise (61.42–88.39 dBA) and vibration (0.332–1.598 m/s2). This study’s results are expected to be utilized as foundational data to determine the agricultural work stress felt by farmers during work through EEG analysis in response to changes in noise and vibration. Full article
(This article belongs to the Special Issue Innovations, Engineering, Technologies and Best Practices for Ensuring Work Safety in Agriculture)
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19 pages, 6180 KiB  
Article
Human–Robot Interaction through Dynamic Movement Recognition for Agricultural Environments
by Vasileios Moysiadis, Lefteris Benos, George Karras, Dimitrios Kateris, Andrea Peruzzi, Remigio Berruto, Elpiniki Papageorgiou and Dionysis Bochtis
AgriEngineering 2024, 6(3), 2494-2512; https://doi.org/10.3390/agriengineering6030146 - 1 Aug 2024
Cited by 1 | Viewed by 1557
Abstract
In open-field agricultural environments, the inherent unpredictable situations pose significant challenges for effective human–robot interaction. This study aims to enhance natural communication between humans and robots in such challenging conditions by converting the detection of a range of dynamic human movements into specific [...] Read more.
In open-field agricultural environments, the inherent unpredictable situations pose significant challenges for effective human–robot interaction. This study aims to enhance natural communication between humans and robots in such challenging conditions by converting the detection of a range of dynamic human movements into specific robot actions. Various machine learning models were evaluated to classify these movements, with Long Short-Term Memory (LSTM) demonstrating the highest performance. Furthermore, the Robot Operating System (ROS) software (Melodic Version) capabilities were employed to interpret the movements into certain actions to be performed by the unmanned ground vehicle (UGV). The novel interaction framework exploiting vision-based human activity recognition was successfully tested through three scenarios taking place in an orchard, including (a) a UGV following the authorized participant; (b) GPS-based navigation to a specified site of the orchard; and (c) a combined harvesting scenario with the UGV following participants and aid by transporting crates from the harvest site to designated sites. The main challenge was the precise detection of the dynamic hand gesture “come” alongside navigating through intricate environments with complexities in background surroundings and obstacle avoidance. Overall, this study lays a foundation for future advancements in human–robot collaboration in agriculture, offering insights into how integrating dynamic human movements can enhance natural communication, trust, and safety. Full article
(This article belongs to the Special Issue Innovations, Engineering, Technologies and Best Practices for Ensuring Work Safety in Agriculture)
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