Roll/Tip-Over Risk Analysis of Agricultural Self-Propelled Machines Using Airborne LiDAR Data: GIS-Based Approach

Occupational Health and Safety (OHS) in agriculture is a critical concern worldwide, with self-propelled machinery accidents, particularly tip/roll-overs, being a leading cause of injuries and fatalities. In such a context, while great attention has been paid to machinery safety improvement, a major...

Full description

Saved in:
Bibliographic Details
Main Authors: Daniele Puri, Leonardo Vita, Davide Gattamelata, Valerio Tulliani
Format: Article
Language:English
Published: MDPI AG 2025-04-01
Series:Machines
Subjects:
Online Access:https://www.mdpi.com/2075-1702/13/5/377
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1849711004534964224
author Daniele Puri
Leonardo Vita
Davide Gattamelata
Valerio Tulliani
author_facet Daniele Puri
Leonardo Vita
Davide Gattamelata
Valerio Tulliani
author_sort Daniele Puri
collection DOAJ
description Occupational Health and Safety (OHS) in agriculture is a critical concern worldwide, with self-propelled machinery accidents, particularly tip/roll-overs, being a leading cause of injuries and fatalities. In such a context, while great attention has been paid to machinery safety improvement, a major challenge is the lack of studies addressing the analysis of the work environment to provide farmers with precise information on field slope steepness. This information, merged with an awareness of machinery performance, such as tilt angles, can facilitate farmers in making decisions about machinery operations in hilly and mountainous areas. To address this gap, the Italian Compensation Authority (INAIL) launched a research programme to integrate georeferenced slope data with the tilt angle specifications of common self-propelled machinery, following EN ISO 16231-2:2015 standards. This study presents the first results of this research project, which was focused on vineyards in the alpine region of the Autonomous Province of Trento, where terrestrial LiDAR technology was used to analyze slope steepness. The findings aim to provide practical guidelines for safer machinery operation, benefiting farmers, risk assessors, and manufacturers. By enhancing awareness of tip/roll-over risks and promoting informed decision-making, this research aims to contribute to improving OHS in agriculture, particularly in challenging terrains.
format Article
id doaj-art-998fefe9179742c18bf82a032dc09795
institution DOAJ
issn 2075-1702
language English
publishDate 2025-04-01
publisher MDPI AG
record_format Article
series Machines
spelling doaj-art-998fefe9179742c18bf82a032dc097952025-08-20T03:14:43ZengMDPI AGMachines2075-17022025-04-0113537710.3390/machines13050377Roll/Tip-Over Risk Analysis of Agricultural Self-Propelled Machines Using Airborne LiDAR Data: GIS-Based ApproachDaniele Puri0Leonardo Vita1Davide Gattamelata2Valerio Tulliani3National Institute for Insurance Against Accidents at Work (INAIL), Via Fontana Candida 1, Monte Porzio Catone, 00078 Rome, ItalyNational Institute for Insurance Against Accidents at Work (INAIL), Via Fontana Candida 1, Monte Porzio Catone, 00078 Rome, ItalyNational Institute for Insurance Against Accidents at Work (INAIL), Via Fontana Candida 1, Monte Porzio Catone, 00078 Rome, ItalyIndependent Researcher, 00100 Rome, ItalyOccupational Health and Safety (OHS) in agriculture is a critical concern worldwide, with self-propelled machinery accidents, particularly tip/roll-overs, being a leading cause of injuries and fatalities. In such a context, while great attention has been paid to machinery safety improvement, a major challenge is the lack of studies addressing the analysis of the work environment to provide farmers with precise information on field slope steepness. This information, merged with an awareness of machinery performance, such as tilt angles, can facilitate farmers in making decisions about machinery operations in hilly and mountainous areas. To address this gap, the Italian Compensation Authority (INAIL) launched a research programme to integrate georeferenced slope data with the tilt angle specifications of common self-propelled machinery, following EN ISO 16231-2:2015 standards. This study presents the first results of this research project, which was focused on vineyards in the alpine region of the Autonomous Province of Trento, where terrestrial LiDAR technology was used to analyze slope steepness. The findings aim to provide practical guidelines for safer machinery operation, benefiting farmers, risk assessors, and manufacturers. By enhancing awareness of tip/roll-over risks and promoting informed decision-making, this research aims to contribute to improving OHS in agriculture, particularly in challenging terrains.https://www.mdpi.com/2075-1702/13/5/377roll-over/tip-over riskself-propelled machinesstatic stabilitydigital terrain model (DTM)geographic information system (GIS)farmer behaviour
spellingShingle Daniele Puri
Leonardo Vita
Davide Gattamelata
Valerio Tulliani
Roll/Tip-Over Risk Analysis of Agricultural Self-Propelled Machines Using Airborne LiDAR Data: GIS-Based Approach
Machines
roll-over/tip-over risk
self-propelled machines
static stability
digital terrain model (DTM)
geographic information system (GIS)
farmer behaviour
title Roll/Tip-Over Risk Analysis of Agricultural Self-Propelled Machines Using Airborne LiDAR Data: GIS-Based Approach
title_full Roll/Tip-Over Risk Analysis of Agricultural Self-Propelled Machines Using Airborne LiDAR Data: GIS-Based Approach
title_fullStr Roll/Tip-Over Risk Analysis of Agricultural Self-Propelled Machines Using Airborne LiDAR Data: GIS-Based Approach
title_full_unstemmed Roll/Tip-Over Risk Analysis of Agricultural Self-Propelled Machines Using Airborne LiDAR Data: GIS-Based Approach
title_short Roll/Tip-Over Risk Analysis of Agricultural Self-Propelled Machines Using Airborne LiDAR Data: GIS-Based Approach
title_sort roll tip over risk analysis of agricultural self propelled machines using airborne lidar data gis based approach
topic roll-over/tip-over risk
self-propelled machines
static stability
digital terrain model (DTM)
geographic information system (GIS)
farmer behaviour
url https://www.mdpi.com/2075-1702/13/5/377
work_keys_str_mv AT danielepuri rolltipoverriskanalysisofagriculturalselfpropelledmachinesusingairbornelidardatagisbasedapproach
AT leonardovita rolltipoverriskanalysisofagriculturalselfpropelledmachinesusingairbornelidardatagisbasedapproach
AT davidegattamelata rolltipoverriskanalysisofagriculturalselfpropelledmachinesusingairbornelidardatagisbasedapproach
AT valeriotulliani rolltipoverriskanalysisofagriculturalselfpropelledmachinesusingairbornelidardatagisbasedapproach