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A solution to prevent and minimize the consequences of accidents with farm tractors in the context of mountainous regions with low population density

2023Journal article Open access
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dc.contributor.authorAlves, Rui
dc.contributor.authorMatos, Paulo
dc.date.accessioned2023-12-20T16:39:34Z
dc.date.available2023-12-20T16:39:34Z
dc.date.issued2023
dc.description.abstractFarm tractors have become a key part of daily routine agriculture, converting complex and time-consuming tasks into tasks that are easier to perform and less dependent on human labor, contributing directly to increasing the economic value generated by this activity sector, either by increasing the productivity or by making certain agricultural crops viable, which otherwise would not be sustainable. However, despite all the advantages, accidents with this type of equipment are common, often with critical and sometimes fatal consequences. The evolution of safety requirements of these machines has occurred at a good level; however, a significant part of the agricultural tractors in use are older models that do not have such solutions. Even in the new models, which contain such solutions, these are not always correctly used, and it is even common that they are turned off or simply not used at all. It is therefore natural that accidents continue to occur, a situation that is aggravated by other factors. Lack of situational awareness of the operators, which can result from advanced age, inadequate training, reduced sensitivity/respect for safety rules, or working on irregular terrain like mountainous areas, contribute to high-risk contexts that end in the loss of human life. The consequences of such accidents are clearly aggravated by the time it takes to assist the victims—either because accidents are simply not identified/reported immediately, or by the time it takes to locate and provide help to the victims. This is a scenario that is more common in mountainous regions and regions with low population density. The current paper, using NB-IoT, a set of sensors, and a web application, presents a conceptual toolset conceived to prevent accidents and minimize consequences (human and material) that can be applied to old and new farm tractors. The development was carried out taking the characterization of the farmers and the land in the region in which the authors’ research institution is located into account, which has the highest rate of fatal accidents with agricultural tractors in the country; it is a region of mountainous with a very low population density.pt_PT
dc.description.sponsorshipPolytechnic Institute of Bragança for financial support through funds from POCH-02-53I2- FSE-000004, project TRACE IPB: Knowledge Transfer and Employability IPB. Foundation for Science and Technology (FCT, Portugal) for financial support through national funds FCT/MCTES (PIDDAC) to CeDRI (UIDB/05757/2020 and UIDP/05757/2020) and SusTEC (LA/P/0007/2021).pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationAlves, Rui; Matos, Paulo (2023). A solution to prevent and minimize the consequences of accidents with farm tractors in the context of mountainous regions with low population density. Sensors. ISSN 1424-3210. 23:18, p. 1-17pt_PT
dc.identifier.doi10.3390/s23187811pt_PT
dc.identifier.eissn1424-8220
dc.identifier.issn1424-3210
dc.identifier.urihttp://hdl.handle.net/10198/29008
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherMDPIpt_PT
dc.relationLA/P/0007/2021pt_PT
dc.relationResearch Centre in Digitalization and Intelligent Robotics
dc.relationResearch Centre in Digitalization and Intelligent Robotics
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectIoTpt_PT
dc.subjectMonitoringpt_PT
dc.subjectPreventionpt_PT
dc.subjectFarm tractorpt_PT
dc.subjectLow population density regionspt_PT
dc.titleA solution to prevent and minimize the consequences of accidents with farm tractors in the context of mountainous regions with low population densitypt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.awardTitleResearch Centre in Digitalization and Intelligent Robotics
oaire.awardTitleResearch Centre in Digitalization and Intelligent Robotics
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F05757%2F2020/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDP%2F05757%2F2020/PT
oaire.citation.endPage17pt_PT
oaire.citation.issue18pt_PT
oaire.citation.startPage1pt_PT
oaire.citation.titleSensorspt_PT
oaire.citation.volume23pt_PT
oaire.fundingStream6817 - DCRRNI ID
oaire.fundingStream6817 - DCRRNI ID
person.familyNameAlves
person.familyNameMatos
person.givenNameRui
person.givenNamePaulo
person.identifierR-002-2BA
person.identifier.ciencia-idA716-1D09-38A0
person.identifier.ciencia-idDD15-B2BC-3908
person.identifier.orcid0000-0003-4128-8779
person.identifier.orcid0000-0003-0010-4777
person.identifier.ridI-5726-2018
person.identifier.scopus-author-id57219876713
person.identifier.scopus-author-id57193342842
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
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relation.isAuthorOfPublication1cb6522c-6039-44d0-a14e-70f65930ef92
relation.isAuthorOfPublication.latestForDiscovery1cb6522c-6039-44d0-a14e-70f65930ef92
relation.isProjectOfPublication6e01ddc8-6a82-4131-bca6-84789fa234bd
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