Please use this identifier to cite or link to this item: http://hdl.handle.net/2067/49525
DC FieldValueLanguage
dc.contributor.authorMonarca, Daniloit
dc.contributor.authorRossi, Pierluigiit
dc.contributor.authorAlemanno, Riccardoit
dc.contributor.authorCossio, Filippoit
dc.contributor.authorNepa, Paoloit
dc.contributor.authorMotroni, Andreait
dc.contributor.authorGabbrielli, Robertoit
dc.contributor.authorPirozzi, Marcoit
dc.contributor.authorConsole, Carlait
dc.contributor.authorCecchini, Massimoit
dc.date.accessioned2023-04-13T08:44:44Z-
dc.date.available2023-04-13T08:44:44Z-
dc.date.issued2022it
dc.identifier.issn2071-1050it
dc.identifier.urihttp://hdl.handle.net/2067/49525-
dc.description.abstractObstacle avoidance is a key aspect for any autonomous vehicles, and their usage in agriculture must overcome additional challenges such as handling interactions with agricultural workers and other tractors in order to avoid severe accidents. The simultaneous presence of autonomous vehicles and workers on foot definitely calls for safer designs, vehicle management systems and major developments in personal protective equipment (PPE). To cope with these present and future challenges, the “SMARTGRID” project described in this paper deploys an integrated wireless safety network infrastructure based on the integration of Bluetooth Low Energy (BLE) devices and passive radio frequency identification (RFID) tags designed to identify obstacles, workers, nearby vehicles and check if the right PPE is in use. With the aim of detecting workers at risk by scanning for passive RFID-integrated into PPE in danger areas, transmitting alerts to workers who wear them, tracking of near-misses and activating emergency stops, a deep analysis of the safety requirements of the obstacle detection system is shown in this study. Test programs have also been carried out on an experimental farm with detection ranging from 8 to 12 meters, proving that the system might represent a good solution for collision avoidance between autonomous vehicles and workers on foot.it
dc.language.isoengit
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.titleAutonomous Vehicles Management in Agriculture with Bluetooth Low Energy (BLE) and Passive Radio Frequency Identification (RFID) for Obstacle Avoidanceit
dc.typearticle*
dc.identifier.doihttps://doi.org/10.3390/su14159393it
dc.identifier.scopus2-s2.0-85137014755it
dc.identifier.isiWOS:000839042400001it
dc.identifier.urlhttps://www.mdpi.com/2071-1050/14/15/9393it
dc.relation.journalSUSTAINABILITYit
dc.relation.article9393it
dc.relation.volume14it
dc.subject.keywordsagriculture; smart farming; work safety; BLE; RFID; remote control; tractorit
dc.description.numberofauthors10it
dc.description.internationalnoit
dc.contributor.countryITAit
dc.type.refereeREF_1it
dc.type.miur262*
item.fulltextWith Fulltext-
item.openairetypearticle-
item.cerifentitytypePublications-
item.grantfulltextrestricted-
item.languageiso639-1en-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
crisitem.journal.journalissn2071-1050-
crisitem.journal.anceE199972-
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