Autonomous Vehicles Management in Agriculture with Bluetooth Low Energy (BLE) and Passive Radio Frequency Identification (RFID) for Obstacle Avoidance

Danilo Monarca, Pierluigi Rossi, Riccardo Alemanno, Filippo Cossio, Paolo Nepa, Andrea Motroni, Roberto Gabbrielli, Marco Pirozzi, Carla Console and Massimo Cecchini
Additional contact information
Danilo Monarca: Department of Agriculture and Forest Sciences (DAFNE), Tuscia University, 01100 Viterbo, Italy
Pierluigi Rossi: Department of Agriculture and Forest Sciences (DAFNE), Tuscia University, 01100 Viterbo, Italy
Riccardo Alemanno: Department of Agriculture and Forest Sciences (DAFNE), Tuscia University, 01100 Viterbo, Italy
Filippo Cossio: Department of Agriculture and Forest Sciences (DAFNE), Tuscia University, 01100 Viterbo, Italy
Paolo Nepa: Department of Information Engineering, University of Pisa, 56122 Pisa, Italy
Andrea Motroni: Department of Information Engineering, University of Pisa, 56122 Pisa, Italy
Roberto Gabbrielli: Department of Civil and Industrial Engineering, University of Pisa, 56122 Pisa, Italy
Marco Pirozzi: National Institute for Insurance against Accidents at Work (INAIL), 4th Laboratory Division—Process and Production Plant Safety, 00143 Rome, Italy
Carla Console: National Institute for Insurance against Accidents at Work (INAIL), 4th Laboratory Division—Process and Production Plant Safety, 00143 Rome, Italy
Massimo Cecchini: Department of Agriculture and Forest Sciences (DAFNE), Tuscia University, 01100 Viterbo, Italy

Sustainability, 2022, vol. 14, issue 15, 1-13

Abstract: Obstacle 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.

Keywords: agriculture; smart farming; work safety; BLE; RFID; remote control; tractor (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2071-1050/14/15/9393/pdf (application/pdf)
https://www.mdpi.com/2071-1050/14/15/9393/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:14:y:2022:i:15:p:9393-:d:877455

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().