On the use of LoRaWAN for the Internet of Intelligent Vehicles in Smart City scenariosShow others and affiliations
2020 (English)In: Proceedings, Institute of Electrical and Electronics Engineers Inc. , 2020Conference paper, Published paper (Refereed)
Abstract [en]
Automotive world is changing with the introduction of Intelligent Vehicles. Today, an increasing number of vehicles may send data to the Internet, helping car manufacturer to implement the Industry 4.0 paradigm. The collected data during the lifetime of the vehicles can be used to improve both product and production facilities. Moreover, the availability of additional data coming from onboard sensors could be used to obtain information about the environment surrounding the vehicle. The Smart City scenario includes an extraordinary number of new sensors (in urban area) and vehicles can be thought as additional mobile sensors. This paper describes the prototype of a Vehicle-to-Cloud interface with OBD-II (On Board Diagnostic) communication, 3G/4G connectivity, and LoRaWAN [used as backup channel]. LoRaWAN infrastructures are largely diffused in Smart Cities and they can provide a suitable alternative to cover some areas when 3G/4G fails. Last, considering the Smart City scenarios, this paper discusses the application constrains and design directions to achieve a correct integration between LoRaWAN infrastructure and the Internet of Intelligent Vehicles. © 2020 IEEE.
Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers Inc. , 2020.
Keywords [en]
Edge Computing, Internet of Intelligent Vehicles, Low Power WAN, OBD-II, Wireless sensor networks, Automobile manufacture, Intelligent vehicle highway systems, Smart city, Vehicles, Additional datum, Automotive world, Backup channels, Car manufacturers, Number of vehicles, On board diagnostics, On-board sensors, Production facility, 3G mobile communication systems
Identifiers
URN: urn:nbn:se:miun:diva-41516DOI: 10.1109/SAS48726.2020.9220069Scopus ID: 2-s2.0-85095579905ISBN: 9781728148427 (print)OAI: oai:DiVA.org:miun-41516DiVA, id: diva2:1536276
Conference
2020 IEEE Sensors Applications Symposium, SAS 2020
2021-03-102021-03-102021-04-27Bibliographically approved