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Open AccessFeature PaperArticle

WSN Hardware for Automotive Applications: Preliminary Results for the Case of Public Transportation

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Department of Electrical and Electronic Engineering, University of Cagliari, 09123 Cagliari, Italy
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Department of Electrical, Electronic, Telecommunications Engineering, and Naval Architecture, University of Genoa, 16145 Genoa, Italy
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CTM S.p.A., V.le Trieste 159/3, 09123 Cagliari, Italy
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National Institute for Astrophysics, Cagliari Astronomical Observatory, Via della Scienza 5, 09047 Selargius, Italy
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Author to whom correspondence should be addressed.
Electronics 2019, 8(12), 1483; https://doi.org/10.3390/electronics8121483
Received: 30 September 2019 / Revised: 28 November 2019 / Accepted: 2 December 2019 / Published: 4 December 2019
(This article belongs to the Special Issue Application of Wireless Sensor Networks in Monitoring)
The ubiquitous nature and great potential of Wireless Sensors Network has not yet been fully exploited in automotive applications. This work deals with the choice of the cost-effective hardware required to face the challenges and issues proposed by the new trend in the development of intelligent transportation systems. With this aim, a preliminary WSN architecture is proposed. Several commercially available open-source platforms are compared and the Raspberry Pi stood out as a suitable and viable solution. The sensing layer is designed with two goals. Firstly, accelerometric, temperature, and relative humidity sensors were integrated on a dedicated PCB to test if mechanical or environmental stresses during bus rides could be harmful to the device or to its performances. The physical quantities are monitored automatically to alert the driver, thus improving the quality of service. Then, the rationale and functioning of the management and service layer is presented. The proposed cost-effective WSN node was employed and tested to transmit messages and videos, while investigating if any quantitative relationship exists between these operations and the environmental and operative conditions experienced by the hardware.
Keywords: automotive; intelligent transportation systems; WSN automotive; intelligent transportation systems; WSN
MDPI and ACS Style

Baire, M.; Melis, A.; Lodi, M.B.; Dachena, C.; Fanti, A.; Farris, S.; Pisanu, T.; Mazzarella, G. WSN Hardware for Automotive Applications: Preliminary Results for the Case of Public Transportation. Electronics 2019, 8, 1483.

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