Next Article in Journal
A User Study of a Wearable System to Enhance Bystanders’ Facial Privacy
Previous Article in Journal
Visual and Artistic Effects of an IoT System in Smart Cities: Research Flow
Article

Predictive Maintenance of Bus Fleet by Intelligent Smart Electronic Board Implementing Artificial Intelligence

Dyrecta Lab srl, Research Institute, Via Vescovo Simplicio 45, 70014 Conversano, Italy
*
Author to whom correspondence should be addressed.
IoT 2020, 1(2), 180-197; https://doi.org/10.3390/iot1020012
Received: 9 September 2020 / Revised: 23 September 2020 / Accepted: 29 September 2020 / Published: 1 October 2020
(This article belongs to the Special Issue Edge Computing Optimization Using Artificial Intelligence Methods)
This paper is focused on the design and development of a smart and compact electronic control unit (ECU) for the monitoring of a bus fleet. The ECU system is able to extract all vehicle data by the on-board diagnostics-(ODB)-II and SAE J1939 standards. The integrated system Internet of Things (IoT) system, is interconnected in the cloud by an artificial intelligence engine implementing multilayer perceptron artificial neural network (MLP-ANN) and is able to predict maintenance of each vehicle by classifying the driver behavior. The key performance indicator (KPI) of the driver behavior has been estimated by data mining k-means algorithm. The MLP-ANN model has been tested by means of a dataset found in literature by allowing the correct choice of the calculus parameters. A low means square error (MSE) of the order of 10−3 is checked thus proving the correct use of MLP-ANN. Based on the analysis of the results, are defined methodologies of key performance indicators (KPIs), correlating driver behavior with the engine stress defining the bus maintenance plan criteria. All the results are joined into a cloud platform showing fleet efficiency dashboards. The proposed topic has been developed within the framework of an industry research project collaborating with a company managing bus fleet. View Full-Text
Keywords: ECU; predictive maintenance; artificial neural networks; driver behavior ECU; predictive maintenance; artificial neural networks; driver behavior
Show Figures

Graphical abstract

MDPI and ACS Style

Massaro, A.; Selicato, S.; Galiano, A. Predictive Maintenance of Bus Fleet by Intelligent Smart Electronic Board Implementing Artificial Intelligence. IoT 2020, 1, 180-197. https://doi.org/10.3390/iot1020012

AMA Style

Massaro A, Selicato S, Galiano A. Predictive Maintenance of Bus Fleet by Intelligent Smart Electronic Board Implementing Artificial Intelligence. IoT. 2020; 1(2):180-197. https://doi.org/10.3390/iot1020012

Chicago/Turabian Style

Massaro, Alessandro, Sergio Selicato, and Angelo Galiano. 2020. "Predictive Maintenance of Bus Fleet by Intelligent Smart Electronic Board Implementing Artificial Intelligence" IoT 1, no. 2: 180-197. https://doi.org/10.3390/iot1020012

Find Other Styles

Article Access Map by Country/Region

1
Back to TopTop