IOT connected predictive vehicle systems
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2018-04-20 https://doi.org/10.14419/ijet.v7i2.21.12449 -
Internet of things, connected cars, predictive maintenance, MQTT, eclipse mosquito, spring tool suite, Smart City. -
Abstract
Predictive maintenance is to identify vehicle maintenance issues before they occur. By leveraging data from navigation locator and motion of vehicle, status and parts of the vehicle, requirement of service, warranty repairs with current vehicle sensor data would be difficult for a human to discover. Predictive data analytics can find meaningful correlations via Connected Vehicle which is a technological advancement in Automobile industry. Using Internet of Things IOT, various information like health information of a driving person and navigation of vehicle can be easily monitored. Connected vehicle deals with cars and other vehicles where we the data will be shared with the backed applications like micro services.
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References
[1] SAP/iot-starter kit. GitHub based on Raspberry Pi – Teach, Learn, and Make with Raspberry Pi.
[2] The simplest way to experience IoT in the HANA Cloud Platform– Part 1 by Jeff Durnwald based on Simple link SensorTag – TI.com
[3] Measure the Sun with Hana Cloud Platform – Hands On Tutorial – 2.0 by Marcus Conrad Behrens based on Electric Imp
[4] RaspberryPi on SAP HANA Cloud Platform by Rui Nogueira base on Raspberry Pi – Teach, Learn, and Make with Raspberry Pi
[5] Hand’s-On Video Tutorials for Internet of Things (IoT) Services by Philip MUGGLESTONE based on Simple link SensorTag – TI.com
[6] SAP HANA IoT Part 1: Introduction to Arduino, Raspberry Pi and why we have selected them by Ajay Nayak.
[7] Particle Photon or Core on HCP – IoT by A. Kamhoot based on Particle (formerly Spark) | Prototyping tools for the Internet of Things.
[8] Connecting mobile devices with IFTTT and Zapier to SAP HCP IoT Service by Weber based on IFTTT.
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Downloads
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How to Cite
., M., Sheela Gowr, P., Latha, M., & V. Anbazhagu, U. (2018). IOT connected predictive vehicle systems. International Journal of Engineering & Technology, 7(2.21), 391-393. https://doi.org/10.14419/ijet.v7i2.21.12449Received date: 2018-05-04
Accepted date: 2018-05-04
Published date: 2018-04-20