Research Article
Experimental analysis of intelligent vehicle monitoring system using Internet of Things (IoT)
@ARTICLE{10.4108/eai.16-4-2021.169336, author={T. Thamaraimanalan and M. Mohankumar and S. Dhanasekaran and H. Anandakumar}, title={Experimental analysis of intelligent vehicle monitoring system using Internet of Things (IoT)}, journal={EAI Endorsed Transactions on Energy Web}, volume={8}, number={36}, publisher={EAI}, journal_a={EW}, year={2021}, month={4}, keywords={Data acquisition, Internet of Things (IoT), Vehicle monitoring system}, doi={10.4108/eai.16-4-2021.169336} }
- T. Thamaraimanalan
M. Mohankumar
S. Dhanasekaran
H. Anandakumar
Year: 2021
Experimental analysis of intelligent vehicle monitoring system using Internet of Things (IoT)
EW
EAI
DOI: 10.4108/eai.16-4-2021.169336
Abstract
Internet of things is an emerging trend and Wireless sensor networks are embedded with IoT to measure various parameters of a vehicle. Measurements and standards of measurements are the most important stages for measuring an object’s size, length, weight etc., Measuring the weight of small objects does not need much time and efforts, but on the other hand weighing large objects needs lots of time and efforts. A new approach is proposed to monitor the location of the vehicle, engine temperature, tyre pressure, oil level, speed control and load measurement of a vehicle. Even if the device is offline, the logs will be stored in the memory card and it can be used for future analysis. In addition to this theft control is introduced for the security of the vehicle. CC3200 microcontroller is connected with load cell to monitor the total weight of the vehicle and engine temperature is monitored using the temperature sensor. By GPS the location and speed of the vehicle is monitored periodically and the location is uploaded in the cloud environment. Vehicle monitoring with load calculation, anti-theft control and the data acquisition from various sensors incorporated with the Electronic Control Unit (ECU) is collected and processed in the cloud. The proposed framework is effectively adaptable at low cost.
Copyright © 2021 T.Thamaraimanalan et al., licensed to EAI . This is an open-access article distributed under the terms of the Creative Commons Attribution license, which permits unlimited use, distribution, and reproduction in any medium so long as the original work is properly cited.