Fleet Management IoT

Author(s)	Shiva Prasad Gupta, Saumya Vatsyayan
Country	India
Abstract	The Internet of Things (IoT) and big data have become popular subjects in recent years. New applications, like predictive maintenance, are possible with all this data being created. For a fleet of public transportation buses, consensus self-organized models approach (COSMO) is an illustration of a predictive maintenance system that aims to identify malfunctioning buses that diverge from the rest of the fleet. The current work suggests an innovative IoT architecture for preventative maintenance and a semi-supervised machine learning method that aims to enhance the COSMO sensor selection process. Fleet maintenance is a crucial exposure to improve availability in fleet management. One such important factor that is taken into account regardless of the actual flaws sets up the need for repair and replacement costs as well as the time associated with them. This is periodic and preventative maintenance. As technology has advanced, IOT and big data have been discussed. With all the data being generated, this system can be used for predictive maintenance. Through better maintenance planning and the elimination of pointless maintenance jobs, IOT-based predictive maintenance can improve fleet availability, stability, and efficiency.
Field	Business Administration
Published In	Volume 5, Issue 3, May-June 2023
Published On	2023-05-14
DOI	https://doi.org/10.36948/ijfmr.2023.v05i03.2977
Short DOI	https://doi.org/gr8p7z

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International Journal For Multidisciplinary Research