Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.12188/22368
Title: Predictive Data Analysis and Machine Learning for Telematics Hub based on sensory data
Authors: Istrefi, Dashmir
Zdravevski, Eftim 
Keywords: Smart Car, Smart City, IoT, Telematics Hub, Machine Learning, Predictive Maintenance
Issue Date: 2020
Conference: UBT International Conference
Abstract: The Internet of things (IoT) paradigm that enables devices to communicate via the Internet, is being adopted in various areas, including smart homes and smart cities. ’Connected Car’ is a new term often associated with cars and other passenger vehicles, capable of internet connectivity and sharing various kinds of data with other systems. This paper evaluates the feasibility and technology readiness for this technology to be adopted in the automotive industry. We evaluate different fleet management systems that are currently considered as a state-ofthe-art from a scientific point of view. Likewise, we consider commercial platforms and sensory-enabled solutions that streamline the day-to-day operations of different companies.
URI: http://hdl.handle.net/20.500.12188/22368
Appears in Collections:Faculty of Computer Science and Engineering: Conference papers

Show full item record

Page view(s)

52
checked on May 2, 2024

Download(s)

36
checked on May 2, 2024

Google ScholarTM

Check


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.