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dc.contributor.authorIstrefi, Dashmiren_US
dc.contributor.authorZdravevski, Eftimen_US
dc.date.accessioned2022-08-17T08:38:56Z-
dc.date.available2022-08-17T08:38:56Z-
dc.date.issued2020-
dc.identifier.urihttp://hdl.handle.net/20.500.12188/22368-
dc.description.abstractThe 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.en_US
dc.subjectSmart Car, Smart City, IoT, Telematics Hub, Machine Learning, Predictive Maintenanceen_US
dc.titlePredictive Data Analysis and Machine Learning for Telematics Hub based on sensory dataen_US
dc.typeProceedingsen_US
dc.relation.conferenceUBT International Conferenceen_US
item.grantfulltextopen-
item.fulltextWith Fulltext-
crisitem.author.deptFaculty of Computer Science and Engineering-
Appears in Collections:Faculty of Computer Science and Engineering: Conference papers
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