Big data e suas vantagens no ramo de monitoramento de veículos

Abstract

This research has as subject-matter the advantages that technology can provide for a specific line of business. Thus, the purpose of this research is how an analysis of the data collected by Internet of Things (IoT) devices can contribute to road transport companies. For this reason it was structured a theoretical reference to the topics of Internet of Things (IoT), data analysis and Big Data, and the current technology in the vehicle monitoring companies, to know in depth, which are the authors on these subjects and what this literature recommends. Following was made a qualitative case study of a company in the vehicle tracking sector named as Car Monitor, fictitious name to ensure the integrity and fidelity of the brand, because it is an academic work. In this case study, we collected data from Vehicle Tracking and Telemetry systems, and secondary data from documents, manuals and technical procedures. In the analysis of the data were constructed tables and graphs aiming to exemplify how the collection of information about the vehicles can be analyzed and provide insights, for example, to obtain the vehicles and drivers that most consume fuel in the fleet; identify drivers who do not make the adequate rest period on their journey; create smarter routes by aggregating information from fuel stations with better prices; optimize fleet management, avoiding idle vehicles; anticipate problems or maintenance of vehicles by analyzing driver behavior. It is concluded that an analysis of data collected through devices and Internet of Things (IoT) sensors stored in a large volume of data conceptualized as Big Data can add competitive value to vehicle monitoring organizations by reducing vehicle fleet costs, and even impacting the environment with a reduction in the emission of gases promoting environmental sustainability of the companies and economical with the reduction of costs and technology. As limitations of the research, the restricted volume of data provided by the company, mainly customer-related data and quantity of data sources, so that future research is suggested as comparing other data sources, differentiating fleet types and aggregating new data on this subject.