Publicação
Leveraging generative AI for optimization of a fleet management platform: a user-centric approach
| Resumo: | The rapid evolution of technology has changed the way we live, work, and communicate, opening up an extensive array of new possibilities. From the rise of smartphones to the adoption of cloud computing, the world has become more interconnected, innovative, and data-driven than ever before. In these last few months, with the surge of the now world-renowned ChatGPT, heads turned towards Artificial Intelligence (AI), its potential to optimize products and services and therefore ability to transform various industries. This is where Nexar comes in, the biggest AI-powered dashcam provider in the USA. These are devices attached to vehicles’ windshields capable of collecting and analysing visual data in real time. The 8-year-old organization aims to create a safer and more informed driving experience through the commercialization of those devices and use of the data by them collected. The main focus of this thesis lays on Nexar’s most recent creation, Nexar Fleets. This product is a fleet management tool and was conceived to support fleet managers in monitoring their vehicles’ location and maintenance needs, facilitating their work through the use of data provided by the dashcams. This project is fixed on the study of possible generative artificial intelligence applications to Nexar Fleets. In the first phase of the project, literature on IoT, fleet management and AI is reviewed, in order to provide a good foundation for the following chapters. Product management is also briefly tackled as frameworks on the area were used. Subsequently, the second phase of the project constitutes a comprehensive overview of Nexar and its suite of products, as well as a surface-level approach on the fleet management market. Next up is an analysis on collected data in respect to the importance of certain features in this kind of platforms and further selection of an area to develop the aforementioned product. Finally, the conclusion of this thesis occurs with the creation of a Minimum Viable Product (MVP) designated FleetVitals, from a usability perspective and not necessarily a technical one. This product is accompanied by a financial analysis that seeks to understand a possible adjustment to the current subscription price of Nexar Fleets, considering the incorporation of FleetVitals into the platform and the advantages associated with it. |
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| Autores principais: | Vaz, João Seco Ferreira |
| Assunto: | AI-powered dashcam Generative AI Fleet management Dashcams Inteligência artificial generativa Gestão de frotas |
| Ano: | 2023 |
| País: | Portugal |
| Tipo de documento: | dissertação de mestrado |
| Tipo de acesso: | acesso embargado |
| Instituição associada: | Universidade do Minho |
| Idioma: | inglês |
| Origem: | RepositóriUM - Universidade do Minho |
| Resumo: | The rapid evolution of technology has changed the way we live, work, and communicate, opening up an extensive array of new possibilities. From the rise of smartphones to the adoption of cloud computing, the world has become more interconnected, innovative, and data-driven than ever before. In these last few months, with the surge of the now world-renowned ChatGPT, heads turned towards Artificial Intelligence (AI), its potential to optimize products and services and therefore ability to transform various industries. This is where Nexar comes in, the biggest AI-powered dashcam provider in the USA. These are devices attached to vehicles’ windshields capable of collecting and analysing visual data in real time. The 8-year-old organization aims to create a safer and more informed driving experience through the commercialization of those devices and use of the data by them collected. The main focus of this thesis lays on Nexar’s most recent creation, Nexar Fleets. This product is a fleet management tool and was conceived to support fleet managers in monitoring their vehicles’ location and maintenance needs, facilitating their work through the use of data provided by the dashcams. This project is fixed on the study of possible generative artificial intelligence applications to Nexar Fleets. In the first phase of the project, literature on IoT, fleet management and AI is reviewed, in order to provide a good foundation for the following chapters. Product management is also briefly tackled as frameworks on the area were used. Subsequently, the second phase of the project constitutes a comprehensive overview of Nexar and its suite of products, as well as a surface-level approach on the fleet management market. Next up is an analysis on collected data in respect to the importance of certain features in this kind of platforms and further selection of an area to develop the aforementioned product. Finally, the conclusion of this thesis occurs with the creation of a Minimum Viable Product (MVP) designated FleetVitals, from a usability perspective and not necessarily a technical one. This product is accompanied by a financial analysis that seeks to understand a possible adjustment to the current subscription price of Nexar Fleets, considering the incorporation of FleetVitals into the platform and the advantages associated with it. |
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