Browsing by Author "Santos, Leonardo Leite Meira dos"
Now showing 1 - 2 of 2
Results Per Page
Sort Options
- Data lake for aggregation of production data and visualization tools in the stamping industryPublication . Santos, Leonardo Leite Meira dos; Alves, Paulo; Marques, KeciaIn this master’s dissertation, the main objective is to develop a system for monitoring industrial sensors, specifically for the stamping industry. The work is motivated by the need for real-time monitoring systems to track machine operation in production, thus enabling data-driven management. The system was implemented using Python on the backend with FastAPI for the API, MongoDB for data storage, and NextJs for the dashboard where the information is displayed. The results indicate that the system is capable of monitoring, analyzing, and presenting sensor data in real-time, with an alert mechanism that triggers notifications based on predefined parameters. The state of the art was reviewed to better understand emerging techniques and technologies in related areas, such as industrial Internet of Things (IoT), big data, and real-time data analysis. The current implementation, although simpler compared to the solutions found in the literature, served as a valid proof of concept and is highly adaptable for future iterations based on feedback from the real production environment. It is concluded that the developed system meets the initial requirements and offers a certain degree of flexibility to adapt to other contexts and make future enhancements. The application of Artificial Intelligence (AI) for data analysis and predictive maintenance of machines are likely directions for research and development of future work.
- Meta social mediaPublication . Lima, Carlos; Santos, Leonardo Leite Meira dos; Matos, PauloThis research project aims to explore the concept of social meta-network, as a way of integrating social networks, such as Facebook, LinkedIn and others, providing an integrated perspective and transversal functionalities of added value for its users. The present approach uses graph databases, implemented using Neo4j. The nodes/vertices of the graph are used to represent people; properties on nodes are used to represent personal information of each individual; the relationships/edges represent directional relationships between individuals according to each social network; and the properties about relationships serve to maintain information about the relationship between individuals for each social network. The model created intends to be mixed solution focused on relationships by type of social network, referring details to the information existing in the native network itself. Native networks are seen as distinct dimensions in which the present solution makes it possible to relate information between these dimensions, even when there are no relationships between the networks/user in question. It also allows for a more complete perspective of each individual, integrating the professional, playful and other more specialized aspects, which leads to results that are much higher than what can be achieved by looking individually to each network - whether for problems/challenges of centrality/influence, identification and characterization of communities, identification of similarities, identification of potential relationships, among many other approaches. In practical terms, a huge asset for marketing purposes.