Artigos
URI permanente para esta coleçãohttps://repositorio.fei.edu.br/handle/FEI/796
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- Development of a Digital Twin for smart farming: Irrigation management system for water saving(2023-02-15) ALVES, R. G.; MAIA, R. F.; Fabio Lima© 2023 Elsevier LtdWorld agriculture faces the challenge of increasing its agricultural production by 50 % from 2012 to 2050, while reducing water consumption, as agriculture accounts for 69 % of all fresh water used on the planet. The use of technologies such as the internet of things, artificial intelligence, digital twins, among others, in the agricultural environment is increasing. Digital twin applied to agriculture is in its early stages of development. A digital twin is one in which data flows automatically and in both directions between a physical object and a virtual object. Withing this context, this paper presents a digital twin of a smart irrigation system in an application scenario. A digital twin for an irrigation system is one in which the physical components of the system, such as its sensors and actuators, are connected with their virtual representations. The system is composed of a FIWARE-based internet of things platform and a discrete event simulation model in Siemens Plant Simulation software. The internet of things platform is used to collect, aggregate and process soil, weather and crop data to calculate daily irrigation prescriptions. The simulation model is used to simulate the behavior of an irrigation system defined in an application scenario. The communication between the platform and the simulation model happens in real-time and is intermediate by an OPC UA server. A application scenario is considered to evaluate the behavior of the system and to evaluate, in future research, different irrigation strategies. The benefits of the systems proposed are twofold. First, evaluate the behavior of the Internet of Things (IoT) platform and an irrigation system before implementing both in the field. Second, enable the evaluation of different irrigation strategies in parallel with current farm practices. Within the system proposed, farmers can evaluate the behavior of the system before implementing in their farms and allowing the system to operate automatically. It is possible to infer that the system can improve farm operations and reduce water usage by allowing farmers to gather soil, weather and crop information and evaluate multiple irrigation strategies.
- Estimation of Energy Consumption in Manufacturing Lines Using Machine Learning into Industry 4.0 Context(2022-01-05) Fabio Lima; NONOGAKI, L. K. B. Y.; CHANG, J.; Alexandre Augusto Massote© 2022 PICMET.This paper deals with the simulation of production lines focusing on opportunities of reducing the energy consumption. The simulation of systems is one of the pillars of the so-called Industry 4.0. It has been used a digital manufacturing software, which allow the creation of digital twins, to carry out the models. Once the model has been created and validated, a machine learning approach, more specifically a Neural Network was trained to estimate the energy consumption of the line. The estimation of the energy consumption allows to use this variable to take decisions of the production scheduling. Moreover, the neural network package is embedded into the digital manufacturing software which provides more flexibility to solve the problem using one single software tool. The results validate the proposal, and, for future work, the effective creation of the digital twin should be performed.
- Innovative laboratory model based on partnerships and active learning(2017-12-12) Rodrigo Maia; Alexandre Augusto Massote; Fabio Lima© 2017 IEEE.The advent of the internet of things and industry 4.0 bring new paradigms that tend to affect the way of organizing several human activities, among them the production processes that are ruled by production and human work on a large scale in the production lines. Therefore, it is inevitable to think of how to prepare students for this new, oncoming reality, since these students will have to deal with a society where usual jobs will no longer be available. This paper presents the initiative of two laboratories developed to prepare students in engineering and computer science to deal with the Internet of Things (IOT) and industry 4.0 (I4.0) subjects. These laboratories were developed in partnership with companies: the first one of Digital Manufacturing (DM) and the second one of IOT, and the integrated work of these laboratories approaches with the students the concepts of I4.0 or advanced manufacturing. The collaborative environment between academia and companies, as well as the joint work of two laboratories, allowed graduate students to develop discussions and works that integrate issues of society and companies with academic studies.