This complete work on innovative practices presents a proposal for a framework applied in an engineering discipline based on hybrid teaching and active methodologies, carefully planned to allow students to contextualize their essential content added to the social impact of their profession. This proposal seeks to guarantee the possibility of assimilating learning between lines and between years of study, guaranteeing connectivity between the teaching teams of the interdisciplinary faculty, between the lines of the curriculum, and between students, inside and outside their formal studies and the classroom. In this way, we provide not only the development of technical skills but also contemplate one of the significant challenges in engineering education, which is the development of socially relevant engineering curricula, thus strengthening the intrinsic motivation and adaptability of the student. In the face of the ongoing transformations in the engineering field - especially considering the rise of Industry 4.0 - professionals in this area must get an inter and trans disciplinary education, in close touch with society and industry needs. This calls for educational practices that stimulate entrepreneur development, dynamical skills, and traditional technical knowledge. In this work, we propose the 4D CV framework based on hybrid teaching and new trends in teaching and learning based on active methodologies, seeking to train a future professional who acts as an active agent in society, capable of facing the challenges of Engineering in the 21st century. We create learning environments that allow for (i) the development of capacity and motivation for teamwork in a technical, multi, and interdisciplinary way; (ii) a creative environment aiming for a comprehensive education along with entrepreneurial spirit and ability to innovate; (iii) reflection and discussion that favor independent critical thinking; (iv) actions that strengthen the university's relationship with the local community allowing closer relation with society and the productive sector. The proposed framework was the subject of a case study applied in the discipline of Curricular Integration Activities IV, of the undergraduate course in Automation Engineering of a Federal University of Brazil, where the technique of the Discourse of the Collective Subject (DCS) to capture the impression of those involved in the study (students, teachers and partner companies). It was possible that the practices of the proposed curriculum project could provide students with inter and multidisciplinarity in their learning process. In addition, students have been motivated in the face of involvement with the needs of society, achieved through practice in an innovative project in which the challenge was based on the real pains/demands/needs of a real startup company, formed by graduates of the course itself, already established in the market. We can thus conclude not only the tremendous innovative potential of our curricular proposal in the face of the significant challenges in engineering education but also its innovative character in approaches to higher education in Brazil.

Demand for ocean-based high-quality and sustainable fish protein soared in the last decade. Unlike precision agriculture, aquaculture remains an under-equipped farming activity. The aquaculture industry has provided remarkable contributions to the Sustainable Development Goal of zero hunger based on providing animal-based protein for human consumption worldwide. The success of the aquaculture industry hinges on appropriate monitoring of key water quality indicators to ensure both animal health and optimal productivity. In this context, the present work presents a cloud-based LoRaWAN system for quasi-real-time tracking of essential water quality parameters by integrating Internet of Things (IoT) sensor devices. The proposed approach harnesses the power of Long Range (LoRa) technology - especially the LoRa Wide Area Network (LoRaWAN) protocol - to facilitate efficient, large-scale monitoring focusing on data security and scalability. With practical insights drawn from IoT system deployment at an industrially relevant aquaculture farm in Brazil, this research provides a comprehensive look into the system's capabilities, drawbacks, and end-user feedback, offering a blueprint for future aquaculture innovations.

This complete work on innovative practices presents a proposal for inserting extension through actions in projects. The current university format in Brazil considers the in-dissociability between teaching, research, and extension. The first two are the most known dimensions, and extension constitutes an interdisciplinary, educational policy, cultural, scientific, and technological process, promoting the transforming interaction between the higher education institutions and society's other sectors, through the knowledge production and application, in permanent joint with research and teaching. In 2014, Brazil's Department of Education instituted the Education National Plan (in Portuguese, “Plano Nacional de Educação” (PNE)), which is still valid until 2023. One of its goals defines that at least 10% of the curricular credits for undergraduate courses must be integrated through extension programs or projects, prioritizing areas of great social relevance. At the same time, since 2019, Education National Conceil has instituted the new National Curricular Guidelines for the Engineering Undergraduate Courses, shifting the focus from the technical content to a new approach considering skills and competencies with the same importance for student education. Within this context, the challenge was to include extension activities, competencies, and skills in the curriculum of three undergraduate courses: Computing Engineering, Automation Engineering, and Information Systems. These courses are in an environment where the project culture is well-established, together with two graduate programs in the field of Computing. Moreover, most of these are research projects, where some activities can be characterized as extension. Also, professors of these courses are involved in specific extension projects. Considering all this context, the innovative practice proposed was to propose a curriculum framework for our undergraduate courses including project activities in the formal curriculum of students, taking place from 10% of traditional classroom training, in a curricular space-time where it is possible to work skills and competencies within real-life problems. In fact, some students experience this project environment but without any curricular formalization. In an empirical analysis of our former students, it is consensual that students who experience projects have a better education than those who only have a traditional classroom environment. The expected result is a curriculum that democratizes all the education spaces in the courses, including components in addition to those already worked in the traditional classroom. Also, it expected the extension as an educational process defined and carried out based on the reality requirements, in a way that university extension be part of the solution to the Brasil social problems.

Studies have been indicating the use of digital resources for interventions with children diagnosed with Autism Spectrum Disorder (ASD), especially when it comes to supporting communication and social interaction. However, there is research that suggests the use of digital environments not only in these aspects but also to assist them in their academic knowledge, such as in their mathematical skills, specifically related to geometric thinking. From this context, Active Methodologies point to various ways of rethinking traditional teaching, one of them being gamification, which can be understood as the use of game elements in non-game situations. Gamification has shown significant benefits for this audience, proving to be an effective tool to aid in the development and learning of these individuals. Therefore, this article in its complete form presents an excerpt from a doctoral thesis that seeks to understand the geometric thinking of nine autistic participants through gamified activities in their real mode. The research is divided into two stages: the first stage involves a preliminary survey with five teachers through structured interviews, aiming to investigate the demand for gamified activities for students with ASD, as well as indicating possibilities for such activities. From the Discursive Textual Analysis (DTA) of these interviews, three categories emerged: opportunities, skills, and limitations. As for the second stage, conducted with nine participants, who are students with ASD, interventions were carried out with these activities in their real mode, which will be implemented digitally later. Through the researcher's observation analysis, based on recorded videos of the interventions, three subcategories related to the initial categories can be identified: potential interactions (opportunities); strategies for geometric thinking (skills); and gamification in the real mode (limitations). The first subcategory emerged due to the need to describe how students with ASD interacted both with the researcher and with the activity. Given the need to showcase how the students solved the activities, as well as the strategies they employed to complete the pairings correctly, the second subcategory emerged. Lastly, the third subcategory arises from limitations that were observed during the interventions, which were still in the real mode and should be taken into account when implementing the digital phase. Therefore, it is evident that there are some points to consider for the activity in its digital mode: implementing gamified activities that incorporate elements from the participants' daily lives (ADLs); understanding the strategies employed by the participants to solve gamified activities; being mindful of the weaknesses of the gamified activity in its real mode, allowing for the provision of resources in various formats.

Fisheries and aquaculture industries notably contribute to animal-source protein production worldwide. Climate change is creating environmental conditions suitable for harmful algal blooms (HAB) on a global scale. Some phytoplankton species can also release toxins, which may cause large-scale marine mortality with knock-on effects on coastal economies. Reliable phytoplankton monitoring and early HAB detection are also essential in climate-resilient solutions for aquaculture applications. Currently, phytoplankton monitoring is primarily based on traditional microscopy. However, it is time-consuming and requires an experienced taxonomist. There is a need to expedite and automate phytoplankton monitoring to support aquaculture industries. Analytical instruments based on microscopy coupled with artificial intelligence (AI) models may be vital to monitoring applications. Digital plankton data sets are usually imbalanced and reflect natural environmental differences. The lack of data to represent minority species/genera prevents AI models from understanding some taxa completely. It compromises system reliability for HAB monitoring applications. The present study investigates state-of-the-art models for class imbalance problems tailored for HAB monitoring within multi-trophic aquaculture farms from Brazil, South Africa, and Scotland. A unified benchmark database covering publicly available microscopic image-based datasets supported phytoplankton modelling. AI deep collaborative models and threshold moving techniques provided the best results compared to standard architectures. It prevailed, especially for low-abundant yet toxic organisms.

Rehabilitation of upper limb movements in patients with hemiparesis has been a longstanding struggle for physical therapy professionals. Tools such as robotically assisted therapies have shown great potential to assist in the rehabilitation process of patients. Regarding traditional rehabilitation interventions, robotic systems can provide more effective and intensive physical therapy as new interventions are now being used to assist in the rehabilitation of patients with certain movement restrictions especially after stroke. Currently, this research work aims to present a study on the trajectory planning of a robotic arm, which will be suggested to the patient in order to perform the movement for rehabilitation. Furthermore, it is intended that the trajectory can be generated in real time to better meet the patient’s movement requirements and restrictions. In view of the need for real-time trajectory generation, it is necessary that a simple model of the manipulator work area is used as a boundary and boundary condition for the task space. In parallel, there is the development of a prototype of the REHABOT robot, a mechanical project developed with components from the Cyton Gamma 1500 and Reachy robots.

Robot-assisted upper limb rehabilitation techniques are advanced rapidly in recent decades. Its diverse interactive strategies allow the personalization of the treatment, through a specialist, for each patient. Thus, the use of assistive robotics provides the individual with rehabilitation and restoration of motor functions, if not totally, at least in part, which directly impacts their quality of life. One of the existing aspects in rehabilitation is game therapy, the therapy based on games and challenges, this brings greater involvement and entertainment for the patient. Through information on limb position or muscle activity of the patient, the game performs a dynamic operation based on information from the sensors. Muscle movements and activations that were previously involuntary on a daily basis in therapy become intentional for the treatment and evaluation of the patient. In this work, an auxiliary system for the treatment, recovery and strengthening of muscle and physiotherapy is developed through surface electromyography data and inertial sensors.

Assistive Robotics has been shown to be an important tool in the patient rehabilitation process. One of the first steps in this process is to capture the movements performed by the patient to analyze the movement restrictions presented. The present work presents a brief review of the state of the art as well as the development of a Range of Motion (ROM) measurement system based on the position of the joints in the three-dimensional space of the upper limbs using the Kinect sensor. In addition, preliminary tests to capture compensatory movements of the trunk are presented aiming to investigate the feasibility of using such system as a tool for detecting compensatory movements.

The production of food for all the population in the world became the biggest concern. The population continues to grow and the number of farmable lands has been decreasing. To make the lands more productive, fertilizers are used on a larger scale. To guarantee the quality of the product, particle size analysis are made by mechanical sieving. With the time, the wear-out of the sieving in the fertilizer industry the results of the particle size analysis will be erroneous. So the computer vision appears as an alternative that is non-invasive and less time-consuming. In this context, this paper has the objective to develop a grain surface simulator capable of generating virtual images with overlapping grains, since there is a difficulty to obtain annotated data of images of fertilizers. In order to validate the proposed simulator using a DIP algorithm, noises are added in the virtual images to compare with the reality in the industry, to show how well the particle size analysis with computer vision were handled towards adversities. The results of the overlapping analysis show that when the virtual image has a fewer number of grains, the DIP algorithm can identify the majority of grains, consequently with less error in the particle size analysis. Different noises, at different intensities, have their effects analyzed on the algorithm. As the analyzes in this study match with the reality showing the consequences, tendencies, and errors of the overlapping of grains and noises in the images, the simulator developed here matches with reality and is extremely useful to facilitate the study of complex cases of application of visual computing and digital image processing in particle size analysis of fertilizers.

Aquaculture has resorted to the use of technology to make control of important variables and improve production. There were two problems observed in the Marine Aquaculture Station — EMA of the Federal University of Rio Grande, more specifically related to the aeration of the culture tanks to pisciculture and carniciculture. Firstly, the high energy consumption of the paddle aerators was identified, due to the continuous need to oxygenate the water. Subsequently, it was noted that static aerators do not aerate the water evenly and they require that their placement be done manually by technicians or assistants. Thus, the article proposes a design of an autonomous aerator with electric power coming from a photovoltaic solar energy system. In the sequence, a navigation system for the aerator is proposed along the tank, based on a differential performance of the motors connected to the paddle.

The need for convergence between technology and shipbuilding processes is identified in the Brazilian shipbuilding industry so that it has a greater competitiveness against the shipyards belonging to the Tiger Cub Economies. In this perspective, wireless sensor networks and identification technologies have gained space regarding industrial solutions. This paper proposes an Internet of Things (IoT) based architecture using RFID and GPS for identification and tracking of blocks in shipyards. A hardware architecture is presented with the objective of identifying, mapping and tracking blocks and consequently the vehicles used in their transport, in a shipyard and offshore.

The robotic welding processes have been highly widespread in manufacturing industries due to large-scale production. An area where these processes are widely applied are shipyards, where there are necessary hundreds to thousands of kilograms of weld by hour. However, systems that operate in open-air environments are vulnerable to sundry disturbances, noises in measures, as well as possible unavailability of measurement of some system states, required for the controller. Taking it into account, in this work, a Robust Model Reference Adaptive Control is proposed to regulate the velocity of a nonlinear motor of a linear welding robot. Furthermore, an Extended Kalman Filter is implemented to estimate the system states and attenuate measurement noises. The proposed control system demonstrated a very good performance with fast convergence and small error.

Welding is an important operation in manufacturing processes and it can represent a highly relevant amount of production costs, depending on material workpieces and required weld quantity. In mechanised and robotised welding processes, robot's travel velocity is an important parameter, which requires a proper regulation to obtain a good quality for weld beam. Then, in this work, a nonlinear model of a robot motor with their identified parameters is presented and a sliding mode control is proposed to regulate robot velocity. Furthermore, an Unscented Kalman Filter and a Cubature Kalman Filter are implemented, separately, for output system estimation. The control system with both estimators presented satisfactory tracking performances, in simulations, converging fast and with very small chattering.

This paper presents two problems observed in the Marine Aquaculture Station - EMA of the Federal University of Rio Grande, more specifically related to the aeration of the culture tanks to pisciculture and/or carniciculture. Firstly, the high energy consumption of the paddle aerators was identified, due to the continuous need to oxygenate the water. Subsequently, it was noted that static aerators do not aerate the water evenly and they require that their placement be done manually by technicians or assistants. Thus, initially, the article proposes a design of an autonomous aerator with electric power coming from a photovoltaic solar energy system. In the sequence, a navigation system for the aerator is proposed along the tank, based on a differential performance of the motors connected to the paddle.

Pipelines have been used to convey products such as oil, gas, chemicals and water. It means that problems with pipelines would indicate money waste and environment damages. To avoid those problems, inspections are realised periodically. The technology improvement has made possible employing robots and mobile platforms to inspect pipes. The focus of this work is to implement a strategy to acquire the pose of robot or platform inside pipe. The method consists in the use of a technique to fuse information from a low cost IMU and encoder. Simulations are realised using Matlab software.

There are many types of transportation of fluids such as a truck, train and ship. However, it is not suitable and economic practical. The employment of truck vehicles increase problems with traffic and pollution. The transport of train requires high maintenance of structures responsible for training moves. The ship conveys can be used just where there is sea or lagoon. The most method used to convey fluids is pipeline. However, aging, corrosion, mechanical damage and cracks in pipes, depending on which product is been transported, can be hazardous to the environment or monetary loss. One of the solutions to this problem is to realise maintenance of pipelines. To reduce time of maintenance, it is realised inspection before maintenance. However, there are inaccessible structures of pipes, size extreme temperature that makes dangerous realise manual inspection. The development of embedded system and field of instrumentation makes possible the employment of robotics for the execution of inspection tasks. The principal objective of this work is to realise a review about robots inspection, expound differences between robots considering application, adaptability, locomotion, sensors inspection and odometers.

In this paper we present the application of the nonlinear model based predictive control to the motion control of an underactuated brachiation robot. The robot has 3 links and only one joint, the second one, is actuated. The aim of this work is to develop a control input sequence that moves continuously forward the robot over an horizontal line. We investigate the use of MPC to control the underactuated brachiation robot due to its advantages, mainly the construction of an optimal stabilizing control law and due to its ability to consider in a direct way the constraints into the optimization problem. We present computational simulations with their respective results and we highlight some important considerations.