2022
Authors
Tinoco, V; Silva, MF; Santos, FN; Valente, A; Rocha, LF; Magalhaes, SA; Santos, LC;
Publication
INDUSTRIAL ROBOT-THE INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH AND APPLICATION
Abstract
Purpose The motivation for robotics research in the agricultural field has sparked in consequence of the increasing world population and decreasing agricultural labor availability. This paper aims to analyze the state of the art of pruning and harvesting manipulators used in agriculture. Design/methodology/approach A research was performed on papers that corresponded to specific keywords. Ten papers were selected based on a set of attributes that made them adequate for review. Findings The pruning manipulators were used in two different scenarios: grapevines and apple trees. These manipulators showed that a light-controlled environment could reduce visual errors and that prismatic joints on the manipulator are advantageous to obtain a higher reach. The harvesting manipulators were used for three types of fruits: strawberries, tomatoes and apples. These manipulators revealed that different kinematic configurations are required for different kinds of end-effectors, as some of these tools only require movement in the horizontal axis and others are required to reach the target with a broad range of orientations. Originality/value This work serves to reduce the gap in the literature regarding agricultural manipulators and will support new developments of novel solutions related to agricultural robotic grasping and manipulation.
2022
Authors
Chella, AA; Lima, J; Goncalves, J; Fernandes, FP; Pacheco, MF; Monteiro, FC; Valente, A;
Publication
CONTROLO 2022
Abstract
The proposed work was developed as part of the SmartHealth project, which aims to advance upper body rehabilitation by granting a robotic alternative to reduce the limitations of physical therapy while conferring more intensive and personalized therapy sessions for patients. The use of robots permits therapists to be relieved of laborious and repetitive tasks while supplying feedback for patients and physiotherapists through automatic recordings. The proposed strategy is to develop new python-based software that controls the robot, collects the patient's forces and muscle activity in real-time, and stores them for future analysis while providing visual feedback, thus allowing session optimization. These features permit the physiotherapist to objectively perceive the patient's performance during exercise. This solution is implemented in robots already commercialized in the industrial field. These kinds of robots are generally mass-produced in production lines at a relatively low cost and with great flexibility.
2022
Authors
Valente, A; Costa, C; Pereira, L; Soares, B; Lima, J; Soares, S;
Publication
AGRICULTURE-BASEL
Abstract
In view of the actual climate change scenario felt across the globe, resource management is crucial, especially with regard to water. In this sense, continuous monitoring of plant water status is essential to optimise not only crop management but also water resources. Currently, monitoring of vine water status is done through expensive and time-consuming methods that do not allow continuous monitoring, which is especially inconvenient in places with difficult access. The aim of the developed work was to install three groups of sensors (Environmental, Plant and Soil) in a vineyard and connect them through LoRaWAN protocol for data transmission. The results demonstrate that the implemented system is capable of continuous data communication without data loss. The reduced cost and superior range of LoRaWAN compared to WiFi or Bluetooth is especially important for applications in remote areas where cellular networks have little coverage. Altogether, this methodology provides a remote, continuous and more effective method to monitor plant water status and is capable of supporting producers in more efficient management of their farms and water resources.
2022
Authors
Kalbermatter, RB; Brito, T; Braun, J; Pereira, AI; Ferreira, AP; Valente, A; Lima, J;
Publication
OPTIMIZATION, LEARNING ALGORITHMS AND APPLICATIONS, OL2A 2022
Abstract
Life in society has initiated a search for comfort and security in social centers. This search generated revolutions within the knowledge about the technologies involved, making the environments automated and integrated. Along with this increase, ecological concerns have also arisen, which have been involved since the design of intelligent buildings, remaining through the years of their use. Based on these two pillars, the present study aims to monitor three central systems inside the apartments of the Apolo Building (Braganca city, Portugal). The electrical energy consumption, water flow, and waste disposal systems are integrated through a single database. The data is sent remotely via WiFi through the microcontroller. For better visualization and analytics of the data, a web application is also developed, which allows for real-time monitoring. The obtained results demonstrate to the consumer his behavior regarding household expenses. The idea of showing the consumer their expenditure is to create an ecological awareness. Through the data collected and the environmental alternatives found, it is possible to observe whether there was a behavior change when receiving this data, either in the short or long term.
2025
Authors
Matos, C; Teixeira, R; Baptista, J; Valente, A; Briga-Sá, A;
Publication
Lecture Notes in Civil Engineering - Construction, Energy, Environment and Sustainability
Abstract
2025
Authors
Ferreira, L; Salgado, P; Valente, A;
Publication
COMPUTATIONAL SCIENCE AND COMPUTATIONAL INTELLIGENCE, CSCI 2024, PT V
Abstract
This paper addresses the persistent rise in motorcycle-related fatalities, even as overall road deaths decline, by introducing an adaptive Fuzzy System based on the Takagi-Sugeno model. The system evaluates parameters such as acceleration and lean angle to classify rider behavior into categories such as normal, aggressive, or dangerous, providing timely feedback aimed at promoting safer driving practices. A key component of this approach is the Local Outlier Factor (LOF) algorithm, which identifies hazardous behaviors by quantifying deviations from standard riding patterns, thereby allowing the establishment of adaptive safety thresholds. By integrating fuzzy logic, the system offers refined decision-making capabilities in complex riding conditions, enhancing active safety systems such as traction and braking controls. This work emphasizes the critical role of behavior-based insights in mitigating accidents, particularly since rider actions are a major contributing factor to motorcycle incidents.
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