2023
Authors
Francisco, M; Ribeiro, F; Metrolho, J; Dionisio, R;
Publication
APPLIED SCIENCES-BASEL
Abstract
Plant diseases and pests significantly influence food production and the productivity and economic profitability of agricultural crops. This has led to great interest in developing technological solutions to enable timely and accurate detection. This systematic review aimed to find studies on the automation of processes to detect, identify and classify diseases and pests in agricultural crops. The goal is to characterize the class of algorithms, models and their characteristics and understand the efficiency of the various approaches and their applicability. The literature search was conducted in two citation databases. The initial search returned 278 studies and, after removing duplicates and applying the inclusion and exclusion criteria, 48 articles were included in the review. As a result, seven research questions were answered that allowed a characterization of the most studied crops, diseases and pests, the datasets used, the algorithms, their inputs and the levels of accuracy that have been achieved in automatic identification and classification of diseases and pests. Some trends that have been most noticed are also highlighted.
2023
Authors
Vuckovic, T; Stefanovic, D; Lalic, DC; Dionisio, R; Oliveira, A; Przulj, D;
Publication
APPLIED SCIENCES-BASEL
Abstract
This study investigated the crucial factors for measuring the success of the information system used in the e-learning process, considering the transformations in the work environment. This study was motivated by the changes caused by COVID-19 witnessed after the shift to fully online learning environments supported by e-learning systems, i.e., learning emphasized with information systems. Empirical research was conducted on a sample comprising teaching staff from two European universities: the University of Novi Sad, Faculty of Technical Sciences in Serbia and the Polytechnic Institute of Castelo Branco in Portugal. By synthesizing knowledge from review of the prior literature, supported by the findings of this study, the authors propose an Extended Information System Success Measurement Model-EISSMM. EISSMM underlines the importance of workforce agility, which includes the factors of proactivity, adaptability, and resistance to change, in the information system performance measurement model. The results of our research provide more extensive evidence and findings for scholars and practitioners that could support measuring information system success primarily in e-learning and other various contextual settings, highlighting the importance of people's responses to work environment changes.
2024
Authors
Amini, MM; Sheikholeslami, DF; Dionísio, R; Heravi, A; Faghihi, M;
Publication
Eurosensors 2023
Abstract
2024
Authors
Santos, O; Ribeiro, F; Metrolho, J; Dionisio, R;
Publication
APPLIED SYSTEM INNOVATION
Abstract
Reducing CO(2 )emissions is currently a key policy in most developed countries. In this article, we evaluate whether smart traffic lights can have a relevant role in reducing CO2 emissions in small cities, considering their specific traffic profiles. The research method is a quantitative modelling approach tested by computational simulation. We propose a novel microscopic traffic simulation framework, designed to simulate realistic vehicle kinematics and driver behaviour, and accurately estimate CO(2 )emissions. We also propose and evaluate a routing algorithm for smart traffic lights, specially designed to optimize CO(2 )emissions at intersections. The simulations reveal that deploying smart traffic lights at a single intersection can reduce CO2 emissions by 32% to 40% in the vicinity of the intersection, depending on the traffic density. The simulations show other advantages for drivers: an increase in average speed of 60% to 101% and a reduction in waiting time of 53% to 95%. These findings can be useful for city-level decision makers who wish to adopt smart technologies to improve traffic flows and reduce CO2 emissions. This work also demonstrates that the simulator can play an important role as a tool to study the impact of smart traffic lights and foster the improvement in smart routing algorithms to reduce CO2 emissions.
2023
Authors
Fabri, V; Stefanovic, M; Pržulj, Ð; Vuckovic, T; Dionisio, R;
Publication
19th International Scientific Conference on Industrial Systems
Abstract
2023
Authors
Spencer, G; Dionísio, R; Neto, L; Torres, PMB; Gonçalves, G;
Publication
2023 6th Experiment@ International Conference (exp.at'23), Évora, Portugal, June 5-7, 2023
Abstract
This paper presents a digital twin demonstrator of a forest harvesters and wood processing machines. The demonstrator is a cyber-physical system that allow the emulation and identification of faults that may occur during regular machine operations. The proposed solution includes a CAN Bus communication between several electronic controller units connected to sensors and actuators. © 2023 IEEE.
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