ESTCB - Artigos em revistas com arbitragem científica
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- Using drones to estimate and reduce the risk of wildfire propagation in wildland–urban interfacesPublication . Santos, Osvaldo; Santos, NatérciaForest fires have become one of the most destructive natural disasters worldwide, causing catastrophic losses, sometimes with the loss of lives. Therefore, some countries have created legislation to enforce mandatory fuel management within buffer zones in the vicinity of buildings and roads. The purpose of this study is to investigate whether inexpensive off-the-shelf drones equipped with standard RGB cameras could be used to detect the excess of trees and vegetation within those buffer zones. The methodology used in this study was the development and evaluation of a complete system, which uses AI to detect the contours of buildings and the services provided by the CHAMELEON bundles to detect trees and vegetation within buffer zones. The developed AI model is effective at detecting the building contours, with a mAP50 of 0.888. The article analyses the results obtained from two use cases: a road surrounded by dense forest and an isolated building with dense vegetation nearby. The main conclusion of this study is that off-the-shelf drones equipped with standard RGB cameras can be effective at detecting non-compliant vegetation and trees within buffer zones. This can be used to manage biomass within buffer zones, thus helping to reduce the risk of wildfire propagation in wildland–urban interfaces.
- ROBIN: Reference observatory of basins for international hydrological climate change detectionPublication . Turner, S.; Hannaford, J.; Barker, L. J.; Suman, G.; Killeen, A.; Armitage, R.; Chan, W.; et al.; Albuquerque, M.T.D.Human-induced warming is modifying the water cycle. Adaptation to posed threats requires an understanding of hydrological responses to climate variability. Whilst these can be computationally modelled, observed streamflow data is essential for constraining models, and understanding and quantifying emerging trends in the water cycle. To date, the identification of such trends at the global scale has been hindered by data limitations – in particular, the prevalence of direct human influences on streamflow which can obscure climate-driven variability. By removing these influences, trends in streamflow data can be more confidently attributed to climate variability. Here we describe the Reference Observatory of Basins for INternational hydrological climate change detection (ROBIN) – the first iteration of a global network of streamflow data from national reference hydrological networks (RHNs) – comprised of catchments which are near-natural or have limited human influences. This collaboration has established a freely available global RHN dataset of over 3,000 catchments and code libraries, which can be used to underpin new science endeavours and advance change detection studies to support international climate policy and adaptation.
- Evacuation of Lisbon’s Baixa-Chiado subway station in case of firePublication . Borralho, Tiago; Rodrigues, João Paulo; Calmeiro dos Santos, CristinaIt is essential to ensure that any building has conditions for a safe evacuation of its occupants. This aspect is essential in subway stations, where evacuation has to be carried out in an upward way, and usually correspond to large structures constituting a single fire compartment. Baixa-Chiado subway station, in Lisbon, Portugal, was selected for studying the evacuation in case of fire, due to its depth, high number of passengers that frequent the station and the existing of two intersecting train lines. A calculation of evacuation time was calculated and the way of evacuation studied, in different fire scenarios, number and location of occupants. The numerical simulations used Fire Dynamics Simulator and Pathfinder softwares, the first for fire spreading and the second for evacuation analysis. The importance of smoke control system, and its rapid activation in case of fire, was highlighted by the results obtained. In situations where this did not occur, there was a significant worsening in the evacuation of the occupants. It was estimated the incapacitation of a significant number of occupants, considering the levels registered for the fractional effective dose. The station’s architectural constraints proved to be a crucial factor in the results of the study. This article highlights important results applicable to subway stations around the world.
- In-bed posture classification using pressure data from a sensor sheet under the mattressPublication . Serra, André; Ribeiro, Fernando Reinaldo; Metrôlho, J.C.M.M.Monitoring and controlling the condition of bedridden individuals can help reduce health risks, as improper nocturnal habits or body positioning can exacerbate issues such as apnea, insomnia, sleep disorders, spinal problems, and pressure ulcers. Techniques using pressure maps from sensors placed on top of the mattress, along with machine learning (ML) algorithms to classify main postures (prone, supine, left side, right side), have achieved up to 99% accuracy. This study evaluated the feasibility of using a sensor sheet placed under the mattress to minimize patient discomfort. Experiments with ten commonly used ML algorithms achieved average accuracy values ranging from 79.14% to 98.93% using K-Fold cross-validation and from 80.03% to 97.14% using Leave-One-Group-Out (LOGO) for classifying the four main postures. The classification was extended to include 28 posture variations (7 variations for each of the 4 main postures), with the SVM algorithm achieving an accuracy of 65.18% in K-Fold validation, marking a significant improvement over previous studies, particularly regarding the number of postures considered. Comparisons with previous studies that used pressure sensors placed both under and on top of the mattress show that this approach achieves comparable accuracy to other methods, surpassing them with some algorithms and achieving the highest average accuracy. In conclusion, using sensors under the mattress is an effective and less invasive alternative for posture classification.
- Closing Editorial: Advances and future directions in autonomous systems for cyber-physical systems and smart industryPublication . Pinto, Rui; Torres, Pedro; Lohweg, VolkerThe rapid evolution of autonomous systems and their integration into cyber–physical Systems (CPS) and the Industrial Internet of Things (IIoT) has been a critical driver of the fourth industrial revolution, also known as Industry 4.0 [1], along with the transition towards Industry 5.0. These systems enable the real-time monitoring, control, and optimization of industrial processes by combining the power of computational intelligence with physical machinery. Autonomous systems offer significant potential for improving efficiency, flexibility, and sustainability in various industrial sectors. However, challenges remain, including interoperability, real-time data processing, and secure communication across heterogeneous devices and networks. Recent advancements in artificial intelligence (AI) [2], edge computing, advanced cyber security, and industrial automation have opened new avenues for innovation in CPS and smart industry. These innovations are driving the development of intelligent decision-making systems capable of self-managing the complexity and scale of modern industrial environments [3]. This Special Issue focuses on exploring the innovations and challenges in autonomous systems, aiming to bridge gaps in current knowledge and foster future research. The contributions to this Special Issue provide a comprehensive overview of the current state of the field while addressing critical challenges.
- Connection-aware digital twin for mobile adhoc networks in the 5G eraPublication . Jesús-Azabal, Manuel; Zhang, Zheng; Gao, Bingxia; Yang, Jing; Soares, V.N.G.J.5G Mobile Adhoc Networks (5G-MANETs) are a popular and agile solution for data transmission in local contexts while maintaining communication with remote entities via 5G. These characteristics have established 5G-MANETs as versatile communication infrastructures for deploying contextual applications, leveraging physical proximity while exploiting the possibilities of the Internet. As a result, there is growing interest in exploring the potential of these networks and their performance in real-world scenarios. However, the management and monitoring of 5G-MANETs are challenging due to their inherent characteristics, such as highly variable topology, unstable connections, energy consumption of individual devices, message routing, and occasional inability to connect to 5G. Considering these challenges, the proposed work aims to address real-time monitoring of 5G-MANETs using a connection-aware Digital Twin (DT). The approach provides two main functions: offering a live virtual representation of the network, even in scenarios where multiple nodes lack 5G connectivity, and estimating the performance of the infrastructure, enabling the specification of customized conditions. To achieve this, a communication architecture is proposed, analyzing its components and defining the involved processes. The DT is implemented and evaluated in a laboratory setting, assessing its accuracy in representing the physical network under varying conditions of topology and Internet availability. The results show 100% accuracy for the DT in fully connected topologies, with ultra-low latency averaging under 80 ms, and suitable performance in partially connected contexts, with latency averages below 3000 ms.
- Efficient data exchange between WebAssembly modulesPublication . Silva, Lucas; Metrôlho, J.C.M.M; Ribeiro, Fernando ReinaldoIn the past two decades, there has been a noticeable decoupling of machines and operating systems. In this context, WebAssembly has emerged as a promising alternative to traditional virtual machines. Originally designed for execution in web browsers, it has expanded to executing code in restricted and secure environments, and it stands out for its rapid startup, small footprint, and porta- bility. However, WebAssembly presents significant challenges in data transfer and the management of interactions with the module. Its specification requires each module to have its own memory, re- sulting in a “share-nothing” architecture. This restriction, combined with the limitations of importing and exporting functions that only handle numerical values, and the absence of an application binary interface (ABI) for sharing more complex data structures, leads to efficiency problems; these are exacerbated by the variety of programming languages that can be compiled and executed in the same environment. To address this inefficiency, the Karmem was designed and developed. It includes a new interface description language (IDL) aimed at facilitating the definition of data, functions, and relationships between modules. Additionally, a proprietary protocol—an optimized ABI for efficient data reading and minimal decoding cost—was created. A code generator capable of producing code for various programming languages was also conceived, ensuring harmonious interaction with the ABI and the foreign function interface. Finally, the compact runtime of Karmem, built atop a WebAssembly runtime, enables communication between modules and shared memory. Results of the experiments conducted show that Karmem represents an innovation in data communication for WASM in multiple environments and demonstrates the ability to overcome challenges of efficiency and interoperability.
- Toward optimal virtualization: An updated comparative analysis of Docker and LXD container technologiesPublication . Silva, Daniel; Rafael, João; Fonte, AlexandreTraditional hypervisor-assisted virtualization is a leading virtualization technology in data centers, providing cost savings (CapEx and OpEx), high availability, and disaster recovery. However, its inherent overhead may hinder performance and seems not scale or be flexible enough for certain applications, such as microservices, where deploying an application using a virtual machine is a longer and resource-intensive process. Container-based virtualization has received attention, especially with Docker, as an alternative, which also facilitates continuous integration/continuous deployment (CI/CD). Meanwhile, LXD has reactivated the interest in Linux LXC containers, which provides unique operations, including live migration and full OS emulation. A careful analysis of both options is crucial for organizations to decide which best suits their needs. This study revisits key concepts about containers, exposes the advantages and limitations of each container technology, and provides an up-to-date performance comparison between both types of containers (applicational vs. system). Using extensive benchmarks and well-known workload metrics such as CPU scores, disk speed, and network throughput, we assess their performance and quantify their virtualization overhead. Our results show a clear overall trend toward meritorious performance and the maturity of both technologies (Docker and LXD), with low overhead and scalable performance. Notably, LXD shows greater stability with consistent performance variability.
- Comparative analysis of Multicriteria Decision‐Making methods for bus washing process selection: a case studyPublication . Ávila, Paulo; Mota, Alzira; Oliveira, Eliana; Castro, Hélio; Ferreira, Luís Pinto; Bastos, João; Fernandes, Nuno O.; Moreira, JoaquimWater is at the core of sustainable development, and its use for human activities, including vehicle washing, should be done in a sustainable way. There are several technical solutions for washing buses offering different performances, making it difficult to choose the one that best meets the requirements of each specific case. The literature on the topic hardly analyzes the choice of the best technical solution for washing buses and does not apply and compare the results of different multicriteria decision-making (MCDM) methods for the problem. The unique information available is from the different suppliers in the market. Whereby, this work intends to give a technical-scientific contribution to fulfill this gaps. Therefore, the main objectives of this work are (1) to select the best sustainable technical solutions for washing buses depending on the specific conditions for a case study and (2) to analyze how different multicriteria decision-making methods behave in the selection process. To achieve these objectives, the problem was approached as a case study in a public transport company in Portugal and the methodology followed the next steps: started with the identification of the different types of commercial technical solutions for washing buses; the company’s experts selected four main criteria: water consumption, operating costs, quality of washing, and time spent; the criteria weights were determined using the fuzzy-AHP method; then four representative MCDM methods were selected, namely, AHP, ELECTRE, TOPSIS, and SMART; the ranks obtained for the four methods were compared; and a sensitivity analysis was performed. Considering the input data for the criteria and their weights, the results for all the methods showed that the best and the worst solution was the same, mobile portico with a brush and porticoes with three brushes, respectively. Furthermore, the results of the sensitivity analysis performed with disturbances for the weights of each criterion presented that the results are slightly affected and the similarity in rankings for the four MCDM methods was validated by Spearman’s rank correlation coefficient (rs) and Kendall’s coefficient of concordance (W). Considering these results, the SMART method, the less complex one, showed no difference from the others. For that reason, simple methods, such as SMART, in line with other works in the literature perform well in most cases. As a final remark of this work, it can be said that the methodology employed in this project can also be deemed applicable to other similar companies seeking technical solutions for bus or truck washing. Furthermore, the application of the SMART method, the less complex one and the most understandable for people, showed no difference from the others, being able to be applied in similar situations.
- DDMRP relative priority for production execution: an assessment by simulationPublication . Fernandes, Nuno O.; Thürer, Matthias; Silva, Sílvio do CarmoDemand-Driven Material Requirements Planning (DDMRP) was designed to improve supply chain performance in complex and uncertain environments. Literature on the topic suggests that production replenishment orders should be dispatched for execution based on the buffers’ penetration ratio of the products ordered, which is a measure of protection against stock depletion. However, the actual performance impact of this dispatching rule remains largely unknown as is the impact of different lot transfer policies. A simulation analysis was carried out to compare the performance of the lowest net flow position, the highest buffer penetration ratio, earliest operation due date and first-come first-served rules under synchronized and unsynchronized lot transfer policies. Results of our study show that the choice of dispatching rules is contingent on the setting of top-of-yellow and top-of-green, which determine the re-order quantity, and on the demand mix of products. The earliest operation due date rule shows great potential to outperform the rule typically applied in a DDMRP context specifically for a high demand mix. These findings provide important insights for improving industrial practice and for guiding future research on DDMRP.