EsACT - Artigos em Revistas Indexados à WoS/Scopus
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Percorrer EsACT - Artigos em Revistas Indexados à WoS/Scopus por Objetivos de Desenvolvimento Sustentável (ODS) "12:Produção e Consumo Sustentáveis"
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- How can Design Thinking improve food sustainability in the Minho Region? A multi-actor perspectivePublication . Campos, Susana; Oliveira, Rafael; Correia, Ricardo Jorge; Oliveira, Ana Teresa; Rodrigues, Ana Sofia; Velho, Manuela VazUsing the Design Thinking methodology and the multi-actor approach, the aim was to find an innovative and collaborative perspective that reconciles gastronomic traditions with health and sus-tainability criteria. To this end, two workshops were held, bringing together 12 participants from the agri-food ecosystem in the Minho region. We concluded that the topics discussed and the solutions proposed highlighted the intrinsic relationship between local production and sustainability, empha-sizing that the proximity between producer and consumer translates not only into a lower carbon footprint but also into the socio-economic and cultural enhancement of the region. The richness of Minho products, from their flavors, textures, and stories, deserves to be celebrated but also protected and adapted to the new challenges of today's society.This study has a very original and multidisci-plinary approach. Integrating different actors, specialties, and perspectives has promoted a rich ex-change of knowledge and experience, materialized in convergent ideas. To improve the future of enogastronomy, the design thinking approach is used for the first time in literature to promote inte-grated solutions in the Minho food system.
- PROMORE: a procedural modeler of virtual rural environments with artificial dataset generation capabilities for remote sensing contextsPublication . Adão, Telmo; Cerqueira, João; Adão, Miguel; Silva, Nuno; Pascoal, David; Magalhães, Luís G.; Barros, Tiago; Premebida, Cristiano; Nunes, Urbano J.; Peres, Emanuel; Morais, RaulRemote sensing (RS) is a rapidly evolving field that facilitates the study of phenomena on the Earth’s surface. Through various platforms, including satellites, manned aircraft, and remotely piloted aerial vehicles (RPAV), RS has been strategically applied to critical sectors like agriculture and forestry, which are essential for humanity’s sustenance. Key applications include crops classification, yield estimation and livestock monitoring and quantification. In the era of artificial intelligence (AI), the development of deep learning (DL) models for such applications often requires extensive field data collection and labor-intensive image labeling, which are both time-consuming and resource-intensive. To address these challenges, this paper presents Procedural Modeling of Rural Environments (PROMORE), a parameterizable, ontology driven system designed to generate 3D virtual environments encompassing forestry, farmland – mainly focused on vineyards – and village settings. This system also implements functionalities to automate the extraction of training data for deep learning applications in remote sensing, with the declared aim of providing complementary capabilities to data augmentation techniques, encompassing both traditional methods (e.g., flips, rotations, zooming) and advanced approaches such as generative adversarial networks (GANs). By simulating RPAV flights and managing virtual object visibility, PROMORE enables the automatic labeling, delineation, and highlighting of elements of interest (e.g., vine plants, trees, buildings), facilitating the generation of datasets tailored for tasks such as semantic segmentation, and object detection.