ESTCB - Escola Superior de Tecnologia
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Browsing ESTCB - Escola Superior de Tecnologia by Author "Aidos, Clara"
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- Computer vision for reducing food waste in an institutional canteen: A literature review and performance analysisPublication . Correia, Ana; Aidos, Clara; Caldeira, J.M.L.P.; Soares, V.N.G.J.Food waste in today's society has been the subject of growing interest and discussion, given its economic, environmental, social, and nutritional implications. Although food waste is present throughout the food supply chain, in developed countries it tends to be higher in the final stages of consumption (e.g., households and food services). This study focuses on institutional canteens, where food waste includes prepared meals that have not been sold (i.e., leftovers), as well as food served that is left on plates after the meal has been consumed (i.e., scraps). It presents a first step towards developing a prototype/solution based on computer vision techniques to identify and quantify food waste in an institutional canteen. It begins by introducing the related concepts. It then surveys the state-of-the-art and categorizes existing solutions, presenting their main characteristics, strengths, and limitations. Inception-V3 and ResNet-50 are identified as the most promising computer vision techniques, and their performance has been evaluated. Information is also provided on open questions and research directions in this area
- Development of a prototype solution for reducing soup waste in an institutional canteenPublication . Correia, Ana; Aidos, Clara; Caldeira, J.M.L.P.; Soares, V.N.G.J.Food waste has gained increasing attention and debate, given its economic, environmental, social, and nutritional implications. One-third of food intended for human consumption is wasted. Although it is present at all stages of the food supply chain, it is in the final stages of consumption, such as households and food services, that the problem becomes most evident. This work builds on a previous study by the same authors, which identified computer vision as a suitable technology for identifying and quantifying food waste in institutional canteens. Based on this result, this paper describes the proposal and implementation process of a prototype demonstration. It is based on a Raspberry Pi 4 platform, a Resnet-50 model adapted with the Faster Region-Convolutional Neural Network (Faster R-CNN) model, and an algorithm for feature extracting. A specially built dataset was used to meet the challenge of detecting soup bowls and classifying waste in their consumption. A web application was developed to visualize the data collected, supporting decision making for more efficient food waste management. The prototype was subjected to validation and functional tests, and proved to be a viable, low-cost solution.
- Utilização de técnicas de visão computacional para redução do desperdício alimentar numa cantina institucionalPublication . Correia, Ana; Aidos, Clara; Soares, Vasco N.G.J.; Caldeira, J.M.L.P.Na sociedade atual, o desperdício alimentar tem sido alvo de interesse e discussão crescente, face às implicações económicas, ambientais, sociais e nutricionais. Este trabalho foca-se nas cantinas institucionais, onde o desperdício alimentar engloba as refeições preparadas que não foram vendidas, bem como os alimentos servidos que sobram nos pratos após o consumo da refeição. Esta apresentação centra-se num estudo que visa validar, avaliar e comparar diferentes técnicas de visão computacional para identificar e quantificar o desperdício alimentar numa cantina institucional. Apresenta os conceitos relacionados com a temática e as soluções apontadas na literatura, discute os pontos fortes e limitações das mesmas e identifica pontos em aberto. Após esta análise, apresenta uma avaliação de desempenho das técnicas mais promissoras para solução deste problema.