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UCO-PEEKING: sistema IoT para automatização da recolha de óleos alimentares usados
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Abstract(s)
Os Óleos Alimentares Usados OAU, vulgarmente resultantes dos processos de confeção culinária, têm efeitos nocivos para a saúde e para o ambiente em geral. No entanto estes resíduos podem ser reutilizados como biocombustíveis, motivando por isso o surgimento de soluções de recolha, particularmente os provenientes de contextos domésticos, uma vez que podem ser reciclados em maior escala.
Existem atualmente redes de pontos de recolha a nível nacional RENO, contudo, a grande maioria do óleo alimentar usado, produzido em ambiente doméstico, ainda não é recolhido, continuando portanto a ser descartado indevidamente e sem entrar nos processos de reciclagem. Adicionalmente, nem todos os depósitos que entram nas redes de recolha são totalmente recicláveis uma vez que os utilizadores depositam por vezes outros líquidos (e.g. água, óleos usados de carro) que não podem entrar nos processos de reciclagem dos OAU.
Com vista a melhorar a eficiência e a taxa de utilização das redes de recolha existentes, propõe-se neste trabalho um sistema IoT que permite automatizar a classificação dos depósitos de óleo alimentar usado, bem como a sua associação a utilizadores registados, aos quais poderão desta forma ser atribuídas bonificações sempre que é detetado um depósito fidedigno.
Neste projeto foram portanto estudadas formas de automatizar a recolha e identificação de OAU, por forma a distinguir depósitos fraudulentos. Pretendeuse em concreto conseguir distinguir OAU de outros líquidos vulgarmente encontrados em depósitos nas redes de recolha, tais como, óleo de automóvel usado e água. Mais concretamente, foram estudados, analisados e combinados vários tipos de sensores que pudessem ser utilizados para diferenciar de forma automática os tipos de líquidos depositados nos oleões de recolha.
Com base nesses sensores e recorrendo à fusão de informação proveniente das várias fontes, foi possível obter uma forma automática de diferenciação dos líquidos depositados. A integração desta solução numa arquitetura IoT permite então automatizar e melhorar o processo de recolha e classificação de forma distribuída e global. Concomitantemente, associado à simplificação e facilidade de utilização da rede de recolha, desenvolveu-se um sistema de gestão e atribuição de benefícios com o objetivo de sensibilizar a população para a reciclagem, e ainda facilitar e incrementar a sua utilização com base num programa de atribuição de pontos diretamente associado aos depósitos domésticos fidedignos de OAU.
Used cooking oils OCU, commonly resulting from cooking processes, have harmful effects on health and the environment in general. However, these residues can be reused as biofuels, thus motivating the emergence of collection solutions, particularly those from domestic contexts, since they can be recycled on a larger scale. There are currently networks of collection points nationwide RENO, however, the vast majority of used cooking oil, produced in the domestic environment, is still not collected, and therefore continues to be improperly disposed without entering the recycling processes. Additionally, not all deposits entering the collection networks are fully recyclable as users sometimes deposit other liquids (e.g. water, used car oils) that cannot enter the OCU recycling processes. In order to improving the efficiency and utilization rate of the existing collection networks, an IoT system is proposed in this work allowing to automate the classification of used cooking oil disposals, as well as their association with registered users, who can benefit from bonuses whenever a trustworthy deposit is detected. In this project, ways were studied to automate the collection and classification of OCU, in order to distinguish fraudulent deposits. The aim was specifically to distinguish OCU from other liquids commonly found in disposals in the OCU collection networks, such as used car oil and water. More specifically, various types of sensors that could be used to automatically differentiate the types of liquid deposited in the collection oils were studied, analyzed and combined. Based on these sensors and using the fusion of information from various sources, it was possible to obtain an automatic way of differentiating the deposited liquids. The integration of this solution in an IoT architecture allows then to automate and improve the collection and classification process in a distributed and global way. At the same time, associated with the simplification and ease of use of the collection network, a management and benefit allocation system was developed with the aim of raising awareness among the population about recycling, and also facilitating and increasing its use based on an allocation program of points directly associated with the trusted domestic deposits of OCU.
Used cooking oils OCU, commonly resulting from cooking processes, have harmful effects on health and the environment in general. However, these residues can be reused as biofuels, thus motivating the emergence of collection solutions, particularly those from domestic contexts, since they can be recycled on a larger scale. There are currently networks of collection points nationwide RENO, however, the vast majority of used cooking oil, produced in the domestic environment, is still not collected, and therefore continues to be improperly disposed without entering the recycling processes. Additionally, not all deposits entering the collection networks are fully recyclable as users sometimes deposit other liquids (e.g. water, used car oils) that cannot enter the OCU recycling processes. In order to improving the efficiency and utilization rate of the existing collection networks, an IoT system is proposed in this work allowing to automate the classification of used cooking oil disposals, as well as their association with registered users, who can benefit from bonuses whenever a trustworthy deposit is detected. In this project, ways were studied to automate the collection and classification of OCU, in order to distinguish fraudulent deposits. The aim was specifically to distinguish OCU from other liquids commonly found in disposals in the OCU collection networks, such as used car oil and water. More specifically, various types of sensors that could be used to automatically differentiate the types of liquid deposited in the collection oils were studied, analyzed and combined. Based on these sensors and using the fusion of information from various sources, it was possible to obtain an automatic way of differentiating the deposited liquids. The integration of this solution in an IoT architecture allows then to automate and improve the collection and classification process in a distributed and global way. At the same time, associated with the simplification and ease of use of the collection network, a management and benefit allocation system was developed with the aim of raising awareness among the population about recycling, and also facilitating and increasing its use based on an allocation program of points directly associated with the trusted domestic deposits of OCU.