Loading...
Publication
MonitorizaĆ§Ć£o de separadores de gordura industriais recorrendo a uma arquitetura Fog Computing
| Name: | Description: | Size: | Format: | |
|---|---|---|---|---|
| 2.3 MB | Adobe PDF |
Authors
Advisor(s)
Abstract(s)
Existe atualmente uma consciencializaĆ§Ć£o social generalizada para a proteĆ§Ć£o do ambiente. Neste trabalho procura-se materializar uma soluĆ§Ć£o tecnolĆ³gica de monitorizaĆ§Ć£o IoT para automatizar separadores/coletores industriais de gordura. Estes separadores industriais de gordura possuem um papel significativo no que diz respeito ao tratamento dos esgotos urbanos, uma vez que evitam que a indĆŗstria da restauraĆ§Ć£o aumente a fatia poluente deste sistema. Os separadores de gordura sĆ£o, portanto, dispositivos que facilitam a separaĆ§Ć£o de parte das gorduras e Ć³leos presentes nos detritos alimentares, que de outra forma seriam lanƧados nos sistemas de esgotos dos restaurantes. O processo de separaĆ§Ć£o utilizado nos coletores de gordura baseia-se na flutuaĆ§Ć£o natural das gorduras em meio aquoso, de forma a reduzir a concentraĆ§Ć£o dos resĆduos que atingem as redes coletoras ou mesmo os sistemas de tratamento individual, quando nĆ£o hĆ” ligaĆ§Ć£o com o sistema pĆŗblico de esgoto.
Neste trabalho propƵe-se uma arquitetura IoT baseada em Fog computing para monitorizar remotamente os nĆveis de gordura em vĆ”rios separadores industriais instalados numa rede de restaurantes a nĆvel nacional. A soluĆ§Ć£o distribuĆda proposta permite a mediĆ§Ć£o remota da quantidade de gordura em todos os separadores instalados. Desta forma, possibilita automatizar e gerir de forma escalĆ”vel todo o processo de limpeza e manutenĆ§Ć£o dos separadores de gordura. Esta separaĆ§Ć£o e recolha permite a reciclagem e tambĆ©m evitar extravasamentos que inevitavelmente iriam aumentar a poluiĆ§Ć£o dos esgotos urbanos.
De uma forma mais precisa, a empresa Hardlevel Ć© responsĆ”vel, a nĆvel nacional, pela recolha de Ć³leo alimentar usado de 5000 restaurantes, tendo atĆ© ao momento 50 separadores de gordura instalados. Esta Ć© uma Ć”rea de negĆ³cio na qual pretende apostar e expandir de forma economicamente rentĆ”vel.
Na soluĆ§Ć£o proposta foi necessĆ”rio identificar e selecionar os sensores mais adequados para medir os nĆveis de enchimento nos separados de gordura existentes. Os fatores de seleĆ§Ć£o incluĆram nĆ£o sĆ³ a efetiva possibilidade de mediĆ§Ć£o dos nĆveis de gordura, como tambĆ©m o custo associado uma vez que a rede de separadores de gordura Ć© extensa e cada restaurante pode possuir vĆ”rias unidades industriais instaladas. Para alĆ©m dos sensores foi ainda necessĆ”rio integrĆ”-los numa arquitetura Fog computing, recorrendo a mĆ³dulos de aquisiĆ§Ć£o e comunicaĆ§Ć£o de dados, que permite automatizar a monitorizaĆ§Ć£o dos nĆveis de gordura em cada separador, e enviar as notificaƧƵes necessĆ”rias sobre as necessidades de limpeza e de manutenĆ§Ć£o. Esta soluĆ§Ć£o estĆ” a ser aplicada a nĆvel nacional e tem-se mostrado adequada e escalĆ”vel Ć s necessidades existentes.
A arquitetura Fog Computing utilizada organiza-se em camadas capazes de processar e agregar os dados recebidos pelos dispositivos IoT conectados entre si. Os sensores utilizados foram: i) o sensor de condutividade, que permite detetar a quantidade de Ć”gua existente nos separadores de gordura; ii) o sensor de turbidez, que permite detetar a quantidade de restos alimentares e a qualidade da Ć”gua. Em resumo, a principal contribuiĆ§Ć£o deste trabalho consiste na soluĆ§Ć£o IoT proposta, baseada numa arquitetura Fog Computing, que recorre aos sensores de condutividade e turbidez. O primeiro, foi desenvolvido no Ć¢mbito desta tese e permite detectar o nĆvel de Ć”gua/gordura e o segundo, foi selecionado entre outros, porque se adequa Ć detecĆ§Ć£o da quantidade de FOG nos separadores de gordura. Desta forma, a soluĆ§Ć£o permite evitar extravasamentos e entupimentos dos esgotos, contribuindo assim para a reciclagem e protecĆ§Ć£o do ambiente.
There is now a widespread social awareness for the protection of the environment. This work seeks to materialize a technological monitoring solution IoT to automate industrial grease separators/collectors. These industrial fat separators play a significant role with regard to the treatment of urban sewage, as they prevent the catering industry from increasing the pollutant share of this system. The fat separators are, therefore, devices that facilitate the separation of part of the fats and oils present in the food waste, which would otherwise be released in the sewage systems of restaurants. The separation process used in fat collectors is based on the natural fluctuation of fats in an aqueous medium, in order to reduce the concentration of waste that reaches the collection networks or even the individual treatment systems, when there is no connection with the public system sewage. In this work, a IoT architecture based on Fog computing is proposed to remotely monitor fat levels in various industrial separators installed in a national restaurant chain. The proposed distributed solution allows remote measurement of the amount of fat in all installed separators. In this way, it makes it possible to automate and manage in a scalable way the entire process of cleaning and maintaining grease separators. This separation and collection allows recycling and also prevents spills that would inevitably increase the pollution of urban sewers. More precisely, the company Hardlevel is responsible, at national level, for the collection of used cooking oil from 5000 restaurants, with 50 fat separators installed so far. This is a business area in which you want to bet and expand in an economically profitable way. In the proposed solution, it was necessary to identify and select the most suitable sensors to measure the filling levels in the existing grease separators. The selection factors included not only the effective possibility of measuring fat levels, but also the associated cost since the network of fat separators is extensive and each restaurant can have several industrial units installed. In addition to the sensors, it was also necessary to integrate them in a Fog computing architecture, using data acquisition and communication modules, which allows to automate the monitoring of fat levels in each separator, and to send the necessary notifications about the needs cleaning and maintenance. This solution is being applied at the national level and has proven to be adequate and scalable to existing needs. The Fog Computing architecture used is organized into layers capable of processing and aggregating the data received by the connected IoT devices. The sensors used were: i) the conductivity sensor, which allows the detection of the amount of water in the grease separators; ii) the turbidity sensor, which allows the detection of the quantity of food waste and the quality of the water. In summary, the main contribution of this work consists of the proposed IoT solution, based on a Fog Compuntig architecture, which uses conductivity and turbidity sensors. The first was developed within the scope of this thesis and allows the detection of the water / fat level and the second, was selected among others, because it is suitable for detecting the amount of FOG in the fat separators. In this way, the solution makes it possible to avoid overflowing and clogging sewers, thus contributing to recycling and environmental protection.
There is now a widespread social awareness for the protection of the environment. This work seeks to materialize a technological monitoring solution IoT to automate industrial grease separators/collectors. These industrial fat separators play a significant role with regard to the treatment of urban sewage, as they prevent the catering industry from increasing the pollutant share of this system. The fat separators are, therefore, devices that facilitate the separation of part of the fats and oils present in the food waste, which would otherwise be released in the sewage systems of restaurants. The separation process used in fat collectors is based on the natural fluctuation of fats in an aqueous medium, in order to reduce the concentration of waste that reaches the collection networks or even the individual treatment systems, when there is no connection with the public system sewage. In this work, a IoT architecture based on Fog computing is proposed to remotely monitor fat levels in various industrial separators installed in a national restaurant chain. The proposed distributed solution allows remote measurement of the amount of fat in all installed separators. In this way, it makes it possible to automate and manage in a scalable way the entire process of cleaning and maintaining grease separators. This separation and collection allows recycling and also prevents spills that would inevitably increase the pollution of urban sewers. More precisely, the company Hardlevel is responsible, at national level, for the collection of used cooking oil from 5000 restaurants, with 50 fat separators installed so far. This is a business area in which you want to bet and expand in an economically profitable way. In the proposed solution, it was necessary to identify and select the most suitable sensors to measure the filling levels in the existing grease separators. The selection factors included not only the effective possibility of measuring fat levels, but also the associated cost since the network of fat separators is extensive and each restaurant can have several industrial units installed. In addition to the sensors, it was also necessary to integrate them in a Fog computing architecture, using data acquisition and communication modules, which allows to automate the monitoring of fat levels in each separator, and to send the necessary notifications about the needs cleaning and maintenance. This solution is being applied at the national level and has proven to be adequate and scalable to existing needs. The Fog Computing architecture used is organized into layers capable of processing and aggregating the data received by the connected IoT devices. The sensors used were: i) the conductivity sensor, which allows the detection of the amount of water in the grease separators; ii) the turbidity sensor, which allows the detection of the quantity of food waste and the quality of the water. In summary, the main contribution of this work consists of the proposed IoT solution, based on a Fog Compuntig architecture, which uses conductivity and turbidity sensors. The first was developed within the scope of this thesis and allows the detection of the water / fat level and the second, was selected among others, because it is suitable for detecting the amount of FOG in the fat separators. In this way, the solution makes it possible to avoid overflowing and clogging sewers, thus contributing to recycling and environmental protection.