Sistema de supervisão e controle de irrigação utilizando técnicas de inteligência artificial
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Data
2003-12-18
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Universidade Estadual Paulista (Unesp)
Resumo
O presente trabalho teve como objetivo a configuração de um sistema de supervisão e controle de irrigação utilizando técnicas de inteligência artificial. De acordo com metodologia adotada, o seu desenvolvimento foi realizado em três fases distintas. Inicialmente foram construídos os seguintes módulos de hardware: Unidade de Sensores, Unidade Concentradora de Dados e Sensor de Umidade do Solo do tipo Capacitivo. Em seguida foi criada uma aplicação através do programa de supervisão e controle do tipo SCADA, Elipse PRO, dedicada à supervisão e controle de uma casa de vegetação. Na fase final foram coletados os dados necessários para o treinamento de uma rede neural artificial que é parte integrante do sensor de umidade de solo do tipo capacitivo. Os resultados obtidos através de um conjunto de teste de medidas demonstraram que o sensor capacitivo apresenta comportamento e desempenho similares ao do sensor de do tipo TDR, o que permite concluir que esta solução pode representar uma significativa contribuição, viabilizando a implantação de sistemas de supervisão e controle em processos de irrigação com uma relação custo/benefício em níveis aceitáveis.
The present work had as objective the configuration of a supervisory and control system for irrigation using artificial intelligence techniques. In agreement with adopted methodology, its development was accomplished in three different phases. Initially the following hardware modules were built: Sensors Unit, Data Concentrator Unit and a Capacitive type Soil Moisture Sensor. Soon afterwards an application was created through the supervisory and control program of the type SCADA, Ellipse PRO, dedicated to the supervision and control of a green house. In the final phase the necessary data were collected for the training of an artificial neural network that is integral part of the capacitive type soil moisture sensor. With the application developed in the Ellipse PRO a database was created for the training of the artificial neural network, containing a group of 2440 measures of soil moisture obtained through a capacitive type sensor and a TDR type sensor. The results obtained through a group of test of measures demonstrated that the capacitive sensor presents a similar behavior to the of the TDR type sensor, the one that allows conclude that this solution can represent a significant contribution, making possible the implantation of supervisory and control systems in irrigation processes with a cost/benefit relationship in acceptable levels.
The present work had as objective the configuration of a supervisory and control system for irrigation using artificial intelligence techniques. In agreement with adopted methodology, its development was accomplished in three different phases. Initially the following hardware modules were built: Sensors Unit, Data Concentrator Unit and a Capacitive type Soil Moisture Sensor. Soon afterwards an application was created through the supervisory and control program of the type SCADA, Ellipse PRO, dedicated to the supervision and control of a green house. In the final phase the necessary data were collected for the training of an artificial neural network that is integral part of the capacitive type soil moisture sensor. With the application developed in the Ellipse PRO a database was created for the training of the artificial neural network, containing a group of 2440 measures of soil moisture obtained through a capacitive type sensor and a TDR type sensor. The results obtained through a group of test of measures demonstrated that the capacitive sensor presents a similar behavior to the of the TDR type sensor, the one that allows conclude that this solution can represent a significant contribution, making possible the implantation of supervisory and control systems in irrigation processes with a cost/benefit relationship in acceptable levels.
Descrição
Palavras-chave
Estufa (Plantas) - Automação, Irrigação, Inteligencia artificial, Green house automation, Artificial neural network, Soil moisture sensor
Como citar
FONTES, Ivo Reis. Sistema de supervisão e controle de irrigação utilizando técnicas de inteligência artificial. 2003. xv,209f. Tese (doutorado) - Universidade Estadual Paulista, Faculdade de Ciências Agronômicas de Botucatu, 2003.