Diego Padilla-Quimbiulco, Juan Morales-García, Magdalena Cantabella, Belén Ayuso, Andrés Muñoz, José M. Cecilia
{"title":"Greenhouse intelligent warning system for precision agriculture","authors":"Diego Padilla-Quimbiulco, Juan Morales-García, Magdalena Cantabella, Belén Ayuso, Andrés Muñoz, José M. Cecilia","doi":"10.1109/IE57519.2023.10179105","DOIUrl":null,"url":null,"abstract":"Greenhouses are complex systems where many variables are involved in order to optimize crops in an intensive agriculture framework. Therefore, monitoring and visualization of all these variables in real-time is mandatory to meet the trade-off between natural resource consumption and production maximization. In this article, we introduce an intelligent warning system to efficiently control agricultural activity in an operational greenhouse to increase productivity by optimizing crop production and energy consumption. The system includes a web application that allows the graphical and statistical representation of data measured by several sensors located inside a greenhouse. These sensors are located in strategic points that allow the reading of real-time data in a more accurate manner, therefore allowing the generation of information with the minimum percentage of error. In addition, the web application offers different data representations to allow a more exhaustive analysis of the data obtained. As a result, this warning system may help greenhouse managers to anticipate abnormal situations affecting their crops.","PeriodicalId":439212,"journal":{"name":"2023 19th International Conference on Intelligent Environments (IE)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 19th International Conference on Intelligent Environments (IE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IE57519.2023.10179105","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Greenhouses are complex systems where many variables are involved in order to optimize crops in an intensive agriculture framework. Therefore, monitoring and visualization of all these variables in real-time is mandatory to meet the trade-off between natural resource consumption and production maximization. In this article, we introduce an intelligent warning system to efficiently control agricultural activity in an operational greenhouse to increase productivity by optimizing crop production and energy consumption. The system includes a web application that allows the graphical and statistical representation of data measured by several sensors located inside a greenhouse. These sensors are located in strategic points that allow the reading of real-time data in a more accurate manner, therefore allowing the generation of information with the minimum percentage of error. In addition, the web application offers different data representations to allow a more exhaustive analysis of the data obtained. As a result, this warning system may help greenhouse managers to anticipate abnormal situations affecting their crops.