{"title":"基于物联网和人工智能的工厂监控系统","authors":"Bhuvan Puri","doi":"10.30991/ijmlnce.2020v04i03.005","DOIUrl":null,"url":null,"abstract":"Plants plays a vital role in the environment because it provides the health support through absorbing the carbon dioxide and releasing the oxygen to the atmosphere. Although, it required to maintain the proper plant growth and health as well as provide the appropriate monitoring. To overcome these concerns, an Artificial Intelligence (AI) and Internet of Things (IoT) based solution is proposed to monitor the plant’s growth and health. This study demonstrates the real-time monitoring of the plants via environmental sensors such as DHT 11 and soil moisture sensors. Real-time values stored in the cloud server and applied the machine learning models to predict the plant’s growth. The Statistical parameters such as RMSE, MAE are used to analyze the resulting outcome from the system.","PeriodicalId":338210,"journal":{"name":"International Journal of Machine Learning and Networked Collaborative Engineering","volume":"36 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"IoT and AI-based Plant Monitoring System\",\"authors\":\"Bhuvan Puri\",\"doi\":\"10.30991/ijmlnce.2020v04i03.005\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Plants plays a vital role in the environment because it provides the health support through absorbing the carbon dioxide and releasing the oxygen to the atmosphere. Although, it required to maintain the proper plant growth and health as well as provide the appropriate monitoring. To overcome these concerns, an Artificial Intelligence (AI) and Internet of Things (IoT) based solution is proposed to monitor the plant’s growth and health. This study demonstrates the real-time monitoring of the plants via environmental sensors such as DHT 11 and soil moisture sensors. Real-time values stored in the cloud server and applied the machine learning models to predict the plant’s growth. The Statistical parameters such as RMSE, MAE are used to analyze the resulting outcome from the system.\",\"PeriodicalId\":338210,\"journal\":{\"name\":\"International Journal of Machine Learning and Networked Collaborative Engineering\",\"volume\":\"36 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Machine Learning and Networked Collaborative Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.30991/ijmlnce.2020v04i03.005\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Machine Learning and Networked Collaborative Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.30991/ijmlnce.2020v04i03.005","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Plants plays a vital role in the environment because it provides the health support through absorbing the carbon dioxide and releasing the oxygen to the atmosphere. Although, it required to maintain the proper plant growth and health as well as provide the appropriate monitoring. To overcome these concerns, an Artificial Intelligence (AI) and Internet of Things (IoT) based solution is proposed to monitor the plant’s growth and health. This study demonstrates the real-time monitoring of the plants via environmental sensors such as DHT 11 and soil moisture sensors. Real-time values stored in the cloud server and applied the machine learning models to predict the plant’s growth. The Statistical parameters such as RMSE, MAE are used to analyze the resulting outcome from the system.