{"title":"基于物联网的精准农业应用网络模型及传感器节点原型","authors":"Josip Spisic, J. Balen, D. Zagar, V. Galić","doi":"10.1109/WF-IoT54382.2022.10152218","DOIUrl":null,"url":null,"abstract":"The recent advancement of the Internet of Things (IoT) enabled the development of precision agriculture by using high technology sensors and analysis tools for improving crop yields and assisting management decisions. Due to its highly interoperable, scalable, widespread, and open nature, the IoT approach is an ideal match for precision agriculture. We built our model in response to the above benefits and potentials of IoT in precision agriculture. In this paper we propose a low cost IoT based network model using the developed IoT sensor node for precision agriculture applications consisting of a near-infrared sensor and general purpose microcontroller for gathering data from agricultural fields. Our model architecture is extremely flexible, and it provides a machine learning data analytics solution that enables small size data processing at the edge of the network (sensor nodes) and large-scale data processing on real-time observation streams of data from a number nodes in the cloud. We employ LoRaWAN™, a wide area networking protocol as a transmission protocol in our solution, which has a low power consumption, long-range capability, it's affordable and requires little maintenance, making it perfect for large fields and variable number of sensor nodes. According to the first results of device testing presented in this report, our device might provide affordable means of field-based spatio-temporal sensing.","PeriodicalId":176605,"journal":{"name":"2022 IEEE 8th World Forum on Internet of Things (WF-IoT)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"IoT Based Network Model And Sensor Node Prototype For Precision Agriculture Application\",\"authors\":\"Josip Spisic, J. Balen, D. Zagar, V. Galić\",\"doi\":\"10.1109/WF-IoT54382.2022.10152218\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The recent advancement of the Internet of Things (IoT) enabled the development of precision agriculture by using high technology sensors and analysis tools for improving crop yields and assisting management decisions. Due to its highly interoperable, scalable, widespread, and open nature, the IoT approach is an ideal match for precision agriculture. We built our model in response to the above benefits and potentials of IoT in precision agriculture. In this paper we propose a low cost IoT based network model using the developed IoT sensor node for precision agriculture applications consisting of a near-infrared sensor and general purpose microcontroller for gathering data from agricultural fields. Our model architecture is extremely flexible, and it provides a machine learning data analytics solution that enables small size data processing at the edge of the network (sensor nodes) and large-scale data processing on real-time observation streams of data from a number nodes in the cloud. We employ LoRaWAN™, a wide area networking protocol as a transmission protocol in our solution, which has a low power consumption, long-range capability, it's affordable and requires little maintenance, making it perfect for large fields and variable number of sensor nodes. According to the first results of device testing presented in this report, our device might provide affordable means of field-based spatio-temporal sensing.\",\"PeriodicalId\":176605,\"journal\":{\"name\":\"2022 IEEE 8th World Forum on Internet of Things (WF-IoT)\",\"volume\":\"43 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-10-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 IEEE 8th World Forum on Internet of Things (WF-IoT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WF-IoT54382.2022.10152218\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE 8th World Forum on Internet of Things (WF-IoT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WF-IoT54382.2022.10152218","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
IoT Based Network Model And Sensor Node Prototype For Precision Agriculture Application
The recent advancement of the Internet of Things (IoT) enabled the development of precision agriculture by using high technology sensors and analysis tools for improving crop yields and assisting management decisions. Due to its highly interoperable, scalable, widespread, and open nature, the IoT approach is an ideal match for precision agriculture. We built our model in response to the above benefits and potentials of IoT in precision agriculture. In this paper we propose a low cost IoT based network model using the developed IoT sensor node for precision agriculture applications consisting of a near-infrared sensor and general purpose microcontroller for gathering data from agricultural fields. Our model architecture is extremely flexible, and it provides a machine learning data analytics solution that enables small size data processing at the edge of the network (sensor nodes) and large-scale data processing on real-time observation streams of data from a number nodes in the cloud. We employ LoRaWAN™, a wide area networking protocol as a transmission protocol in our solution, which has a low power consumption, long-range capability, it's affordable and requires little maintenance, making it perfect for large fields and variable number of sensor nodes. According to the first results of device testing presented in this report, our device might provide affordable means of field-based spatio-temporal sensing.