Gianmarco Canello, Silvia Mignardi, K. Mikhaylov, C. Buratti, T. Hänninen
{"title":"无人机网关LoRaWAN传感器网络数据采集:设计、实证结果与数据集","authors":"Gianmarco Canello, Silvia Mignardi, K. Mikhaylov, C. Buratti, T. Hänninen","doi":"10.1109/EuCNC/6GSummit58263.2023.10188238","DOIUrl":null,"url":null,"abstract":"Collecting data from Internet-of-Things (IoT) devices, especially the variety of sensors dispersed in the environment, is an increasingly important and difficult task. Several long-range radio-access technologies, such as low-power wide-area networks (LPWAN) and specifically LoRaWAN, have been proposed to address this challenge. However, until now, the key focus of the related studies has been on static terrestrial LPWAN deployments. In this study, we depart from this vision and investigate the practical feasibility and performance of a LoRaWAN gateway (GW) on a flying platform, specifically - an unmanned aerial vehicle (UAV). The key contributions of this study are (i) the design and field-testing of a packet-sniffer-based mobile LoRaWAN GW prototype, allowing collection of the data from LoRaWAN networks, including the already deployed ones; (ii) the open-publication of the data collected during our experimental campaign in the 426 LoRaWAN sensor node network of the University of Oulu illustrating the performance of different drone trajectories; (iii) the initial results of the system's performance analysis, revealing some interesting trends and setting goals for further studies, and pinpointing the lessons learned during the experimental campaign. Our empirical findings suggest that the Travelling Salesman Problem (TSP) trajectory is the most effective moving trajectory for the number of packets collected and the average energy consumed per packet collected.","PeriodicalId":65870,"journal":{"name":"公共管理高层论坛","volume":"4 1","pages":"555-560"},"PeriodicalIF":0.0000,"publicationDate":"2023-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Data collection from LoRaWAN sensor network by UAV gateway: design, empirical results and dataset\",\"authors\":\"Gianmarco Canello, Silvia Mignardi, K. Mikhaylov, C. Buratti, T. Hänninen\",\"doi\":\"10.1109/EuCNC/6GSummit58263.2023.10188238\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Collecting data from Internet-of-Things (IoT) devices, especially the variety of sensors dispersed in the environment, is an increasingly important and difficult task. Several long-range radio-access technologies, such as low-power wide-area networks (LPWAN) and specifically LoRaWAN, have been proposed to address this challenge. However, until now, the key focus of the related studies has been on static terrestrial LPWAN deployments. In this study, we depart from this vision and investigate the practical feasibility and performance of a LoRaWAN gateway (GW) on a flying platform, specifically - an unmanned aerial vehicle (UAV). The key contributions of this study are (i) the design and field-testing of a packet-sniffer-based mobile LoRaWAN GW prototype, allowing collection of the data from LoRaWAN networks, including the already deployed ones; (ii) the open-publication of the data collected during our experimental campaign in the 426 LoRaWAN sensor node network of the University of Oulu illustrating the performance of different drone trajectories; (iii) the initial results of the system's performance analysis, revealing some interesting trends and setting goals for further studies, and pinpointing the lessons learned during the experimental campaign. Our empirical findings suggest that the Travelling Salesman Problem (TSP) trajectory is the most effective moving trajectory for the number of packets collected and the average energy consumed per packet collected.\",\"PeriodicalId\":65870,\"journal\":{\"name\":\"公共管理高层论坛\",\"volume\":\"4 1\",\"pages\":\"555-560\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-06-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"公共管理高层论坛\",\"FirstCategoryId\":\"96\",\"ListUrlMain\":\"https://doi.org/10.1109/EuCNC/6GSummit58263.2023.10188238\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"公共管理高层论坛","FirstCategoryId":"96","ListUrlMain":"https://doi.org/10.1109/EuCNC/6GSummit58263.2023.10188238","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Data collection from LoRaWAN sensor network by UAV gateway: design, empirical results and dataset
Collecting data from Internet-of-Things (IoT) devices, especially the variety of sensors dispersed in the environment, is an increasingly important and difficult task. Several long-range radio-access technologies, such as low-power wide-area networks (LPWAN) and specifically LoRaWAN, have been proposed to address this challenge. However, until now, the key focus of the related studies has been on static terrestrial LPWAN deployments. In this study, we depart from this vision and investigate the practical feasibility and performance of a LoRaWAN gateway (GW) on a flying platform, specifically - an unmanned aerial vehicle (UAV). The key contributions of this study are (i) the design and field-testing of a packet-sniffer-based mobile LoRaWAN GW prototype, allowing collection of the data from LoRaWAN networks, including the already deployed ones; (ii) the open-publication of the data collected during our experimental campaign in the 426 LoRaWAN sensor node network of the University of Oulu illustrating the performance of different drone trajectories; (iii) the initial results of the system's performance analysis, revealing some interesting trends and setting goals for further studies, and pinpointing the lessons learned during the experimental campaign. Our empirical findings suggest that the Travelling Salesman Problem (TSP) trajectory is the most effective moving trajectory for the number of packets collected and the average energy consumed per packet collected.