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dc.contributor.authorWang, Shie-Yuanen_US
dc.contributor.authorZou, Ji-Jheen_US
dc.contributor.authorChen, Yo-Ruen_US
dc.contributor.authorHsu, Chun-Chiaen_US
dc.contributor.authorCheng, Yu-Hsiangen_US
dc.contributor.authorChang, Chia-Hungen_US
dc.date.accessioned2020-10-05T02:00:31Z-
dc.date.available2020-10-05T02:00:31Z-
dc.date.issued2018-01-01en_US
dc.identifier.isbn978-1-5386-6355-4en_US
dc.identifier.urihttp://hdl.handle.net/11536/155037-
dc.description.abstractRecently, LoRa/LoRaWAN has been proposed as a promising LPWAN technology for Internet-of-Things (IoT) applications. For monitoring the long-term PM2.5 air quality on our campus, starting from February 1 2017, we have set up a LoRaWAN-based PM2.5 air quality monitoring system on our campus. In total, twenty-two PM2.5 sensor devices have been operating at the rooftop of buildings or on the lamp poles since then. Each of these PM2.5 sensor devices uses a LoRaWAN module to send its most recent PM2.5 value to the LoRaWAN gateway every 72 seconds. After being received successfully by the LoRaWAN gateway, the packets carrying these values were stored into a database with their SNR/RSSI information. With the sequence numbers added by our PM2.5 application running on each device, the packets stored in the database provide many important information about the long-term packet loss rate performance of LoRaWAN on campus. In this paper, we process these data to report real long-term performance of LoRaWAN when used on campus.en_US
dc.language.isoen_USen_US
dc.subjectLPWANen_US
dc.subjectLoRaWANen_US
dc.subjectLoRaen_US
dc.titleLong-Term Performance Studies of a LoRaWAN-based PM2.5 Application on Campusen_US
dc.typeProceedings Paperen_US
dc.identifier.journal2018 IEEE 87TH VEHICULAR TECHNOLOGY CONFERENCE (VTC SPRING)en_US
dc.citation.spage0en_US
dc.citation.epage0en_US
dc.contributor.department資訊工程學系zh_TW
dc.contributor.departmentDepartment of Computer Scienceen_US
dc.identifier.wosnumberWOS:000541851800023en_US
dc.citation.woscount0en_US
Appears in Collections:Conferences Paper