Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.11960/3154
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dc.contributor.authorPasandi, Hannaneh Barahouei-
dc.contributor.authorHaqiqat, Asma-
dc.contributor.authorMoradbeikie, Azin-
dc.contributor.authorKeshavarz, Ahmad-
dc.contributor.authorRostami, Habib-
dc.contributor.authorPaiva, Sara-
dc.contributor.authorLopes, Sérgio Ivan-
dc.date.accessioned2023-01-27T11:24:28Z-
dc.date.available2023-01-27T11:24:28Z-
dc.date.issued2022-
dc.identifier.citationPasandi, H. B., Haqiqat, A., Moradbeikie, A., Keshavarz, A., Rostami, H., Paiva, S., & Lopes, S. I. (2022). Low-cost traffic sensing system based on LoRaWAN for urban areas. In EmergingWireless ’22: Proceedings of the 1st International Workshop on Emerging Topics in Wireless, December 9, 2022, Italy (pp. 6-11). ACM. https://doi.org/10.48550/arXiv.2211.00992pt_PT
dc.identifier.isbn978-145039934-0-
dc.identifier.urihttp://hdl.handle.net/20.500.11960/3154-
dc.description.abstractThe advent of Low Power Wide Area Networks (LPWAN) has enabled the feasibility of wireless sensor networks for environmental traffic sensing across urban areas. In this study, we explore the usage of LoRaWAN end nodes as traffic sensing sensors to offer a practical traffic management solution. The monitored Received Signal Strength Indicator (RSSI) factor is reported and used in the gateways to assess the traffic of the environment. Our technique utilizes LoRaWAN as a long-range communication technology to provide a large-scale system. In this work, we present a method of using LoRaWAN devices to estimate traffic flows. LoRaWAN end devices then transmit their packets to different gateways. Their RSSI will be affected by the number of cars present on the roadway. We used SVM and clustering methods to classify the approximate number of cars present. This paper details our experiences with the design and real implementation of this system across an area that stretches for miles in urban scenarios. We continuously measured and reported RSSI at different gateways for weeks. Results have shown that if a LoRaWAN end node is placed in an optimal position, up to 96% of correct environment traffic level detection can be obtained. Additionally, we share the lessons learned from such a deployment for traffic sensing.pt_PT
dc.language.isoengpt_PT
dc.publisherACMpt_PT
dc.rightsopenAccesspt_PT
dc.subjectRSSIpt_PT
dc.subjectTraffic sensingpt_PT
dc.subjectLoRaWANpt_PT
dc.subjectSmart citiespt_PT
dc.titleLow-cost traffic sensing system based on LoRaWAN for urban areaspt_PT
dc.typeconferenceObjectpt_PT
dc.date.updated2023-01-26T12:40:37Z-
dc.description.version5311-8814-F0ED | Sara Maria da Cruz Maia de Oliveira Paiva-
dc.description.versionN/A-
dc.identifier.slugcv-prod-3127080-
dc.peerreviewedyespt_PT
degois.publication.firstPage6pt_PT
degois.publication.lastPage11pt_PT
degois.publication.titleEmergingWireless ’22: Proceedings of the 1st International Workshop on Emerging Topics in Wirelesspt_PT
degois.publication.locationItalypt_PT
dc.identifier.doi10.48550/arXiv.2211.00992-
dc.identifier.eid2-s2.0-85142527018-
Appears in Collections:ESTG - Artigos indexados à WoS/Scopus

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