Citywide Traffic Sensor Network in Nova Gorica, Slovenia 2025-2026 Telraam S2 Dataset
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| Format: | Recurso digital |
| Langue: | anglais |
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Zenodo
2026
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| _version_ | 1866902002424872960 |
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| author | Berčič, Tomaž |
| author_facet | Berčič, Tomaž |
| contents | <p>This dataset contains multimodal traffic counts collected by a network of 26 Telraam S2 sensors deployed across Nova Gorica, Slovenia, as part of the Interreg Central Europe EnCLOD project. Sensors were installed along arterial corridors, residential streets, and sections of the city's ring road, covering 23 indoor window-mounted units and 3 experimental outdoor units.</p> <p>Records are aggregated at 15-minute intervals and include directional counts for pedestrians, bicycles, motorcycles, cars, light trucks, trucks, buses, trailers, tractors, and strollers, as well as a nighttime detection category. Derived metrics include histograms of car speed (10 km/h bins) and the V85 speed per interval. Accompanying metadata cover sensor coordinates, street names, segment identifiers, installation type, uptime indicators, and calendar attributes.</p> <p>All processing is performed on-device; no images or videos are stored or transmitted. The data are fully anonymised and compliant with privacy regulations. Raw data were accessed via the Telraam REST API in JSON format and are archived here as structured CSV files.</p> <p>This is the first systematic, fine-grained traffic monitoring dataset for Nova Gorica. It is suitable for transport modelling, modal share analysis, speed behaviour assessment, and urban mobility planning, and may serve as a reference for comparable low-cost sensor deployments elsewhere in Europe.</p> <p>The data was produced under the Interreg CENTRAL Europe project EnCLOD, grant no. CE0200649 https://www.interreg-central.eu/projects/enclod/</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_19373042 |
| institution | Zenodo |
| language | eng |
| publishDate | 2026 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Citywide Traffic Sensor Network in Nova Gorica, Slovenia 2025-2026 Telraam S2 Dataset Berčič, Tomaž Traffic Cars Pedestrians Bicycles Large vehicles Vehicles EnCLOD Citizens science Nova Gorica <p>This dataset contains multimodal traffic counts collected by a network of 26 Telraam S2 sensors deployed across Nova Gorica, Slovenia, as part of the Interreg Central Europe EnCLOD project. Sensors were installed along arterial corridors, residential streets, and sections of the city's ring road, covering 23 indoor window-mounted units and 3 experimental outdoor units.</p> <p>Records are aggregated at 15-minute intervals and include directional counts for pedestrians, bicycles, motorcycles, cars, light trucks, trucks, buses, trailers, tractors, and strollers, as well as a nighttime detection category. Derived metrics include histograms of car speed (10 km/h bins) and the V85 speed per interval. Accompanying metadata cover sensor coordinates, street names, segment identifiers, installation type, uptime indicators, and calendar attributes.</p> <p>All processing is performed on-device; no images or videos are stored or transmitted. The data are fully anonymised and compliant with privacy regulations. Raw data were accessed via the Telraam REST API in JSON format and are archived here as structured CSV files.</p> <p>This is the first systematic, fine-grained traffic monitoring dataset for Nova Gorica. It is suitable for transport modelling, modal share analysis, speed behaviour assessment, and urban mobility planning, and may serve as a reference for comparable low-cost sensor deployments elsewhere in Europe.</p> <p>The data was produced under the Interreg CENTRAL Europe project EnCLOD, grant no. CE0200649 https://www.interreg-central.eu/projects/enclod/</p> |
| title | Citywide Traffic Sensor Network in Nova Gorica, Slovenia 2025-2026 Telraam S2 Dataset |
| topic | Traffic Cars Pedestrians Bicycles Large vehicles Vehicles EnCLOD Citizens science Nova Gorica |
| url | https://doi.org/10.5281/zenodo.19373042 |