- Titel
- Data collection of rental bikes using a low power self-sufficient multisensorplatform
- Zitierfähige Url:
- https://nbn-resolving.org/urn:nbn:de:bsz:105-qucosa2-981291
- Konferenz
- Workshop on Autonomous Delivery and Service Robots on Pedestrian and Cycle Paths. Schkeuditz, Germany, 19.-20.05.2025
- Quellenangabe
- Collected Volume of the Workshop on Autonomous Delivery and Service Robots on Pedestrian and Cycle Paths
Erscheinungsort: Freiberg
Erscheinungsjahr: 2025 - Abstract (EN)
- To evaluate the readiness and suitability of cities for autonomous vehicles, environmental data is essential. The collection of various types of information contributes to the creation of maps that robots can use for navigation. Such measurements are gathered by electronic devices, including modern cars or public transportation systems. However, many frequently used routes beyond public roads are not tracked. This results in blind spots that may still be relevant for small self-driving systems. Using rental bikes to collect data in these areas allows for denser and more reliable data sets. Therefore, bikes are equipped with self-sufficient low-power sensor systems that acquire data on speed, ground quality, positional tracking, and obstacle detection. NarrowBand-Internet of Things (NB-IoT) is used to transmit the data collected to cloud services. Through the use of efficient algorithms and low-power modules, system up-time can exceed eight years. When different data transmission strategies are compared, the amount of data transmitted per battery charge can more than double. Data collected from multiple rental bikes provides valuable insight through route and sensor data comparison. Over extended periods, commonly used paths can be identified.
- Freie Schlagwörter (EN)
- low power, self sufficient, multisensor, rental bikes, data collecting, http, mqtt, narrowband iot, signal quality, micro machines, autonomous, operational durability
- Klassifikation (DDC)
- 004
- Normschlagwörter (GND)
- Fahrrad
- Multisensor
- Raumdaten
- Narrowband IoT
- Herausgeber (Institution)
- Technische Universität Bergakademie Freiberg, Freiberg
- Version / Begutachtungsstatus
- publizierte Version / Verlagsversion
- URN Qucosa
- urn:nbn:de:bsz:105-qucosa2-981291
- Veröffentlichungsdatum Qucosa
- 24.09.2025
- Dokumenttyp
- Konferenzbeitrag
- Sprache des Dokumentes
- Englisch
- Lizenz / Rechtehinweis
CC BY 4.0