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Cervoneac, Andrei, Marques, Rhonny Javier Diaz, Korca, Meri Kortsa Or, Rokossa, Felix, Dunsin, Dipo, Das, Sonjoy Ranjon and Hassan, Bilal (2026) RaspDash: a cloud-Internet of Things (IoT) for smart parking solution with predictive analytics. In: 2025 8th Conference on Cloud and Internet of Things (CIoT), 29-31 October 2025, London, United Kingdom.
This short paper presents the development and deployment of an Internet of Things (IoT)-based smart parking system that integrates edge computing with Microsoft Azure cloud services. Utilizing a Raspberry Pi and ultrasonic sensor for real-time vehicle detection, the system transmits data to Azure IoT Hub, where it is processed via Azure Stream Analytics and stored in Azure Structured Query Language (SQL) Database. A machine learning model predicts peak parking hours, and the results are visualized through a custom web dashboard, RaspDash. The architecture prioritizes costefficiency, scalability, and performance optimization, providing a viable solution for intelligent parking management in urban environments.
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