Abstract
This paper presents a case study of using an AI-based platform to monitor and manage urban infrastructure elements, such as waste containers and traffic lights, in a smart city. The platform leverages Internet of Things (IoT) technologies and MQTT protocol for data ingestion, preprocessing, analysis, and visualization. The case study demonstrates the ease of creating interactive visualizations and dashboards using the platform, enabling city officials and other stakeholders to monitor the status of various urban elements effectively, without the need for extensive technical knowledge or programming skills.
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Acknowledgment
This work has been partially supported by the project TED2021-132339B-C43 (idrECO), funded by MCIN/AEI/10.13039/501100011033 and by the European Union “NextGenerationEU”/PRTR.
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Pinto-Santos, F., González-Ramos, J.A., Curto, J., Alonso, R.S., Corchado, J.M. (2023). AI-Based Platform for Smart Cities Urban Infrastructure Monitorization. In: Ossowski, S., Sitek, P., Analide, C., Marreiros, G., Chamoso, P., Rodríguez, S. (eds) Distributed Computing and Artificial Intelligence, 20th International Conference. DCAI 2023. Lecture Notes in Networks and Systems, vol 740. Springer, Cham. https://doi.org/10.1007/978-3-031-38333-5_27
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