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Scientific Article details

Title A Cloud-Based Data Storage and Visualization Tool for Smart City IoT: Flood Warning as an Example Application
ID_Doc 38890
Authors Sobral, VAL; Nelson, J; Asmare, L; Mahmood, A; Mitchell, G; Tenkorang, K; Todd, C; Campbell, B; Goodall, JL
Title A Cloud-Based Data Storage and Visualization Tool for Smart City IoT: Flood Warning as an Example Application
Year 2023
Published Smart Cities, 6, 3
DOI 10.3390/smartcities6030068
Abstract Collecting, storing, and providing access to Internet of Things (IoT) data are fundamental tasks to many smart city projects. However, developing and integrating IoT systems is still a significant barrier to entry. In this work, we share insights on the development of cloud data storage and visualization tools for IoT smart city applications using flood warning as an example application. The developed system incorporates scalable, autonomous, and inexpensive features that allow users to monitor real-time environmental conditions, and to create threshold-based alert notifications. Built in Amazon Web Services (AWS), the system leverages serverless technology for sensor data backup, a relational database for data management, and a graphical user interface (GUI) for data visualizations and alerts. A RESTful API allows for easy integration with web-based development environments, such as Jupyter notebooks, for advanced data analysis. The system can ingest data from LoRaWAN sensors deployed using The Things Network (TTN). A cost analysis can support users' planning and decision-making when deploying the system for different use cases. A proof-of-concept demonstration of the system was built with river and weather sensors deployed in a flood prone suburban watershed in the city of Charlottesville, Virginia.
Author Keywords Internet of Things; smart cities; environmental monitoring; LoRaWAN; cloud computing; AWS; data management; cost analysis
Index Keywords Index Keywords
Document Type Other
Open Access Open Access
Source Emerging Sources Citation Index (ESCI)
EID WOS:001015823300001
WoS Category Engineering, Electrical & Electronic; Urban Studies
Research Area Engineering; Urban Studies
PDF https://www.mdpi.com/2624-6511/6/3/68/pdf?version=1684481813
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