Abstract
Water quality is an ongoing concern and wireless water quality sensing promises societal benefits. Our goal is to contribute to a low-cost water quality sensing system. The particular focus of this work is the selection of a database for storing water quality data. Recently, time series databases have gained popularity. This paper formulates criteria for comparison, measures selected databases and makes a recommendation for a specific database. A low-cost low-power server, such as a Raspberry Pi, can handle as many as 450 sensors’ data at the same time by using the InfluxDB time series database.
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Fadhel, M., Sekerinski, E., Yao, S. (2019). A Comparison of Time Series Databases for Storing Water Quality Data. In: Auer, M., Tsiatsos, T. (eds) Mobile Technologies and Applications for the Internet of Things. IMCL 2018. Advances in Intelligent Systems and Computing, vol 909. Springer, Cham. https://doi.org/10.1007/978-3-030-11434-3_33
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