Smart River Platform - River Quality Monitoring and Environmental Awareness

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Optimization, Learning Algorithms and Applications (OL2A 2021)

Abstract

In the technology communication era, the use of the Internet of Things (IoT) has become popular among other digital solutions, since it offers the integration of information from several organisms and at several sources. By means of this, we can access data from distant locations and at any time. In the specific case of water monitoring, the conventional outdated measurement methods can lead to low efficiency and complexity issues. Hence, Smart systems rise as a solution for a broad of cases. Smart River is a smart system platform developed to optimize the resources and monitoring the quality of water parameters of the Fervença river. The central solution is based at Centro Ciência Viva de Bragança (CCVB), one of the 21 science centers in Portugal that aims to promote the preservation and environmental awareness for the population. By using the IoT technologies, the system allows real-time data collection with low cost and low energy consumption, being a complement of existing projects that are being developed to promote the ecological importance of natural resources. This paper covers sensor module selection for data collection inside the river and data storage. The parameters of the river are visualized using a program developed in Unity engine to present data averages and comparison between weeks, months, and years.

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Acknowledgments

This work has also been supported by Fundação La Caixa within the Project Scope: Natureza Virtual, and FCT - Fundação para a Ciência e Tecnologia within the Project Scope: UIDB/05757/2020.

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Correspondence to Ana I. Pereira .

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Cabanga, K.P. et al. (2021). Smart River Platform - River Quality Monitoring and Environmental Awareness. In: Pereira, A.I., et al. Optimization, Learning Algorithms and Applications. OL2A 2021. Communications in Computer and Information Science, vol 1488. Springer, Cham. https://doi.org/10.1007/978-3-030-91885-9_34

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  • DOI: https://doi.org/10.1007/978-3-030-91885-9_34

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