Abstract
Water is one of the main natural resources for humanity and it is important for countries to be aware of the water quality. The physical, chemical and biological parameters provide information on the current condition of surface waters used for municipal, industrial and agricultural water supply. Thus, the design and development of equipment used for water quality monitoring and analysis are essential to avoid dangerous situations. Feedback sources from the monitoring equipment are the main interface between the study area and the specialists. This equipment must have the necessary features and tools to achieve an optimal water quality analysis. This study proposes a desktop application design to support the management of water quality monitoring equipment. The design was developed based on the methodology and stages of User Centered Design from the ISO 9241-210-2019 standard. The evaluation of the prototype was done using the question technique and task assignment. The results showed a quick adaptability and easy navigation by users. In addition, the implementation of a Machine Learning algorithm showed preliminary results of water quality prediction.
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Guzman-Fernandez, M. et al. (2021). Desktop Application for Water Quality Prediction and Monitoring System Using ISO 9241-210 and Machine Learning Techniques. In: Ruiz, P.H., Agredo-Delgado, V., Kawamoto, A.L.S. (eds) Human-Computer Interaction. HCI-COLLAB 2021. Communications in Computer and Information Science, vol 1478. Springer, Cham. https://doi.org/10.1007/978-3-030-92325-9_4
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