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WaterExcVA: a system for exploring and visualizing data exception in urban water supply


In order to ensure the safety of water use and the stability of enterprise production, water affairs experts need to analyze the water supply data in time and make timely decisions on abnormal conditions. However, experts are faced with great challenges in decision-making, because with the continuous development of Internet of things technology, the amount of water affairs data and the types of related data is increasing rapidly, which makes decision-making require many human resources and time. This situation prompted us to cooperate with experts and put forward a visualization system based on data analysis of urban water supply network system. There are three main challenges in developing such a system: (1) deep analysis of complex supply water data generated by the water supply network; (2) interactive generation of data comparison scheme; (3) effective methods for analyzing the abnormal causes. For challenge 1, we use customizable visual views from the whole to the details, which can customize and stratify the complex water structure system, so as to effectively explore the abnormal facilities and equipment. For challenge 2, we provide rich interaction methods to facilitate exploring water data according to users’ interests. For challenge 3, we introduce the strategy of influence degree parameter to help users analyze the influence degree of different factors on water affairs data, and help users find the causes of anomalies. Based on the actual business needs of the water supply industry and the data of the water supply network, we evaluated the WaterExcVA system through case studies, proved the applicability and practicability of the system, and communicated with water experts, obtaining positive feedback.

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This work was supported in part by Provincial Key Research and Development Program of Anhui of China (201904d07020010), the Science and Technology Program of Huangshan of China (2019KN-05), the Anhui Key Laboratory of Intelligent Building and Building Energy Conservation of Anhui Jianzhu University (IBES2021KF05), and the Scientific and Technological Achievement Cultivation Project of Intelligent Manufacturing Research Institute of Hefei University of Technology (IMIPY2021022).

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Correspondence to Qiang Lu.

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Lu, Q., Ge, Y., Rao, J. et al. WaterExcVA: a system for exploring and visualizing data exception in urban water supply. J Vis (2023).

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  • Visual analysis
  • Graphic design
  • Intelligent water affairs
  • Visualization