Combining model-driven engineering and sewerage networks: towards a generic representation

Yassine Bel-Ghaddar, Abderrahmane Seriai, Ahlame Begdouri, C. Delenne, N. Chahinian, Mustapha Derras
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Abstract

Representing and processing digital data related to underground networks, particularly sewerage networks, is increasingly becoming a priority for the managers of these networks. Indeed, better representation would allow them, among others, to improve knowledge and to take the best decisions regarding these generally poorly identified infrastructures. The heterogeneity of data and the multiplicity of data models representing sewerage networks, often specific to each operator, as well as the imperfections associated with both the available data and those collected from different sources, generate complexity in terms of on-the-field interventions' efficiency. They also highlight the need for aggregation (unification), control and analysis. The main objective of our work is to merge multi-source data to obtain more precise and complete digital maps of sewerage networks. In this paper, we propose a generic data modelling for data fusion purposes taking into consideration the uncertainty aspects related to the collected data by allowing a confidence value for each data source and for each single data provided by a source.
结合模型驱动工程和污水管网:走向通用表示
表示和处理与地下网络,特别是污水网络有关的数字数据,正日益成为这些网络管理人员的优先事项。事实上,更好的代表权将使他们,除其他外,能够增进知识,并对这些通常不太确定的基础设施作出最佳决定。数据的异质性和代表污水管网的数据模型的多样性(通常针对每个运营商),以及与可用数据和从不同来源收集的数据相关的不完善,在现场干预的效率方面产生了复杂性。它们还强调了对聚合(统一)、控制和分析的需求。我们工作的主要目标是合并多源数据,以获得更精确和完整的污水管网数字地图。在本文中,我们提出了一种用于数据融合目的的通用数据建模,考虑到与收集数据相关的不确定性方面,允许每个数据源和数据源提供的每个单个数据的置信度值。
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