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L.C. Dechamps
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2 records found
1
Master thesis
(2024)
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L.C. Dechamps, G. Agugiaro, J.E. Stoter, B. van Loenen, L.G.G. Olde Scholtenhuis
Utility networks are critical components of urban infrastructure, providing essential services such as water supply, electricity, gas, and telecommunications. The traditional method for mapping these networks is typically two-dimensional (2D) schematic representations rather than topographically and geometrically correct maps. These representations lack the capacity to convey the complexity and vertical intricacies of urban infrastructures. This limitation hampers comprehensive planning, efficient management, and risk mitigation during construction activities because 2D maps do not effectively represent the multi-layered and interconnected nature of urban utilities, leading to potential oversights and inaccuracies. This thesis addresses the challenge of enriching utility network data by integrating detailed data from utility trench surveys. These surveys provide precise positional and attribute information about utilities that are often missing in standard maps, such as the exact depth, spatial configuration, and physical characteristics of the utility lines.
Data from utility trenches in three Dutch cities—Enschede, Rotterdam, and Amsterdam—was acquired and analyzed. Methodologies were developed to extract, standardize, and integrate this data into existing utility network maps, enhancing their semantic content and spatial accuracy. The research demonstrated that integrating trench data can reveal inaccuracies in traditional utility network maps at the utility trench locations.
Key findings include the development of algorithms for extracting and processing utility trench data, the identification of common challenges between cities such as cable/pipeline labeling inconsistencies, and the comparison of enriched utility data and that of traditional utility networks. The research also highlights the importance of standardizing data models and the potential of three-dimensional models to provide a more comprehensive understanding of utility networks. A resulting recommendation was to improve data collection by including all information found and providing properly geo-referenced data. ...
Data from utility trenches in three Dutch cities—Enschede, Rotterdam, and Amsterdam—was acquired and analyzed. Methodologies were developed to extract, standardize, and integrate this data into existing utility network maps, enhancing their semantic content and spatial accuracy. The research demonstrated that integrating trench data can reveal inaccuracies in traditional utility network maps at the utility trench locations.
Key findings include the development of algorithms for extracting and processing utility trench data, the identification of common challenges between cities such as cable/pipeline labeling inconsistencies, and the comparison of enriched utility data and that of traditional utility networks. The research also highlights the importance of standardizing data models and the potential of three-dimensional models to provide a more comprehensive understanding of utility networks. A resulting recommendation was to improve data collection by including all information found and providing properly geo-referenced data. ...
Utility networks are critical components of urban infrastructure, providing essential services such as water supply, electricity, gas, and telecommunications. The traditional method for mapping these networks is typically two-dimensional (2D) schematic representations rather than topographically and geometrically correct maps. These representations lack the capacity to convey the complexity and vertical intricacies of urban infrastructures. This limitation hampers comprehensive planning, efficient management, and risk mitigation during construction activities because 2D maps do not effectively represent the multi-layered and interconnected nature of urban utilities, leading to potential oversights and inaccuracies. This thesis addresses the challenge of enriching utility network data by integrating detailed data from utility trench surveys. These surveys provide precise positional and attribute information about utilities that are often missing in standard maps, such as the exact depth, spatial configuration, and physical characteristics of the utility lines.
Data from utility trenches in three Dutch cities—Enschede, Rotterdam, and Amsterdam—was acquired and analyzed. Methodologies were developed to extract, standardize, and integrate this data into existing utility network maps, enhancing their semantic content and spatial accuracy. The research demonstrated that integrating trench data can reveal inaccuracies in traditional utility network maps at the utility trench locations.
Key findings include the development of algorithms for extracting and processing utility trench data, the identification of common challenges between cities such as cable/pipeline labeling inconsistencies, and the comparison of enriched utility data and that of traditional utility networks. The research also highlights the importance of standardizing data models and the potential of three-dimensional models to provide a more comprehensive understanding of utility networks. A resulting recommendation was to improve data collection by including all information found and providing properly geo-referenced data.
Data from utility trenches in three Dutch cities—Enschede, Rotterdam, and Amsterdam—was acquired and analyzed. Methodologies were developed to extract, standardize, and integrate this data into existing utility network maps, enhancing their semantic content and spatial accuracy. The research demonstrated that integrating trench data can reveal inaccuracies in traditional utility network maps at the utility trench locations.
Key findings include the development of algorithms for extracting and processing utility trench data, the identification of common challenges between cities such as cable/pipeline labeling inconsistencies, and the comparison of enriched utility data and that of traditional utility networks. The research also highlights the importance of standardizing data models and the potential of three-dimensional models to provide a more comprehensive understanding of utility networks. A resulting recommendation was to improve data collection by including all information found and providing properly geo-referenced data.
“Adsum ergo sum.” I am here, therefore I am
Indoor localisation for blind people with use of LiDAR scanning and ArcGIS Indoors
Student report
(2022)
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L.C. Dechamps, M.I. van Esch, M. Hengelmolen, L.W.L. Kan, Y. YANG, E. Verbree, N. van der Vaart, V.P. van Altena
Blind and visually impaired people currently have inconveniences locating themselves in the indoor environment. No standardized system exists for them yet. After an inventory of the requirements of blind people, different representations do qualify for providing specific information blind people need. The main research question is: "How can blind people localise themselves (near) real-time in indoor environments with the combination of 3 representations of reality, namely (1) LiDAR point cloud matching, (2) ArcGIS Indoors and (3) Audio dynamic tactile map as the user interface?". Room detection and positioning of the user within the room are obtained by LiDAR scanning and point cloud matching. The processed point cloud height raster grids are acquired and imported into the Esri ArcGIS platform. The rooms are geo-referenced, and data is enriched by contextual awareness. As a user interface for blind people this report proposes two deliverables: a dynamic tactile map and an added or stand-alone audible supported user interface. Preliminary results of the qualitative validation show positive outcomes. This report is a stepping stone for the possibility of integrating multiple into one device.
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Blind and visually impaired people currently have inconveniences locating themselves in the indoor environment. No standardized system exists for them yet. After an inventory of the requirements of blind people, different representations do qualify for providing specific information blind people need. The main research question is: "How can blind people localise themselves (near) real-time in indoor environments with the combination of 3 representations of reality, namely (1) LiDAR point cloud matching, (2) ArcGIS Indoors and (3) Audio dynamic tactile map as the user interface?". Room detection and positioning of the user within the room are obtained by LiDAR scanning and point cloud matching. The processed point cloud height raster grids are acquired and imported into the Esri ArcGIS platform. The rooms are geo-referenced, and data is enriched by contextual awareness. As a user interface for blind people this report proposes two deliverables: a dynamic tactile map and an added or stand-alone audible supported user interface. Preliminary results of the qualitative validation show positive outcomes. This report is a stepping stone for the possibility of integrating multiple into one device.