An indoor logical network qualitatively represents abstract relationships between indoor spaces, and it can be used for path computation. In this paper, we concentrate on the logical network that does not have notions for metrics. Instead, it relies on the semantics and properties of indoor spaces. A navigation path can be computed by deriving parameters from these semantics and minimizing them in routing algorithms. Although previous studies have adopted semantic approaches to build logical networks, routing methods are seldom elaborated. The main issue with such networks is to derive criteria for path computation using the semantics of spaces. Here, we present a routing mechanism that is based on a dedicated space classification and a set of routing criteria. The space classification reflects characteristics of spaces that are important for navigation, such as horizontal and vertical directions, doors and windows, etc. Six routing criteria are introduced, and they involve: (1) the spaces with the preferred semantics; and/or (2) their centrality in the logical network. Each criterion is encoded as the weights to the nodes or edges of the logical network by considering the semantics of spaces. Logical paths are derived by a traditional shortest-path algorithm that minimizes these weights. Depending on the building’s interior configuration, one criterion may result in several logical paths. Therefore, we introduce a priority ordering of criteria to support path selection and decrease the possible number of logical paths. We provide a proof-of-concept implementation for several buildings to demonstrate the usability of such a routing. The main benefit of this routing method is that it does not need geometric information to compute a path. The logical network can be created using verbal descriptions only, and this routing method can be applied to indoor spaces derived from any building subdivision.

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Excavation work takes place almost continually in most cities around the Western hemisphere. Many cities are already full of infrastructures, buried networks, and street furniture, so excavation work is not without any thread to the operator and surrounding environment. Small construction sites, for example, are often constrained by operating infrastructure on surface level and underground. Although different agencies and network owners have information about the location of the objects that put excavation work at risk, this information is not centralized. Different organizations manage location information of buried cables, unexploded ordnance, and pollution, for example. This significantly complicates the early-stage planning and last minute risk assessment processes because professionals need to manually collect, assess, and integrate data about subsurface objects into a comprehensive risk assessment. To smoothen this process, ExcaSafeZone project, therefore, develops a system that collects location data, defines expert-based rules for safety risk assessment, and that synthesizes this into an open source prototype that visualized safety risks on a heat map.

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This paper proposes an initial LADM country profile of Saudi Arabia. The model aims to build a better communication system between all the stockholders to secure the land registration. The initial development of the spatial and non-spatial classes are have been based on the regulation of Saudi Arabia. For the development of the LADM profile for Saudi Arabia, several steps have been completed: 1- Interviews have been conducted with the stakeholders to collect information about the regulations of the land/building ownership. 2- Analysis of the current system of the land registration and its requirement for both spatial and non-spatial data has been performed. 3- Local regulations have been utilized to develop the initial LADM country profile.@en

Generation of indoor networks for navigation will normally be done out of standard floor plans that are only 2D and is more often manual than automatic. These floor plans are drawn at a specific time and do not correspond to the reality, moreover some of those buildings were built already differently than designed. Then in due course the building will change both externally and internally. Also objects like furniture will be moved around in the building. If these changes are not updated in the map of the building, it becomes out of date and cannot be used for the creation of indoor navigable models anymore. To enable correct indoor navigation, we will need to have the current data of the indoor environment. This article concentrates on providing a new approach to generate up to date floor plans by using a mobile (and hand held) laser scanner in the fastest way. This device creates a point cloud and the corresponding trajectory at the same time. Because the mobile laser scanner device is operated by a walking human, the trajectory contains information about the surface the person is walking on. In this article, a method is explained for the detection of walkable spaces based on the analysis of the point cloud and its corresponding trajectory provided by the mobile laser scanner. Three steps will be used: voxelization, trajectory analysis and the identification of floor regions. Dynamic objects, doors, and furniture objects are also used to identify the surfaces which are available for navigation purposes. Three types of surfaces are considered: horizontal, slopes, and stairs.@en

This paper presents the development of database for the conceptual model of LADM-IndoorGML. The aim of this work is to investigate all issues that related to generating the database and visualizing the content of the database. Based on the result of the transformation from conceptual model to the technical model that has been proposed by (Alattas et al., 2018), we have selected some classes of the conceptual model of LADM-IndoorGML to create a database in PostgreSQL with the extension of PostGIS. By converting those classes from class diagram to SQL DDL, a database has been generated and stored different type of data. A visualization tool has been used to visualize indoor spaces based on RRRs for the users.@en

3D indoor navigation in multi-story buildings and under changing environments is still difficult to perform. 3D models of buildings are commonly not available or outdated. 3D point clouds turned out to be a very practical way to capture 3D interior spaces and provide a notion of an empty space. Therefore, pathfinding in point clouds is rapidly emerging. However, processing of raw point clouds can be very expensive, as these are semantically poor and unstructured data. In this article we present an innovative octree-based approach for processing of 3D indoor point clouds for the purpose of multi-story pathfinding. We semantically identify the construction elements, which are of importance for the indoor navigation of humans (i.e., floors, walls, stairs, and obstacles), and use these to delineate the available navigable space. To illustrate the usability of this approach, we applied it to real-world data sets and computed paths considering user constraints. The structuring of the point cloud into an octree approximation improves the point cloud processing and provides a structure for the empty space of the point cloud. It is also helpful to compute paths sufficiently accurate in their consideration of the spatial complexity. The entire process is automatic and able to deal with a large number of multi-story indoor environments.

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This paper shows the conversion of LADM-IndoorGML conceptual model to technical model. The aim of this research is assessing the conceptual model and discovering the possibilities and the shortcomings of the conceptual model via the conversion to technical model. There are three steps to convert the conceptual model: - Prepare the LADM-IndoorGML UML model; - Transform the class diagram to table diagram; - Generate SQL DDL code from the table diagram. During the work from step to step several issues did appear and they are addressed in this paper to enable more automated transformation possibilities from the conceptual model to technical mode. Most of the issues are quite generic and also applicable when converting other conceptual models into technical models. There are a few issues related to our specific conceptual models (IndoorGML and LADM packages) and the Enterprise Architect software (which is the used tool in our case), but most issues are generic: the primary keys that have been created to all tables by the software even if there an ID attributes, foreign keys, the association multiplicity, the attributes multiplicity, data type, spatial data type, index, spatial index, constraints, and inheritance. The research shows that there is a need to develop a complete UML diagram for IndoorGML that contain all the attributes and their datatypes. The current class structure of the code list in LADM standard has been developed for better semantic meaning during the implementation by creating an intermediate conceptual model class to support the transformation. Many critical decisions have been taken during the derivation of the technical model to solve these issues.@en

With the increasing number of indoor navigation applications, it is essential to have clear and complete conceptual model (in the form of UML class diagram) for IndoorGML. The current version of IndoorGML standard has an incomplete class diagram (incomplete w.r.t. attributes, of which some are appearing in the XML/GML schema), and that provides confusion for the users of the standard. Furthermore, there are some issues related to unclear association names, unclear class names, classes that related to the Primal space and the Dual space, code lists not specific per type (which should have their own code list values), untyped relationships to external object classes, and semantically overlapping classes. In this paper, we propose an enhancement for IndoorGML conceptual model (UML class diagram) to avoid the misunderstanding. We propose a conceptual model that maps the classes of the standard in a better way. This conceptual model is the basis for 1) a database schema when storing IndoorGML data, 2) the XML schema when exchanging IndoorGML data, and 3) when developing IndoorGML applications with an intuitive and clear GUI. Furthermore, the proposed conceptual model provides constraints for more meaningful model and to define more sharply what is considered valid data. This paper briefly reports these preliminary results on the UML conceptual model.@en

As we realize that we spend most of our time in increasingly complex indoor environments, applications to assist indoor activities (e.g. guidance) have gained a lot of attention in the recent years. The advances in ubiquitous computing made possible the development of several spatial models intending to support context-aware and fine-grained indoor navigation systems. However, the available models often rely on simplified representations (e.g. 2D plans) and ignore the indoor features (e.g. furniture), thereby missing to reflect the complexity of the indoor environment. In this paper, we introduce the Flexible Space Subdivision framework (FSS) that allows to automatically identify the spaces that can be used for indoor navigation purpose. We propose a classification of indoor objects based on their ability to autonomously change location and we define a spatial subdivision of the indoor environment based on the classified objects and their functions. The framework can consider any 3D indoor configuration, the static and dynamic activities it hosts and it enables the possibility to consider all types of locomotion (e.g. walking, flying, etc.). It relies on input 3D models with geometric, semantic and topological information and identifies a set of subspaces with dedicated properties. We assess the framework against criteria defined in previous researches and we provide an example.

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Precise and comprehensive knowledge about 3D urban space is required for simulation and analysis in the fields of urban and environmental planning, city administration and disaster management. In order to facilitate these applications, geo-information about functional, semantic, and topographic aspects of urban features, their mutual dependencies and relations is needed. Substantial work has been done in the modelling and representation of above-ground features in the context of 3D city modelling. However, the belowground part of the real world, of which utility networks form a big part, is often neglected. Existing data models for utility networks are generally very domain-specific and, therefore, not suitable either. This paper describes a 3D data modelling approach for integrated management of below-ground utility networks and related above-ground city objects. This approach consists of manipulating first the structure of existing utility data in the commonly used Feature Manipulation Engine ETL software in order to make the data compliant to the CityGML Utility Network ADE data model. Subsequently, workspaces are created that take care of storing the CityGML data into the free and open-source 3D City Database, which has been extended in order to manage utility network data, too. Moreover, the research shows the suitability of the extended 3DCityDB to perform graph-based topological operations by means of the PostgreSQL pgRouting extension. Lastly, the results are visualized in typical GIS applications, e.g. QGIS and ArcGIS.

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Visibility is a common measure to describe the spatial properties of an environment related to the spatial behaviour. Isovists represent the space that can be seen from one observation point, and they are used to analyse the existence of obstacles affecting or blocking intervisibility in an area. Although point clouds depict the as-built reality in a very detailed and accurate way, literature addressing the analysis of visibility in 3D, and more specifically the usage of point clouds to visibility analysis, is rather limited. In this paper, a methodology to evaluate visibility from point clouds in indoor environments is proposed, resulting in the creation of 3D isovists. Point cloud is firstly discretized in a voxel-based structure and voxels are labelled into ‘exterior’, ‘occupied’, ‘visible’ and ‘occluded’ based on an occupancy followed by a visibility analysis performed from a ray-tracing algorithm. 3D Isovists are created from the boundary of visible voxels from an observer position and considering as input parameters the visual angle, maximum line of sight, and eye gaze direction.@en

Subdivision of land parcels in the vertical space has made it necessary for cadastral jurisdictions to manage cadastral objects both in 2D as well as 3D. Modern sensor and hardware capabilities for capture and utilisation of large point clouds is one of the major drivers to consider Spatial Database Management Systems (SDBMS) in 3D and organisations are still progressing towards it. 3D data models and their topological relationships are two of the important parts of 3D spatial data management. 3D spatial systems should enable data models that handle a large variety of 3D objects, perform automated data quality checks, search and analysis, rapid data dissemination, 3D rendering and visualisation with close linkages to standards. This chapter asserts that while there has been work done in defining 2D and 3D vector geometry in standards, it is still not sufficient for 3D cadastre purposes as 3D cadastral objects have a much more rigorous definition. The Land Administration Domain Model (LADM), which is an ISO Standard, addresses many of the issues in 3D representation and storage of 3D data in a database management system (DBMS). The chapter further discusses the various approaches to storing 3D data such as through voxels, or point cloud data type and elaborates on the characteristics of a 3D DBMS capable of storing 3D data. Approaches for spatial indexing to improve the fast access of data and the various available options for a 3D geographical database system are presented. Several spatial operations on and amongst 3D objects are illustrated with linkages to the current standards including the LADM. Next, construction of 3D topological and geometrical models based on standards and including their characteristics is discussed. Current 3D spatial database managements systems and their characteristics, including some comparison between selected DBMS including the hardware capabilities are elaborated in detail. Finally, the chapter proposes a 3D topology model based on Tetrahedron Network (TEN) synchronised with LADM specifications for 3D cadastral registration. This topological model utilises surveying boundaries to generate 3D cadastral objects with consistent topology and rapid query and management capabilities. The definition for validation of 3D solids also considers the automatic repair of invalid solids. Point cloud and TEN related data structures available in SDBMSs are also investigated to enable storage of non-spatial attributes so that database updates would store all spatial and attribute information directly inside the spatial database.@en

In this chapter we address various aspects of 3D Cadastral Information Modelling. Of course, this is closely related to the legal framework and initial registration as presented in the first two chapters. Cadastral data models, such as the Land Administration Domain Model, which include 3D support, have been developed for legal information modelling and management purposes without providing correspondence to the object’s physical counterparts. Building Information Models and virtual 3D topographic/ city models (e.g. LandXML, InfraGML, CityGML, IndoorGML) can be used to describe the physical reality. The main focus of such models is on the physical and functional characteristics of urban structures (Aien et al, 2015). However, by definition, those two aspects need to be interrelated; i.e. a tunnel, a building, a mine, etc. always have both a legal status and boundaries as well as a physical description; while it is evident that their integration would maximise their utility and flexibility to support different applications. A model driven architecture approach, including the formalization of constraints is preferred. In the model driven architecture design approach as proposed by the Object Management Group the information model, often expressed in the form of a UML class diagram is the core of the development. This so-called Platform Independent Model (PIM, as presented in the current chapter) is then transformed into Platform Specific Model (PSM). This could be a relational database schema for a spatial DBMS (as will be discussed in the next chapter), or XML schema for a data exchange format or the structure of maps, forms and tables as used in the graphic user interface of a spatial application. Constraints have proved effective in providing the solutions needed to avoid errors and enable maintenance of data quality; thus the need to specify and implement them. This chapter explores possibilities of linking 3D legal right, restriction, responsibilities spaces, modelled with the Land Administration Domain Model (ISO 19152), with physical reality of 3D objects (described via CityGML, IFC, InfraGML, etc).@en

3-D modeling has been the subject of increased attention in the last two decades. Technology has been developed to such a degree that large datasets can be collected, processed, analyzed, managed, and visualized in reasonable time. Domain applications are looking with much interest at 3-D representations, acknowledging the increased possibilities for display and analysis of data. The tendency of using 3-D data from different domains in one application is growing, and this poses many challenges. Developed independently through the years, 3-D applications involve various representations (vector, raster, freeform curves, and surfaces), levels of detail, appearance, semantics, and topology. Representing the real world in 3-D differs significantly from representation in 2-D. Technology and approaches for data collection (detect vertical elements of objects, overhanging sections – as sheds, bridges, and roofs), data processing, data structures, data models, and visualization have to be adapted, extended, and/or improved to deal with vertical and overhanging elements as well as objects located inside, above or below each other. Many of the well-known approaches in 2-D GIS are not readily applicable to 3-D representation. This requires investigation of new possibilities for representation, structuring, and visualization of data. This entry outlines the most commonly used 3-D geometric representations in terms of their geometry, resolution, topology, and semantics, elaborates on their use in a wide range of applications, and discusses some of the challenges in research and development.@en

Three-dimensional modelling plays a vital role in indoor 3D tracking, navigation, guidance and emergency evacuation. Reconstruction of indoor 3D models is still problematic, in part, because indoor spaces provide challenges less-documented than their outdoor counterparts. Challenges include obstacles curtailing image and point cloud capture, restricted accessibility and a wide array of indoor objects, each with unique semantics. Reconstruction of indoor environments can be achieved through a photogrammetric approach, e.g. by using image frames, aligned using recurring corresponding image points (CIP) to build coloured point clouds. Our experiments were conducted by flying a QUAV in three indoor environments and later reconstructing 3D models which were analysed under different conditions. Point clouds and meshes were created using Agisoft PhotoScan Professional. We concentrated on flight paths from two vantage points: 1) safety and security while flying indoors and 2) data collection needed for reconstruction of 3D models. We surmised that the main challenges in providing safe flight paths are related to the physical configuration of indoor environments, privacy issues, the presence of people and light conditions. We observed that the quality of recorded video used for 3D reconstruction has a high dependency on surface materials, wall textures and object types being reconstructed. Our results show that 3D indoor reconstruction predicated on video capture using a QUAV is indeed feasible, but close attention should be paid to flight paths and conditions ultimately influencing the quality of 3D models. Moreover, it should be decided in advance which objects need to be reconstructed, e.g. bare rooms or detailed furniture.@en

This paper introduces and compares two types of GML-based data standards for indoor location-based services, i.e., iIndoorGML and iIndoorLocationGML. By elaborating the advantages of the both standards and their data models, we conclude that the two data standards are complementary to each other. A jointed data model is presented to show the integration of the two standards. iIndoorGML can supply subdivision of building for data of iIndoorLocationGML, and the semantics of locations defined in iIndoorLocationGML can be added to iIndoorGML. By proposing two use cases, we take the initiative in attempting to combine the use of the two standards. The first case is to collect details from files of the two standards for an indoor path; the second one is to generate verbal directions for indoor guidance from files of the two standards. Some future work is given for further development, such as automatic integration of separate data from both standards.

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This paper investigates the integration of traffic information (TI) into the routing in the presence of moving obstacles. When traffic accidents occur, the incidents could generate different kinds of hazards (e.g., toxic plumes), which make certain parts of the road network inaccessible. On the other hand, the first responders, who are responsible for management of the traffic incidents, need to be fast and safely guided to the incident place. To support navigation in the traffic network affected by moving obstacles, in this paper, we provide a spatio-temporal data model to structure the information of traffic conditions that is essential for the routing, and present an extended path planning algorithm, named MOAAstar–TI (Moving Obstacle Avoiding A* using Traffic Information), to generate routes avoiding the obstacles. A speed adjustment factor is introduced in the developed routing algorithm, allowing integration of both the information of vehicles and traffic situations to generate routes avoiding the moving obstacles caused by the incidents. We applied our system to a set of navigation scenarios. The application results show the potentials of our system in future application in real life.@en

Updated and detailed indoor models are being increasingly demanded for various applications such as emergency management or navigational assistance. The consolidation of new portable and mobile acquisition systems has led to a higher availability of 3D point cloud data from indoors. In this work, we explore the combined use of point clouds and trajectories from SLAM-based laser scanner to automate the reconstruction of building indoors. The methodology starts by door detection, since doors represent transitions from one indoor space to other, which constitutes an initial approach about the global configuration of the point cloud into building rooms. For this purpose, the trajectory is used to create a vertical point cloud profile in which doors are detected as local minimum of vertical distances. As point cloud and trajectory are related by time stamp, this feature is used to subdivide the point cloud into subspaces according to the location of the doors. The correspondence between subspaces and building rooms is not unambiguous. One subspace always corresponds to one room, but one room is not necessarily depicted by just one subspace, for example, in case of a room containing several doors and in which the acquisition is performed in a discontinue way. The labelling problem is formulated as combinatorial approach solved as a minimum energy optimization. Once the point cloud is subdivided into building rooms, envelop (conformed by walls, ceilings and floors) is reconstructed for each space. The connectivity between spaces is included by adding the previously detected doors to the reconstructed model. The methodology is tested in a real case study.@en

At present, 87 % of people's activities are in indoor environment; indoor navigation has become a research issue. As the building structures for people's daily life are more and more complex, many obstacles influence humans' moving. Therefore it is essential to provide an accurate and efficient indoor path planning. Nowadays there are many challenges and problems in indoor navigation. Most existing path planning approaches are based on 2D plans, pay more attention to the geometric configuration of indoor space, often ignore rich semantic information of building components, and mostly consider simple indoor layout without taking into account the furniture. Addressing the above shortcomings, this paper uses BIM (IFC) as the input data and concentrates on indoor navigation considering obstacles in the multi-floor buildings. After geometric and semantic information are extracted, 2D and 3D space subdivision methods are adopted to build the indoor navigation network and to realize a path planning that avoids obstacles. The 3D space subdivision is based on triangular prism. The two approaches are verified by the experiments.

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