OGC Indoor Mapping and Navigation Pilot Engineering Report

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The concept in this initiative is to take advantage of currently available LiDAR technology and camera imagery to capture a building as a set of 3D point cloud data during routing pre-planning operations, and then transform the data into usable formats for visualization and mapping. These tools already exist for the architecture, engineering, and construction (AEC) community, and it is expected that future investments will significantly lower the costs of tools such that it will become a cost-effective approach for public safety, building managers, and other industries.

In order to demonstrate this public-safety driven scenario, the following activities were conducted in this initiative:

The Information Viewpoint considers the information models and encodings that will make up the content of the services and exchanges to be extended or developed to support this initiative. The following technical service components, data exchanges, and data model extension were developed by the initiative participants and demonstrated in this initiative:

Figure 1 below shows a tiered technical viewpoint of the components in this pilot. Each tier is comprised of various components which access each other through open standards and interfaces to demonstrate interoperability. The Access Tier represents those components which include the data and the component services required to store and access the data. The Business Process Tier represents the components which provide data conversion into other data formats. The Client Tier represents the pre-planning clients which provide a user interface to interact with the components.

The Computational Viewpoint is concerned with the functional decomposition of the system into a set of objects that interact at interfaces – enabling system distribution. The interface architecture for the Indoor Mapping and Navigation Pilot initiative is derived from the functional architecture provided in the CFP with some key changes. The architecture, as described by the Indoor Mapping and Navigation CFP, places a focus on the use of OGC web services for implementation of the modeler services as seen in Figure 2.

During the kick-off discussions, it was determined that the initial viewpoint of the Building Modeler and Navigation Modeler fit well in the paradigm for WPS 2.0. However, it was determined that the interactions between the Pre-planning Tool Client and the Indoor Navigation Service is is better implemented using WPS instead of WFS. Additionally, the WFS-T originally envisioned for the Building Model Repository was replaced with a CSW-T interface. All components interface directly with the Building Model Repository via the CSW-T interface, retrieving necessary data and storing the resulting transformed data. The clients access the CSW-T to retrieve each data set to display in the client user interface and generate indoor routes for navigation. Figure 3 shows the updated component architecture after discussion at the Indoor Pilot Kick-off meeting.

It should be noted that the Navigation Modeler service was implemented in two different ways: 1) converting the CityGML output of the Building Modeler into IndoorGML, and 2) reversely, converting point cloud data directly into IndoorGML and then back into CityGML. The reason for this is due to the fact that one participant focused on the indoor spatial mapping from point cloud data rather than from a top-down building geometry to indoor space workflow. More details can be found in Chapter 7, Navigation Modeler Service.

The Engineering Viewpoint is concerned with the infrastructure required to support system distribution. It focuses on the mechanisms and functions required to support distributed interaction between objects in the system, and hides the complexities of those interactions. It exposes the distributed nature of the system, describing the infrastructure, mechanisms and functions for object distribution, distribution transparency and constraints, bindings and interactions.

The following sequence diagram describes the conceptual flow for the Pilot architecture.

Each of the following chapters in this ER describe the individual Technology Viewpoint of the various components, how they are developed, the software tools utilized, and the distribution of components needed to achieve the result of the Technology Integration Experiments (TIEs) conducted in this initiative.

Chapter 5, Data Sources describes the various data sets provided in this pilot. The datasets include point clouds, CityGML, and IndoorGML data. This chapter also catalogs the provided sample data, the official demonstration data, data derived and converted from the original formats, and details the data cleansing and enrichment. Some data is enriched with Public Safety Features CityGML ADE, which is documented in a separate ER. For more information, refer to the OGC 19-032 CityGML Public Safety ADE Engineering Report.

Chapter 6, Building Modeler Service describes the Building Modeler Service which converts point cloud data into CityGML data. This task was to create a building modeler application that can convert point cloud models and associated images (such as those generated by the Building Data) into semantic 3D building models compliant with the most recent or stable version of CityGML (2.0). Models generated by this component are notated with Public Safety Features from the CityGML ADE. The building modeler may be developed as a web processing service (WPS) compliant with the OGC WPS 2.0 Interface Standard (OGC14-065), although this was not a strict requirement.

Chapter 7, Navigation Modeler Service describes the Navigation Modeler Service which converts CityGML data into IndoorGML data. This task was to create a navigation modeler application that can convert output from the Building Modeler Service to IndoorGML usable for indoor navigation. The Navigation Modeler also generated navigation network information to support route calculations by the Indoor Navigation Service. The navigation modeler may be developed as a WPS compliant service, although this was not a strict requirement.

Chapter 8, Building Model Repository describes the Building Model Repository which stores the various datasets and makes them available to other services and end users. This task was to create a building model repository to store and serve point cloud, building, and navigation models (see Building Data, Building Modeler Service, and Navigation Modeler Service). The repository exposes a model catalog and provides authenticated access. The repository is interoperable with application clients.

Chapter 9, Indoor Navigation Service describes the Indoor Navigation Service which consumes the IndoorGML data to produce a navigation route based on parametric inputs. This task involved creating an indoor navigation service that can derive ‘turn-by-turn’ instructions between any two points in a building, including exits, based on network models created by the Navigation Modeler Service and stored in the IndoorGML. The service used navigation algorithms, not necessarily developed in this Initiative, which were optimized for specific criteria (e.g. routes optimized based on time, distance, or risk) requested by the Pre-planning Tool Client.

Chapter 10, Pre-planning Tool Client describes the Pre-planning Tool Client for end user access to the services and dataset renderings for mapping and navigation display. This task was to create a visualization client application for users to request and view point cloud data and building models from the Building Model Repository, as well as navigation instructions and routes from the Indoor Navigation Service. The client is a graphical user interface that enables public safety personnel to view and annotate models captured during pre-planning. The client should seamlessly transition between 2D and 3D views and should allow users to visualize hypothetical routes into, through, and out of buildings along with the appropriate metrics (e.g. estimated time, distance, risk, etc.) based on additional input parameters considered by the navigation service. The client should use the OGC WFS Interface Standard and OGC 3DPS to request and receive models, scenes, and services.

This Pilot uses several data sources for testing and experimentation including Point Cloud data, CityGML data, and IndoorGML data. CityGML is an open standardized data model and exchange format to store digital 3D models of cities and landscapes. The data files are hosted by the OGC in a secure File Transfer Protocol (FTP) server accessible to participants. Enriched data includes cleansed data which is then enriched with an Application Domain Extension (ADE), a built-in mechanism of CityGML to augment its data model with additional concepts required by particular use cases. The ADE is a mechanism for enriching the data model with new feature classes and attributes, while preserving the semantic structure of CityGML. IndoorGML is an OGC standard for an open data model and XML schema for indoor spatial information. IndoorGML does not officially have an extension mechanism, but one was needed to carry the Public Safety features that were forwarded from the CityGML Public Safety ADE.

The following sample data was provided by the participants for testing and evaluation as components were being developed. This was done to ensure parallel development to achieve the TIEs later in the project while participants were waiting on the demonstration data.