# An Overview of Indoor Positioning and Mapping Technology Standards
## 2 Related Work
### Indoor Mapping Technologies  
With the development of smart cities, digital twins, or the metaverse, there is a growing demand for more effective spatial information acquisition, processing, modeling, representation, and visualization of indoor environments. Unlike the outdoor space, the indoor space is typically bounded and constrained by architectural structures [9]. The challenges of the structural complexity of buildings and indoor location-based applications have been growing in interest in indoor mapping and surveying. Indoor mapping and modeling varies from that of outdoor in many ways due to the complexity and constraints of the indoor space. Therefore, indoor spatial information is acquired by mobile mapping systems (MMS), which makes it possible to acquire time-saving and fully-equipped environmental data using laser scanners from moving platforms. Research and development on multi-sensor mobile mapping systems has been ongoing since the early 1990s. Indoor mapping and modeling (IMM) has greatly accelerated in recent years given the advancements in photogrammetry, computer vision and image analysis, computer graphics, robotics, and laser scanning [36]. Two common ways to examine this literature include identifying ethical issues and the problem areas and applications. [PERSON] et al. [37] examined 35 interlinked IMM problems related to indoor map data acquisitions and sensors, data structures and modelling, visualization, applications, and legal issues and standards in the form of a problem matrix detailing existing and emerging problems, their solutions, and best practices. This problem matrix framework is evaluated and updated yearly. [PERSON] et al. [8] presented a research review in the fields of information acquisition by sensors, model definition, model integration, indoor positioning and LBS, routing and navigation methods, augmented and virtual reality applications, and ethical issues. Based on their work, we focus on a survey of indoor map data acquisition, modelling and presentation. Indoor map data acquisition refers to the measurement techniques, sensors, media, and platforms used to acquire raw data of indoor environments [37]. Based on the measurement device configuration, commercial mobile indoor mapping systems can be classified into different groups: handheld; backpack and trolley [38] in indoor environments or human-based; wheel-based; boat-based; and sledge-based [39] in outdoor environments. The sensors used for 2D/3D indoor environment mapping usually consist of light detection and ranging (LiDAR), terrestrial laser scanner, RGB-D camera, inertial measurement units (IMUs), etc. [PERSON] et al. [39] present a comprehensive review of mobile laser scanning systems applied in both outdoor and indoor environments, grouped into five application domains: the built and urban environment, cultural heritage and archaeology, the underground environment, environmental monitoring, forestry, and agriculture. [PERSON] et al. [40] present an approach for reconstruction of virtual indoor environments based on photogrammetry/image, terrestrial laser scanning, and depth camera, integrated with game engine to evaluate the quality and usability of geometric indoor models. Othershave presented methods for searching the optimum location of the terrestrial laser scanner by using a genetic algorithm. For information acquisition of the environment based on mobile mapping systems, usually one or more sensors are used [36]. Simultaneous localization and mapping (SLAM) refers to building a map of the environment without any prior information and based on the data obtained from one or more sensors; it has been shown by the research community to be a robust technology for indoor mapping. [PERSON] et al. [12] present a survey of major active SLAM methods as they relate to the robots used, the sensor from which the information is gathered, how the world is represented, the core concept of the contribution, the optimization objective, and where the test was performed. [PERSON] et al.