# L5 IN: Overview of an Indoor Navigation Pilot Project
## 1 Introduction  
Navigation is the art and science of determining the position of a mobile vehicle, and guiding it to a specific destination [1], thereby answering the question of how to \"get from point A to point B\". In large areas, at sea or in the air, outdoor navigation based on GNSS is standard today. The decisive advantage here is the open space with good signal reception, which thus ensures sufficient permeability. Google Maps is one of the most popular projects benefiting from GNSS, meaning that it is therefore limited to outdoor services. However, the mobile Maps application directs people almost anywhere and anytime around the globe [2]. Navigation paths are not the same for all types of users; for instance, cars need different route to bicycles. Users may select the desired navigation type that they would like to be navigated by. When it comes to indoor navigation usage, specialized solutions are available to provide services only for limited buildings or users. The enclosed space is much less developed, as it is often not possible to work with GNSS data. However, large building complexes and connected facilities, such as a campus with many buildings, also require navigation aids. Therefore, indoor navigation has become a central challenge in recent years [3]. Bluetooth or WLAN solutions are the most used today [4; 5; 6], but these methods of positioning usually require a client system, e.g.,in the form of a software app on a smartphone, special devices, or at least a login to the WLAN system. These systems are therefore neither autonomous nor anonymous. There are also limitations regarding the availability of corresponding visual navigation material, such as missing map material. In contrast, the corresponding outdoor navigation maps are generated automatically, thanks to the long-time availability of GNSS positioning. Different mapping technologies like mobile mapping systems can provide and update the map information automatically and regularly around the world, because there is GNSS solutions as a reference for positioning. Even a giant company like Apple has shown interest in using WLAN-based positioning techniques. However, as is discussed later, WLAN and similar approaches cannot be considered as extendable positioning techniques. Regarding the Apple Indoor program [7], preparing maps for indoor positioning purposes plays an important role. Users can define different layers of access for public usage, including the level, units, and opening. It is shown later that the BIM can provide even deeper information for use in indoor maps. The project Level 5 Indoor Navigation (LSIN) represents a new approach to pedestrian indoor navigation based on novel technologies. The project consistently relies on mobile communications as the orientation signal. Here, the special performance of the future mobile communication standard 5G plays the central role in enabling technology. The aim of this project is to use the new available 5G technology to show how navigation systems, which have thus far only been available in the outdoor segment, can now be integrated into existing smartphone systems for indoor navigation. This is accompanied by the further development of positioning methods for indoor localization with a hybrid fusion of smartphone sensors and available information from 5G networks. In addition to a wide range of application possibilities, this will also enable simplified use that does not require specific integration into singular systems. Additional hardware technologies such as WiFi, which entail high maintenance and implementation costs, were avoided for navigation in the converted space and, furthermore, a generic offer was created, which allows a navigation ecology beyond a model use case. Indoor navigation will be enabled through the use of a specific app with open interfaces in all buildings that had been modeled accordingly. The remainder of this paper is structured as follows: The project is described using the work packages in the next section.