"In God we trust, all others bring data!"
-W. Edwards Deming
In the recent years, devices equipped with sensors able of estimating the location of an entity (e.g. a human, an object, etc.), called Location Services (LS), are becoming pervasive (e.g. smartphones, wearables, etc.). LS are commonly used for adding value to the functionality of existing tools, such as navigation or recommendation engines. These services are called Location-Based Services (LBS). An LBS implies the existence of localization technology (i.e. LS) and a map. A map can be defined as a model that describes the geometry, topology and some semantic information of a place. Even though people spend approximately 80% of their time indoors, LBS are mostly developed for the outdoor world, where localization and mapping problems have largely been addressed. Unfortunately, the same does not apply to indoor environments. Global Navigation Satellite System (GNSS) cannot work indoors, since their signals cannot penetrate solid objects, such as building walls. Additionally, most of the indoor places lack indoor maps. Understanding the indoor environments is therefore of great importance.
Additionally, the accuracy of LBS systems exponentially increases the number of their users. Hence, methods for generating, integrating and enhancing indoor maps need to be researched, in order to cover the increasing demand. As an aside need, modeling semantic information for indoor places (i.e. information that can be used for localization or navigation) is equally important with modeling the geometric and topological properties of a place. Finally, Indoor LBS needs to be constantly enhanced for allowing future technologies, such as the Internet of Things (IoT) or Augmented Reality (AR), to be fully exploited.
Dipl.-Ing. Georgios Pipelidis Co-founder and Managing Director of AriadneMaps GmbH