# Methods and Applications of Space Understanding in Indoor Environment--A Decade Survey
###### Abstract
Similarly, during the research, we found only two other surveys focused on spatial data and discussing 3D building modeling [2; 3]. Searching for a survey focused on the diversity of available data structures yielded no results. There is expected to be a significant improvement in digitalization technology and both the quantity and quality of available data sources each year, not to mention each decade. We can clearly observe the need for a catalog of the newest possibilities. This would have to be massive and comprehensive so that the companies (at all stages of their digital transformation) can use it as a guide through the extensiveness of data they can analyze and applications they can benefit from. It should present what types of data are worth gathering and how they can be used. It is also worth discussing the commonly found challenges and mistakes so that others do not repeat them. To answer this need, in this paper we present a set of taxonomies dedicated to space understanding in the indoor environment. These taxonomies organize the current state of knowledge on three different levels: processed input data types, high-level category of the processing method, and actual low-level application. We summarize each of the taxonomies with extensive discussion and conclude the observations in a section dedicated to visible research challenges. We propose a custom review protocol and present literature research on space segmentation and classification systems across diverse input data structures, with a primary focus on the processing of 2D images. In this analysis, we followed the instructions of a Systematic Literature Review (SLR) [4; 5; 6]. A guide to this methodology was presented by [PERSON] and [PERSON] [7]. Their process is grounded in eight consecutive steps executed one after another. It allows for minimizing the researcher bias that can occur in the case of an entirely subjective choice of papers. Based on their proposals, we adapted the idea, created a set of twelve execution steps, and used them analogically--to prepare a new research protocol, adjusted and dedicated to our needs. Previous works were overly task-focused and mainly discussed only the newly presented algorithms and under specific conditions. To widen the research base, we wanted to avoid focusing on any particular solution and expected the whole research to be data-focused instead. We expected the analyzed systems to fulfill just one essential requirement: solutions needed to work correctly in the indoor environment. In summary, in this paper we extend the current state of literature by:  
* a customized SLR on the topic of room segmentation and classification,
* three interdisciplinary taxonomies for the research done so far and summarizing research findings,
* extended discussion of the application scenarios of found solutions,
* description of observed challenges and research directions that need further analysis. The remainder of this paper is structured as follows: Section 2 describes the methodology we used, the proposed survey execution protocol, and its conduction results. Sections 3-5 present the taxonomies of input data type, high-level abstraction category of the performed process, and its low-level application (taxonomy of the accomplished task), respectively. Section 6 provides a bibliometric analysis of the articles found. Section 7 focuses on the encountered challenges the researchers are trying to overcome, Section 8 discusses the newest trends in the area, and Section 9 summarizes this document with a short review of the findings and a general survey conclusion.