On the right track : comfort and confusion in indoor environments

Indoor navigation systems are not well adapted to the needs of their users. The route planning algorithms implemented in these systems are usually limited to shortest path calculations or derivatives, minimalizing Euclidian distance. Guiding people along routes that adhere better to their cognitive processes could ease wayfinding in indoor environments. This paper examines comfort and confusion perception during wayfinding by applying a mixed-method approach. The aforementioned method combined an exploratory focus group and a video-based online survey. From the discussions in the focus group, it could be concluded that indoor wayfinding must be considered at different levels: the local level and the global level. In the online survey, the focus was limited to the local level, i.e., local environmental characteristics. In this online study, the comfort and confusion ratings of multiple indoor navigation situations were analyzed. In general, the results indicate that open spaces and stairs need to be taken into account in the development of a more cognitively-sounding route planning algorithm. Implementing the results in a route planning algorithm could be a valuable improvement of indoor navigation support

Indoor Semantic Modelling for Routing:

Humans perform many activities indoors and they show a growing need for indoor navigation, especially in unfamiliar buildings such as airports, museums and hospitals. Complexity of such buildings poses many challenges for building managers and visitors. Indoor navigation services play an important role in supporting these indoor activities. Indoor navigation covers extensive topics such as: 1) indoor positioning and localization; 2) indoor space representation for navigation model generation; 3) indoor routing computation; 4) human wayfinding behaviours; and 5) indoor guidance (e.g., textual directories). So far, a large number of studies of pedestrian indoor navigation have presented diverse navigation models and routing algorithms/methods. However, the major challenge is rarely referred to: how to represent the complex indoor environment for pedestrians and conduct routing according to the different roles and sizes of users. Such complex buildings contain irregular shapes, large open spaces, complicated obstacles and different types of passages. A navigation model can be very complicated if the indoors are accurately represented. Although most research demonstrates feasible indoor navigation models and related routing methods in regular buildings, the focus is still on a general navigation model for pedestrians who are simplified as circles. In fact, pedestrians represent different sizes, motion abilities and preferences (e.g., described in user profiles), which should be reflected in navigation models and be considered for indoor routing (e.g., relevant Spaces of Interest and Points of Interest). In order to address this challenge, this thesis proposes an innovative indoor modelling and routing approach – two-level routing. It specially targets the case of routing in complex buildings for distinct users. The conceptual (first) level uses general free indoor spaces: this is represented by the logical network whose nodes represent the spaces and edges stand for their connectivity; the detailed (second) level focuses on transition spaces such as openings and Spaces of Interest (SOI), and geometric networks are generated regarding these spaces. Nodes of a geometric network refers to locations of doors, windows and subspaces (SOIs) inside of the larger spaces; and the edges represent detailed paths among these geometric nodes. A combination of the two levels can represent complex buildings in specified spaces, which avoids maintaining a largescale complete network. User preferences on ordered SOIs are considered in routing on the logical network, and preferences on ordered Points of Interest (POI) are adopted in routing on geometric networks. In a geometric network, accessible obstacle-avoiding paths can be computed for users with different sizes. To facilitate automatic generation of the two types of network in any building, a new data model named Indoor Navigation Space Model (INSM) is proposed to store connectivity, semantics and geometry of indoor spaces for buildings. Abundant semantics of building components are designed in INSM based on navigational functionalities, such as VerticalUnit(VU) and HorizontalConnector(HC) as vertical and horizontal passages for pedestrians. The INSM supports different subdivision ways of a building in which indoor spaces can be assigned proper semantics. A logical and geometric network can be automatically derived from INSM, and they can be used individually or together for indoor routing. Thus, different routing options are designed. Paths can be provided by using either the logical network when some users are satisfied with a rough description of the path (e.g., the name of spaces), or a geometric path is automatically computed for a user who needs only a detailed path which shows how obstacles can be avoided. The two-level routing approach integrates both logical and geometric networks to obtain paths, when a user provides her/his preferences on SOIs and POIs. For example, routing results for the logical network can exclude unrelated spaces and then derive geometric paths more efficiently. In this thesis, two options are proposed for routing just on the logical network, three options are proposed for routing just on the geometric networks, and seven options for two-level routing. On the logical network, six routing criteria are proposed and three human wayfinding strategies are adopted to simulate human indoor behaviours. According to a specific criterion, space semantics of logical nodes is utilized to assign different weights to logical nodes and edges. Therefore, routing on the logical network can be accomplished by applying the Dijkstra algorithm. If multiple criteria are adopted, an order of criteria is applied for routing according to a specific user. In this way, logical paths can be computed as a sequence of indoor spaces with clear semantics. On geometric networks, this thesis proposes a new routing method to provide detailed paths avoiding indoor obstacles with respect to pedestrian sizes. This method allows geometric networks to be derived for individual users with different sizes for any specified spaces. To demonstrate the use of the two types of network, this thesis tests routing on one level (the logical or the geometric network). Four case studies about the logical network are presented in both simple and complex buildings. In the simple building, no multiple paths lie between spaces A and B, but in the complex buildings, multiple logical paths exist and the candidate paths can be reduced by applying these routing criteria in an order for a user. The relationships of these criteria to user profiles are assumed in this thesis. The proposed geometric routing regarding user sizes is tested with three case studies: 1) routing for pedestrians with two distinct sizes in one space; 2) routing for pedestrians with changed sizes in one space; and 3) a larger geometric network formed by the ones in a given sequence of spaces. The first case shows that a small increase of user size can largely change the accessible path; the second case shows different path segments for distinct sizes can be combined into one geometric path; the third case demonstrates a geometric network can be created ’on the fly’ for any specified spaces of a building. Therefore, the generation and routing of geometric networks are very flexible and fit to given users. To demonstrate the proposed two-level routing approach, this thesis designs five cases. The five cases are distinguished according to the method of model creation (pre-computed or ’on-the-fly’) and model storage (on the client or server). Two of them are realized in this thesis: 1) Case 1 just in the client pre-computes the logical network and derives geometric networks ’on the fly’; 2) Case 2 just in the client pre-computes and stores the logical and geometric networks for certain user sizes. Case 1 is implemented in a desktop application for building managers, and Case 2 is realized as a mobile mock-up for mobile users without an internet connection. As this thesis shows, two-level routing is powerful enough to effectively provide indicative logical paths and/or comprehensive geometric paths, according to different user requirements on path details. In the desktop application, three of the proposed routing options for two-level routing are tested for the simple OTB building and the complex Schiphol Airport building. These use cases demonstrate that the two-level routing approach includes the following merits: It supports routing in different abstraction forms of a building. The INSM model can describe different subdivision results of a building, and it allows two types of routing network to be derived – pure logical and geometric ones. The logical network contains the topology and semantics of indoor spaces, and the geometric network provides accurate geometry for paths. A consistent navigation model is formed with the two networks, i.e., the conceptual and detailed levels. On the conceptual level, it supports routing on a logical network and assists the derivation of a conceptual path (i.e., logical path) for a user in terms of space sequence. Routing criteria are designed based on the INSM semantics of spaces, which can generate logical paths similar to human wayfinding results such as minimizing VerticalUnit or HorizontalConnector. On the detailed level, it considers the size of users and results in obstacle-avoiding paths. By using this approach, geometric networks can be generated to avoid obstacles for the given users and accessible paths are flexibly provided for user demands. This approach can process changes of user size more efficiently, in contrast to routing on a complete geometric network. It supports routing on both the logical and the geometric networks, which can generate geometric paths based on user-specific logical paths, or re-compute logical paths when geometric paths are inaccessible. This computation method is very useful for complex buildings. The two-level routing approach can flexibly provide logical and geometric paths according to user preferences and sizes, and can adjust the generated paths in limited time. Based on the two-level routing approach, this thesis also provides a vision on possible cooperation with other methods. A potential direction is to design more routing options according to other indoor scenarios and user preferences. Extensions of the two-level routing approach, such as other types of semantics, multi-level networks and dynamic obstacles, will make it possible to deal with other routing cases. Last but not least, it is also promising to explore its relationships with indoor guidance, different building subdivisions and outdoor navigation

Indoor Semantic Modelling for Routing: The Two-Level Routing Approach for Indoor Navigation

Humans perform many activities indoors and they show a growing need for indoor navigation, especially in unfamiliar buildings such as airports, museums and hospitals. Complexity of such buildings poses many challenges for building managers and visitors. Indoor navigation services play an important role in supporting these indoor activities. Indoor navigation covers extensive topics such as: 1) indoor positioning and localization; 2) indoor space representation for navigation model generation; 3) indoor routing computation; 4) human wayfinding behaviours; and 5) indoor guidance (e.g., textual directories). So far, a large number of studies of pedestrian indoor navigation have presented diverse navigation models and routing algorithms/methods. However, the major challenge is rarely referred to: how to represent the complex indoor environment for pedestrians and conduct routing according to the different roles and sizes of users. Such complex buildings contain irregular shapes, large open spaces, complicated obstacles and different types of passages. A navigation model can be very complicated if the indoors are accurately represented. Although most research demonstrates feasible indoor navigation models and related routing methods in regular buildings, the focus is still on a general navigation model for pedestrians who are simplified as circles. In fact, pedestrians represent different sizes, motion abilities and preferences (e.g., described in user profiles), which should be reflected in navigation models and be considered for indoor routing (e.g., relevant Spaces of Interest and Points of Interest). In order to address this challenge, this thesis proposes an innovative indoor modelling and routing approach – two-level routing. It specially targets the case of routing in complex buildings for distinct users. The conceptual (first) level uses general free indoor spaces: this is represented by the logical network whose nodes represent the spaces and edges stand for their connectivity; the detailed (second) level focuses on transition spaces such as openings and Spaces of Interest (SOI), and geometric networks are generated regarding these spaces. Nodes of a geometric network refers to locations of doors, windows and subspaces (SOIs) inside of the larger spaces; and the edges represent detailed paths among these geometric nodes. A combination of the two levels can represent complex buildings in specified spaces, which avoids maintaining a largescale complete network. User preferences on ordered SOIs are considered in routing on the logical network, and preferences on ordered Points of Interest (POI) are adopted in routing on geometric networks. In a geometric network, accessible obstacle-avoiding paths can be computed for users with different sizes. To facilitate automatic generation of the two types of network in any building, a new data model named Indoor Navigation Space Model (INSM) is proposed to store connectivity, semantics and geometry of indoor spaces for buildings. Abundant semantics of building components are designed in INSM based on navigational functionalities, such as VerticalUnit(VU) and HorizontalConnector(HC) as vertical and horizontal passages for pedestrians. The INSM supports different subdivision ways of a building in which indoor spaces can be assigned proper semantics. A logical and geometric network can be automatically derived from INSM, and they can be used individually or together for indoor routing. Thus, different routing options are designed. Paths can be provided by using either the logical network when some users are satisfied with a rough description of the path (e.g., the name of spaces), or a geometric path is automatically computed for a user who needs only a detailed path which shows how obstacles can be avoided. The two-level routing approach integrates both logical and geometric networks to obtain paths, when a user provides her/his preferences on SOIs and POIs. For example, routing results for the logical network can exclude unrelated spaces and then derive geometric paths more efficiently. In this thesis, two options are proposed for routing just on the logical network, three options are proposed for routing just on the geometric networks, and seven options for two-level routing. On the logical network, six routing criteria are proposed and three human wayfinding strategies are adopted to simulate human indoor behaviours. According to a specific criterion, space semantics of logical nodes is utilized to assign different weights to logical nodes and edges. Therefore, routing on the logical network can be accomplished by applying the Dijkstra algorithm. If multiple criteria are adopted, an order of criteria is applied for routing according to a specific user. In this way, logical paths can be computed as a sequence of indoor spaces with clear semantics. On geometric networks, this thesis proposes a new routing method to provide detailed paths avoiding indoor obstacles with respect to pedestrian sizes. This method allows geometric networks to be derived for individual users with different sizes for any specified spaces. To demonstrate the use of the two types of network, this thesis tests routing on one level (the logical or the geometric network). Four case studies about the logical network are presented in both simple and complex buildings. In the simple building, no multiple paths lie between spaces A and B, but in the complex buildings, multiple logical paths exist and the candidate paths can be reduced by applying these routing criteria in an order for a user. The relationships of these criteria to user profiles are assumed in this thesis. The proposed geometric routing regarding user sizes is tested with three case studies: 1) routing for pedestrians with two distinct sizes in one space; 2) routing for pedestrians with changed sizes in one space; and 3) a larger geometric network formed by the ones in a given sequence of spaces. The first case shows that a small increase of user size can largely change the accessible path; the second case shows different path segments for distinct sizes can be combined into one geometric path; the third case demonstrates a geometric network can be created ’on the fly’ for any specified spaces of a building. Therefore, the generation and routing of geometric networks are very flexible and fit to given users. To demonstrate the proposed two-level routing approach, this thesis designs five cases. The five cases are distinguished according to the method of model creation (pre-computed or ’on-the-fly’) and model storage (on the client or server). Two of them are realized in this thesis: 1) Case 1 just in the client pre-computes the logical network and derives geometric networks ’on the fly’; 2) Case 2 just in the client pre-computes and stores the logical and geometric networks for certain user sizes. Case 1 is implemented in a desktop application for building managers, and Case 2 is realized as a mobile mock-up for mobile users without an internet connection. As this thesis shows, two-level routing is powerful enough to effectively provide indicative logical paths and/or comprehensive geometric paths, according to different user requirements on path details. In the desktop application, three of the proposed routing options for two-level routing are tested for the simple OTB building and the complex Schiphol Airport building. These use cases demonstrate that the two-level routing approach includes the following merits: It supports routing in different abstraction forms of a building. The INSM model can describe different subdivision results of a building, and it allows two types of routing network to be derived – pure logical and geometric ones. The logical network contains the topology and semantics of indoor spaces, and the geometric network provides accurate geometry for paths. A consistent navigation model is formed with the two networks, i.e., the conceptual and detailed levels. On the conceptual level, it supports routing on a logical network and assists the derivation of a conceptual path (i.e., logical path) for a user in terms of space sequence. Routing criteria are designed based on the INSM semantics of spaces, which can generate logical paths similar to human wayfinding results such as minimizing VerticalUnit or HorizontalConnector. On the detailed level, it considers the size of users and results in obstacle-avoiding paths. By using this approach, geometric networks can be generated to avoid obstacles for the given users and accessible paths are flexibly provided for user demands. This approach can process changes of user size more efficiently, in contrast to routing on a complete geometric network. It supports routing on both the logical and the geometric networks, which can generate geometric paths based on user-specific logical paths, or re-compute logical paths when geometric paths are inaccessible. This computation method is very useful for complex buildings. The two-level routing approach can flexibly provide logical and geometric paths according to user preferences and sizes, and can adjust the generated paths in limited time. Based on the two-level routing approach, this thesis also provides a vision on possible cooperation with other methods. A potential direction is to design more routing options according to other indoor scenarios and user preferences. Extensions of the two-level routing approach, such as other types of semantics, multi-level networks and dynamic obstacles, will make it possible to deal with other routing cases. Last but not least, it is also promising to explore its relationships with indoor guidance, different building subdivisions and outdoor navigation. &nbsp

Spatial Queries for Indoor Location-based Services

Indoor Location-based Services (LBS) facilitate people in indoor scenarios such as airports, train stations, shopping malls, and office buildings. Indoor spatial queries are the foundation to support indoor LBSs. However, the existing techniques for indoor spatial queries are limited to support more advanced queries that consider semantic information, temporal variations, and crowd influence. This work studies indoor spatial queries for indoor LBSs. Some typical proposals for indoor spatial queries are compared theoretically and experimentally. Then, it studies three advanced indoor spatial queries, a) Indoor Keyword-aware Routing Query. b) Indoor Temporal-variation aware Routing Query. c) Indoor Crowd-aware Routing Query. A series of techniques are proposed to solve these problems.</p

스캔 도면을 활용한 이동약자용 실내 그래프 데이터베이스 구축

학위논문(박사) -- 서울대학교대학원 : 공과대학 건설환경공학부, 2021.8. 박슬아.사람들의 실내 활동이 다양해지면서 건물의 규모가 커지고 구조가 복잡해지고 있다. 이러한 실내 환경의 변화는 교통약자의 이동성 보장에 대한 사회적 관심을 증가시켰으며, 교통약자 맞춤형 실내 라우팅 서비스에 대한 수요 또한 증가시켰다. 특히 많은 이동 제약을 가지는 이동약자 대상 서비스의 경우에는, 최적 경로를 계획하는 과정에서 개인의 선호나 경험이 반영된 개인화된 서비스로 범위가 확장되고 있다. 이러한 배경에서, 스키마가 유연하고 데이터의 가공 및 처리가 효율적인 데이터베이스의 구축이 필요하다. 본 연구에서는 스캔한 도면 이미지를 활용한 이동약자용 실내 그래프데이터베이스 구축 기법을 제안하였다. 먼저, 국내외 실내 공간 관련 표준 및 설계 기준들의 검토를 통해 이동약자의 통행과 관련된 실내 공간 및 객체, 영향 요인들을 도출하여 개념적 데이터 모델을 설계하였다. 또한, 실내의 각 공간과 시설물의 기하정보와 위상정보를 기반으로 이동약자의 접근성 및 통행 가능성을 정량화하기 위한 접근성 지수를 설계하였다. 다음으로, 스캔 도면을 입력하여 이동약자용 실내 그래프 데이터베이스 구축을 위한 프로세스를 제안하였다. 제안한 프로세스는 전이학습 기반 접근 방식을 통해 스캔 도면에서 공간의 구조 정보를 추출하고, 토폴로지 추출 및 접근성 평가를 통해 이동약자용 네트워크 모델을 생성하며, 생성한 네트워크 모델을 그래프 데이터베이스로 자동 변환하는 과정을 포함한다. 구체적으로, 제안 프로세스는 수정된 ResNet 기반의 모델을 새롭게 라벨링한 도면으로 미세 조정하여 사용함으로써 실내 구조맵을 생성한다. 이후 추출된 객체들의 공간 관계를 기반으로 각 공간을 노드와 링크로 표현한 실내 네트워크 모델을 구축한다. 각 공간의 접근성 정보는 제안된 접근성 지수와 임계값을 사용하여 생성된 후 데이터베이스에 저장되어, 이동약자를 위한 접근 가능한 그래프 추출에 활용될 수 있다. 본 연구에서는 제안한 기법을 서울대학교 도면 데이터 셋에 적용하여 이동약자용 실내 그래프 데이터베이스를 구축하고 평가하였다. 구축한 실내 그래프 데이터베이스를 활용하여 다층 경로 계획과 실내외 연계 경로 계획의 2가지 시나리오에 따라 최적 경로를 도출하였다. 그 결과, 일반 보행자의 최적 경로와 비교하여 이동약자용 최적 경로는 가까운 계단이 아닌 엘리베이터를 통한 수직 이동을 포함하였을 뿐만 아니라 접근 불가능한 공간을 회피하도록 도출되었다. 즉, 제안한 기법을 통해 이동약자 측면에서 통행 장애 정보를 포함하여 실내 환경을 적절하게 묘사하는 데이터베이스의 구축이 가능함을 확인할 수 있었다. 또한, 출입로로 명명된 관계 생성만으로 스케일이나 좌표 변환 없이 실내외 연계 경로 계획이 가능하였는데, 이는 독립적인 데이터 간 연계 사용에 적합한 그래프 데이터베이스의 특성을 반영한 결과로 판단할 수 있다. 본 연구의 주요 기여는 스캔한 도면을 사용하여 이동약자용 실내 그래프 데이터베이스를 구축하기 위한 프로세스를 개발한 것이다. 구체적으로, 이동약자의 이동에 초점을 두고 설계한 데이터 모델을 기반으로 한 데이터베이스 구축이 가능하므로 이동약자용 실내 길안내 서비스에 활용될 수 있다. 또한, 토폴로지 구축 및 그래프 데이터베이스로의 변환을 위한 하위 프로시져를 개발하였으며, 제안 프로세스는 해당 프로시져들로 구성되어 도면 입력을 통해 이동약자용 실내 그래프 데이터베이스 구축을 가능하게 한다. 해당 하위 프로시져들은 자동으로 수행될 수 있어 데이터베이스 구축 시 소요되는 시간과 비용을 절감할 수 있다. 또한, 다양한 정형 및 비정형 데이터의 연계에 적합한 그래프 데이터베이스의 특징에 의해, 제안한 프로세스를 통해 구축한 실내 데이터베이스는 기존 공간 모델의 기능을 포함하면서 다양한 유형의 길안내 서비스에 활용될 수 있을 것으로 기대된다.Changes to the indoor environment have increased social interest in ensuring the mobility of people with disabilities. Therefore, the demand for customized indoor routing services for people with mobility disabilities (PWMD), who have many travel restrictions, is increasing. These services have progressed from spatial routing to personalized routing, which reflects personal preferences and experiences in planning an optimal path. In this regard, it is necessary to generate a database for PWMD with a flexible schema suitable for the efficient manipulation and processing of data. This study aims to propose a technique of generating an indoor graph database for PWMD using scanned floor plans. First, a conceptual data model was developed by deriving relevant indoor features and influential factors, considering various international regulations on indoor environments. Also, the accessibility index was designed based on the data model to quantify the difficulties in accessing spaces based on each indoor spaces geometric characteristics. Next, a three-stage process was proposed: retrieving the structure of spaces from scanned floor plans through a transfer learning-based approach, retrieving topology and assessing accessibility for creating an indoor network model for PWMD, and converting the network model into a graph database. Specifically, an indoor structure map is created by fine-tuning the modified Resnet-based model with newly annotated floor plans for extracting structure information. Also, based on the spatial relationship of the extracted features, the indoor network model was created by abstracting indoor spaces with nodes and links. The accessibility of each space is determined by the proposed indices and thresholds; thereby, a feasible network for PWMD could be derived. Then, a process was developed for automatically converting an indoor network model, including accessibility property, into a graph database. The proposed technique was applied to the Seoul National University dataset to generate an indoor graph database for PWMD. Two scenario-based routing tests were conducted using the generated database to verify the utility of results: multi-floor routing and integrated indoor-outdoor routing. As a result, compared with the path for general pedestrians, the optimal path for PWMD was derived by avoiding inaccessible spaces, including vertical movement using elevators rather than the nearest stairs. In other words, applying the proposed technique, a database that adequately described an indoor environment in terms of PWMD with sufficient mobile constraint information could be constructed. Moreover, an integrated indoor-outdoor routing could be conducted by only creating an entrance-labeled relationship, without scale and coordinate transformation. This result reflects the usability of the generated graph database and its suitability regarding the incorporation of multiple individual data sources. The main contribution lies in the development of the process for generating an indoor graph database for PWMD using scanned floor plans. In particular, the database for PWMD routing can be generated based on the proposed data model with PWMD-related features and factors. Also, sub-procedures for topology retrieval and graph database conversion are developed to generate the indoor graph database by the end-to-end process. The developed sub-procedures are performed automatically, thereby reducing the required times and costs. It is expected that the target database of the proposed process can be generated considering utilization for various types of routing since the graph database is easily integrated with multiple types of information while covering the existing spatial models function.1. Introduction 1 1.1 Objectives and contributions 1 1.2 Related works 7 1.2.1 Indoor environment conceptualization 7 1.2.2 Indoor data construction 11 1.2.3 Accessibility assessment 19 1.3 Research scope and flow 22 2. Conceptual modeling 26 2.1 Relevant features and factors 28 2.2 Proposed data model 30 2.3 Space accessibility for PWMD 36 2.3.1 Influential factors within indoor environments 37 2.3.2 Accessibility index 41 3. Indoor graph database for PWMD from scanned floor plans 43 3.1 Retrieving structure of indoor spaces 43 3.1.1 Pre-trained model for detecting indoor geometry 45 3.1.2 Dataset with new annotation 47 3.1.3 Transfer learning-based approach 52 3.2 Generating the indoor network model for PWMD 56 3.2.1 Definition of nodes and links in the network model 60 3.2.2 The classification rule of space polygons 63 3.2.3 Connection between general spaces and doors 68 3.2.4 Node-link generation for horizontal transition spaces 71 3.2.5 Vertical link generation 75 3.2.6 Connectivity and accessibility information generation 79 3.3 Indoor graph database for PWMD 80 3.3.1 Graph representation of indoor environments 80 3.3.2 Conversion of network model into graph database 83 3.4 Entire process 87 4. Experiment and results 89 4.1 Experimental setup and test data 89 4.2 Evaluation for retrieved information 92 4.2.1 Results of structure retrieval 92 4.2.2 Results of topology retrieval 99 4.3 Generated indoor graph database for PWMD 128 4.3.1 Results of the indoor graph database for PWMD 128 4.3.2 Query-based routing 136 5. Conclusion 147 References 150 Appendix 166 국문초록 178박

Space Subdivision For Indoor Navigation: A Systematic Literature Review

Along with the increasing demand for indoor navigation, many attempts were made to improve indoor navigation performance. Information about the room becomes important, because one of the characteristics of indoor navigation is the dynamic indoor conditions. Space subdivision is an effort made to make indoor navigation even more accurate. The purpose of this study is to create a systematic literature review (SLR) regarding the topic of space subdivision for indoor navigation which is based on a SLR method, previously defined research question. This study examines several previous works specifically in the field of space subdivision for indoor navigation with the SLR. This research is expected to be the basis for further research to improve the quality of indoor navigation based on space subdivision

Emergency response in complex buildings: Automated selection of safest and balanced routes

The extreme importance of emergency response in complex buildings during natural and human-induced disasters has been widely acknowledged. In particular, there is a need for efficient algorithms for finding safest evacuation routes, which would take into account the 3-D structure of buildings, their relevant semantics, and the nature and shape of hazards. In this article, we propose algorithms for safest routes and balanced routes in buildings, where an extreme event with many epicenters is occurring. In a balanced route, a trade-off between route length and hazard proximity is made. The algorithms are based on a novel approach that integrates a multiattribute decision-making technique, Dijkstra's classical algorithm and the introduced hazard proximity numbers, hazard propagation coefficient and proximity index for a route

3D indoor modeling and game theory based navigation for pre and post COVID-19 situation

The COVID-19 pandemic has greatly affected human behavior, creating a need for individuals to be more cautious about health and safety protocols. People are becoming more aware of their surroundings and the importance of minimizing the risk of exposure to potential sources of infection. This shift in mindset is particularly important in indoor environments, especially hospitals, where there is a greater risk of virus transmission. The implementation of route planning in these areas, aimed at minimizing interaction and exposure, is crucial for positively influencing individual behavior. Accurate maps of buildings help provide location-based services, prepare for emergencies, and manage infrastructural facilities. There aren’t any maps available for most installations, and there are no proven techniques to categorize features within indoor areas to provide location-based services. During a pandemic like COVID-19, the direct connection between the masses is one of the significant preventive steps. Hospitals are the main stakeholders in managing such situations. This study presents a novel method to create an adaptive 3D model of an indoor space to be used for localization and routing purposes. The proposed method infuses LiDAR-based data-driven methodology with a Quantum Geographic Information System (QGIS) model-driven process using game theory. The game theory determines the object localization and optimal path for COVID-19 patients in a real-time scenario using Nash equilibrium. Using the proposed method, comprehensive simulations and model experiments were done using QGIS to identify an optimized route. Dijkstra algorithm is used to determine the path assessment score after obtaining several path plans using dynamic programming. Additionally, Game theory generates path ordering based on the custom scenarios and user preference in the input path. In comparison to other approaches, the suggested way can minimize time and avoid congestion. It is demonstrated that the suggested technique satisfies the actual technical requirements in real-time. As we look forward to the post-COVID era, the tactics and insights gained during the pandemic hold significant value. The techniques used to improve indoor navigation and reduce interpersonal contact within healthcare facilities can be applied to maintain a continued emphasis on safety, hygiene, and effective space management in the long term. The use of three-dimensional (3D) modeling and optimization methodologies in the long-term planning and design of indoor spaces promotes resilience and flexibility, encouraging the adoption of sustainable and safe practices that extend beyond the current pandemic