scholarly journals A BIM Based Hybrid 3D Indoor Map Model for Indoor Positioning and Navigation

2020 ◽  
Vol 9 (12) ◽  
pp. 747
Author(s):  
Jianhua Liu ◽  
Jingyan Luo ◽  
Jiwei Hou ◽  
Danqi Wen ◽  
Guoqiang Feng ◽  
...  
Keyword(s):  
Emergency Response ◽  
Indoor Positioning ◽  
Location Based Services ◽  
Information Modeling ◽  
Data Organization ◽  
Navigation Systems ◽  
Indoor Location ◽  
Navigation Function ◽  
Building Information ◽  
Indoor Spaces

Accurate and fast indoor Location-Based Services (LBS) is very important for daily life and emergency response. Indoor map is the basis of indoor LBS. The model construction and data organization of indoor map are the key scientific problems that urgently need to be solved in the current indoor LBS application. In recent years, hybrid models have been used widely in the research of indoor map, because they can balance the limitations of single models. However, the current studies about hybrid model pay more attention to the model accuracy and modeling algorithm, while ignoring its relationship between positioning and navigation and its practicality in mobile indoor LBS applications. This paper addresses a new indoor map model, named Building Information Modeling based Positioning and Navigation (BIMPN), which is based on the entity model and the network model. The highlight of BIMPN is that it proposes a concept of Step Node (SN) to assist indoor positioning and navigation function. We developed the Mobile Indoor Positioning and Navigation System (MIPNS) to verify the practicability of BIMPN. Results indicate that the BIMPN can effectively organize the characteristics of indoor spaces and the building features, and assist indoor positioning and navigation. The BIMPN proposed in this paper can be used for the construction of indoor maps and it is suitable for mobile indoor positioning and navigation systems.

scholarly journals Development of an Omnidirectional-Image-Based Data Model through Extending the IndoorGML Concept to an Indoor Patrol Service

2017 ◽  
Vol 2017 ◽  
pp. 1-14 ◽  
Author(s):  
Hyo-jin Jung ◽  
Jiyeong Lee
Keyword(s):  
Data Model ◽  
Indoor Navigation ◽  
Location Based Services ◽  
Indoor Location ◽  
Indoor Space ◽  
Omnidirectional Image ◽  
Space Data ◽  
Omnidirectional Images ◽  
Indoor Spaces ◽  
Topological Data

Different indoor representation methods have been studied for their ability to provide indoor location-based services (LBS). Among them, omnidirectional imaging is one of the most typical and simple methods for representing an indoor space. However, a georeferenced omnidirectional image cannot be used for simple attribute searches, spatial queries, and spatial awareness analyses. To perform these functions, topological data are needed to define the features of and spatial relationships among spatial objects including indoor spaces as well as facilities like CCTV cameras considered in patrol service applications. Therefore, this study proposes an indoor space application data model for an indoor patrol service that can implement functions suited to linking indoor space data and service objects. In order to do this, the study presents a method for linking data between omnidirectional images representing indoor spaces and topological data on indoor spaces based on the concept of IndoorGML. Also, we conduct an experimental implementation of the integrated 3D indoor navigation model for patrol service using GIS data. Based on the results, we evaluate the benefits of using such a 3D data fusion method that integrates omnidirectional images with vector-based topological data models based on IndoorGML for providing indoor LBS in built environments.

scholarly journals A hybrid fusion of wireless signals and RGB image for indoor positioning

2018 ◽  
Vol 14 (2) ◽  
pp. 155014771875766 ◽  
Author(s):  
Jichao Jiao ◽  
Fei Li ◽  
Weihua Tang ◽  
Zhongliang Deng ◽  
Jichang Cao
Keyword(s):  
Three Dimensional ◽  
Texture Feature ◽  
Local Binary Patterns ◽  
Indoor Positioning ◽  
Location Based Services ◽  
Coarse Grained ◽  
Wireless Data ◽  
Indoor Location ◽  
Matching Process ◽  
Positioning Algorithm

In this article, we propose a new indoor positioning algorithm using smartphones, where wireless signals and images are deeply combined together to improve the positioning performance. Our approach is based on the use of local binary patterns’ feature, which has the advantages of rotation invariance and scale invariance. Moreover, the term “uniform” are fundamental properties of local image textures and their occurrence histogram is proven to be a very powerful texture feature. Besides, the received signal strength acts as a reliable cue on a person’s identity. We first obtain a coarse-grained estimation based on the visualization of wireless signals, which are presented by a vector, making use of fingerprinting methods. Then, we perform a matching process to determine correspondences between two-dimensional pixels and three-dimensional points based on images collected by the smartphone. After being evaluated by experiments, our proposed method demonstrates that the combination of the visual and the wireless data significantly improves the positioning accuracy and robustness. It can be widely applied to smartphones to better analyze human behavior and offer high-accuracy indoor location–based services.

scholarly journals A Simplified Method of Cartographic Visualisation of Buildings’ Interiors (2D+) for Navigation Applications

2020 ◽  
Vol 9 (6) ◽  
pp. 407
Author(s):  
Dariusz Gotlib ◽  
Michał Wyszomirski ◽  
Miłosz Gnat
Keyword(s):  
Computer Aided Design ◽  
3D Model ◽  
Three Dimensional ◽  
Original Method ◽  
Facility Management ◽  
Indoor Navigation ◽  
Location Based Services ◽  
Navigation Systems ◽  
Building Information ◽  
The One

This article proposes an original method of a coherent and simplified cartographic presentation of the interior of buildings called 2D+, which can be used in geoinformation applications that do not support an extensive three-dimensional visualisation or do not have access to a 3D model of the building. A simplified way of cartographic visualisation can be used primarily in indoor navigation systems and other location-based services (LBS) applications. It can also be useful in systems supporting facility management (FM) and various kinds of geographic information systems (GIS). On the one hand, it may increase an application’s efficiency; on the other, it may unify the method of visualisation in the absence of a building’s 3D model. Thanks to the proposed method, it is possible to achieve the same effect regardless of the data source used: Building Information Modelling (BIM), a Computer-aided Design (CAD) model, or traditional architectural and construction drawings. Such a solution may be part of a broader concept of a multi-scale presentation of buildings’ interiors. The article discusses the issues of visualising data and converting data to the appropriate coordinate system, as well as the properties of the application model of data.

scholarly journals Developing a Data Model of Indoor Points of Interest to Support Location-Based Services

2020 ◽  
Vol 2020 ◽  
pp. 1-16
Author(s):  
Alexis Richard C. Claridades ◽  
Jiyeong Lee
Keyword(s):  
Spatial Data ◽  
Data Model ◽  
Unified Modeling Language ◽  
Location Based Services ◽  
Accurate Information ◽  
Indoor Location ◽  
Unified Modeling ◽  
Points Of Interest ◽  
Sample Data ◽  
Indoor Spaces

Focus on indoor spatial applications has been rising with the growing interest in indoor spaces. Along with the widespread use of mobile devices and the internet, it has increased demands for indoor location-based services (LBS), demanding more efficient representation and management of indoor spatial data. Indoor points of interest (Indoor POI) data, representing both spaces and facilities located indoors, provide the infrastructure for these services. These datasets are vital in delivering timely and accurate information to users, such as in cases of managing indoor facilities. However, even though there are studies that explore its use across applications and efforts exerted towards the standardization of the data model, most POI development studies have focused on the outdoors and remain underdeveloped in the indoors. In this paper, we propose a spatial-temporal Indoor POI data model to provide direction for the establishment of indoor POI data and to address limitations in currently available data specifications. By exploring how different Indoor POIs are from its outdoor counterparts, particularly on extending its outdoor counterparts’ functions on searching, sharing, and labeling, we describe the data model and its components using the Unified Modeling Language (UML). We perform an SQL-based query experiment to demonstrate the potential use of the data model using sample data.

scholarly journals Smart Facility Management: Future Healthcare Organization through Indoor Positioning Systems in the Light of Enterprise BIM

Smart Cities ◽  
2020 ◽  
Vol 3 (3) ◽  
pp. 793-805
Author(s):  
Tor Åsmund Evjen ◽  
Seyed Reza Hosseini Raviz ◽  
Sobah Abbas Petersen ◽  
John Krogstie
Keyword(s):  
Data Collection ◽  
Indoor Positioning ◽  
Facility Management ◽  
Information Modeling ◽  
Holistic View ◽  
Positioning Systems ◽  
Building Information ◽  
The Status ◽  
Real Estate Management ◽  
Smart Mobile

Synthesizing the Internet of Things (IoT) with building information modeling (BIM) can improve the performance of the data collection. In this regard, BIM endeavors to enable real-time monitoring conditions of buildings. This paper is focused on the indoor positioning system (IPS) as a key enabling technology for IoT applications, which uses smart and non-smart mobile devices (object tags and beacons) with the aim of positioning and objects tracking that lead to a smart approach in the field of facility management (FM). Hence, we have surveyed the joint use of IPS and BIM in FM based on the concept of enterprise BIM (EBIM). EBIM forms the basis for the future strategic real estate management using virtual models and open standards. As a result, we gained the ability to collect positioning data continuously, save them in a BIM database, and present them on two-dimensional (2D) maps. This is a part of an ongoing study that aims to use data collection effectively for FM as an organizational function in large and complex buildings. Hence, for this purpose, we have considered St. Olavs Hospital, one of the biggest healthcare centers in Norway, as a case study. The effectiveness of data collection by IoT devices installed in buildings and how the combination of BIM and IoT technology can support a holistic view of the status of the buildings, which subsequently can enhance data usage efficiency and FM development, will be demonstrated.

scholarly journals EXTRACTING TOPOLOGICAL RELATIONS BETWEEN INDOOR SPACES FROM POINT CLOUDS

2017 ◽  
Vol IV-2/W4 ◽  
pp. 401-406 ◽  
Author(s):  
H. Tran ◽  
K. Khoshelham ◽  
A. Kealy ◽  
L. Díaz-Vilariño
Keyword(s):  
Emergency Management ◽  
Principal Components ◽  
Point Clouds ◽  
3D Models ◽  
Indoor Navigation ◽  
Location Based Services ◽  
Indoor Environments ◽  
Topological Relations ◽  
Indoor Location ◽  
Indoor Spaces

3D models of indoor environments are essential for many application domains such as navigation guidance, emergency management and a range of indoor location-based services. The principal components defined in different BIM standards contain not only building elements, such as floors, walls and doors, but also navigable spaces and their topological relations, which are essential for path planning and navigation. We present an approach to automatically reconstruct topological relations between navigable spaces from point clouds. Three types of topological relations, namely containment, adjacency and connectivity of the spaces are modelled. The results of initial experiments demonstrate the potential of the method in supporting indoor navigation.

scholarly journals Improving Room-Level Location for Indoor Trajectory Tracking with Low IPS Accuracy

2021 ◽  
Vol 10 (9) ◽  
pp. 620
Author(s):  
Taehoon Kim ◽  
Kyoung-Sook Kim ◽  
Ki-Joune Li
Keyword(s):  
Moving Objects ◽  
Three Dimensional ◽  
Synthetic Data ◽  
Geographic Location ◽  
Indoor Positioning ◽  
Location Based Services ◽  
Ultra Wideband ◽  
Map Matching ◽  
Unit Space ◽  
Indoor Spaces

With the development of indoor positioning methods, such as Wi-Fi positioning, geomagnetic sensor positioning, Ultra-Wideband positioning, and pedestrian dead reckoning, the area of location-based services (LBS) is expanding from outdoor to indoor spaces. LBS refers to the geographic location information of moving objects to provide the desired services. Most Wi-Fi-based indoor positioning methods provide two-dimensional (2D) or three-dimensional (3D) coordinates in 1–5 m of accuracy on average approximately. However, many applications of indoor LBS are targeted to specific spaces such as rooms, corridors, stairs, etc. Thus, they require determining a service space from a coordinate in indoor spaces. In this paper, we propose a map matching method to assign an indoor position to a unit space a subdivision of an indoor space, called USMM (Unit Space Map Matching). Map matching is a commonly used localization improvement method that utilizes spatial constraints. We consider the topological information between unit spaces and moving objects’ probabilistic properties, compared to existing room-level mappings based on sensor signals, especially received signal strength-based fingerprinting. The proposed method has the advantage of calculating the probability even if there is only one input trajectory. Last, we analyze the accuracy and performance of the proposed USMM methods by extensive experiments in real and synthetic environments. The experimental results show that our methods bring a significant improvement when the accuracy level of indoor positioning is low. In experiments, the room-level location accuracy improves by almost 30% and 23% with real and synthetic data, respectively. We conclude that USMM methods are helpful to correct valid room-level locations from given positioning locations.

scholarly journals CAPTURE: A Mobile Based Indoor Positioning System using Wireless Indoor Positioning System

2018 ◽  
Vol 12 (1) ◽  
pp. 61 ◽  
Author(s):  
Yohanes Erwin Dari ◽  
Suyoto Suyoto Suyoto ◽  
Pranowo Pranowo Pranowo
Keyword(s):  
Nearest Neighbor ◽  
Access Point ◽  
Indoor Positioning ◽  
Location Based Services ◽  
Positioning System ◽  
K Nearest Neighbor ◽  
Indoor Location ◽  
Pointing Device ◽  
Accurate Position ◽  
Indoor Positioning System

The existence of mobile devices as a location pointing device using Global Positioning System (GPS) is a very common thing nowadays. The use of GPS as a tool to determine the location of course has a shortage when used indoors. Therefore, the used of indoor location-based services in a room that leverages the use of Access Point (AP) is very important. By using the information of the Received Signal Strength (RSS) obtained from AP, then the location of the device can be determined without the need to use GPS. This technique is called the location fingerprint technique using the characteristics of received RSS’s fingerprint, then use it to determine the position. To get a more accurate position then authors used the K-Nearest Neighbor (KNN) method. KNN will use some of the data that obtained from some AP to assist in positioning the device. This solution of course would be able to determine the position of the devices in a storied building.

scholarly journals Smartphone Sensor Based Indoor Positioning: Current Status, Opportunities, and Future Challenges

Electronics ◽  
2020 ◽  
Vol 9 (6) ◽  
pp. 891
Author(s):  
Imran Ashraf ◽  
Soojung Hur ◽  
Yongwan Park
Keyword(s):  
Radio Frequency Identification ◽  
Indoor Localization ◽  
Indoor Positioning ◽  
Location Based Services ◽  
Ultra Wideband ◽  
Current Status ◽  
Indoor Location ◽  
Use Of Data ◽  
Future Challenges ◽  
Smartphone Sensors

The last two decades have witnessed a rich variety of indoor positioning and localization research. Starting with Microsoft Research pioneering the fingerprint approach based RADAR, MIT’s Cricket, and then moving towards beacon-based localization are few among many others. In parallel, researchers looked into other appealing and promising technologies like radio frequency identification, ultra-wideband, infrared, and visible light-based systems. However, the proliferation of smartphones over the past few years revolutionized and reshaped indoor localization towards new horizons. The deployment of MEMS sensors in modern smartphones have initiated new opportunities and challenges for the industry and academia alike. Additionally, the demands and potential of location-based services compelled the researchers to look into more robust, accurate, smartphone deployable, and context-aware location sensing. This study presents a comprehensive review of the approaches that make use of data from one or more sensors to estimate the user’s indoor location. By analyzing the approaches leveraged on smartphone sensors, it discusses the associated challenges of such approaches and points out the areas that need considerable research to overcome their limitations.

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