scholarly journals Automatic Generation of High-Accuracy Stair Paths for Straight, Spiral, and Winder Stairs Using IFC-Based Models

2020 ◽  
Vol 9 (4) ◽  
pp. 215
Author(s):  
Will Y. Lin
Keyword(s):  
Emergency Evacuation ◽  
Automatic Generation ◽  
High Accuracy ◽  
Location Based Services ◽  
Test Cases ◽  
Floor Level ◽  
Indoor Location ◽  
Indoor Space ◽  
Space Model ◽  
Novel Approach

The indoor space model is the foundation of most indoor location-based services (LBS). A complete indoor space model includes floor-level paths and non-level paths. The latter includes passages connecting different floors or elevations such as stairs, elevators, escalators, and ramps. Most related studies have merely discussed the modeling and generation of floor-level paths, while those considering non-level paths usually simplify the formation and generation of non-level paths, especially stairs, which play an important role in emergency evacuation and response. Although the algorithm proposed by i-GIT approach, which considers both floor-level and non-level paths, can automatically generate paths of straight stairs, it is not applicable to the spiral stairs and winder stairs that are common in town houses and other public buildings. This study proposes a novel approach to generate high-accuracy stair paths that can support straight, spiral, and winder stairs. To implement and verify the proposed algorithm, 54 straight and spiral stairs provided by Autodesk Revit’s official website and three self-built winder stairs are used as test cases. The test results show that the algorithm can successfully produce the stair paths of most test cases (49/50), which comprehensively extends the applicability of the proposed algorithm.

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 INDOOR SPACE LOCATION MODEL BASED ON LOCATION SERVICE

2017 ◽  
Vol XLII-4/W7 ◽  
pp. 49-53
Author(s):  
Y. Zhou ◽  
G. Zeng ◽  
Y. Huang ◽  
X. Yang
Keyword(s):  
Spatial Information ◽  
Indoor Navigation ◽  
Location Model ◽  
Location Information ◽  
Location Based Service ◽  
Location Services ◽  
Indoor Location ◽  
Indoor Space ◽  
Location Service ◽  
Space Model

Location is the basis for the realization of location services, the integrity of the location information and its way of representation in indoor space model directly restricts the quality of location services. The construction of the existing indoor space model is mostly for specific applications and lack of uniform representation of location information. Several geospatial standards have been developed to meet the requirement of the indoor spatial information system, among which CityGML LOD4 and IndoorGML are the most relevant ones for indoor spatial information. However, from the perspective of Location Based Service (LBS), the CityGML LOD4 is more inclined to visualize the indoor space. Although IndoorGML is mainly used for indoor space navigation and has description (such as geometry, topology, and semantics) benefiting for indoor LBS, this standard model lack explicit representation of indoor location information. In this paper, from the perspective of Location Based Service (LBS), based on the IndoorGML standard, an indoor space location model (ISLM) conforming to human cognition is proposed through integration of the geometric and topological and semantic features of the indoor spatial entity. This model has the explicit description of location information which the standard indoor space model of IndoorGML and CityGML LOD4 does not have, which can lay the theoretical foundation for indoor location service such as indoor navigation, indoor routing and location query.

scholarly journals Ephemeral ID Beacon-Based Improved Indoor Positioning System

Symmetry ◽  
2018 ◽  
Vol 10 (11) ◽  
pp. 622 ◽  
Author(s):  
Jinsu Kang ◽  
Jeonghoon Seo ◽  
Yoojae Won
Keyword(s):  
Tracking System ◽  
Rapid Development ◽  
Communication Technologies ◽  
Location Based Services ◽  
Received Signal Strength Indicator ◽  
Indoor Location ◽  
Indoor Space ◽  
Outdoor Spaces ◽  
Physical Barriers ◽  
Positioning Algorithm

Recently, the rapid development of mobile devices and communication technologies has dramatically increased the demand for location-based services that provide users with location-oriented information and services. User location in outdoor spaces is measured with high accuracy using GPS. However, because the indoor reception of GPS signals is not smooth, this solution is not viable in indoor spaces. Many on-going studies are exploring new approaches for indoor location measurement. One popular technique involves using the received signal strength indicator (RSSI) values from the Bluetooth Low Energy (BLE) beacons to measure the distance between a mobile device and the beacons and then determining the position of the user in an indoor space by applying a positioning algorithm such as the trilateration method. However, it remains difficult to obtain accurate data because RSSI values are unstable owing to the influence of elements in the surrounding environment such as weather, humidity, physical barriers, and interference from other signals. In this paper, we propose an indoor location tracking system that improves performance by correcting unstable RSSI signals received from BLE beacons. We apply a filter algorithm based on the average filter and the Kalman filter to reduce the error range of results calculated using the RSSI values.

Geometry-Aided BLE-Based Smartphone Positioning for Indoor Location-Based Services

2020 ◽  
Author(s):  
Branislav Rudic ◽  
Maria Anneliese Klaffenbock ◽  
Markus Pichler-Scheder ◽  
Dmitry Efrosinin ◽  
Christian Kastl
Keyword(s):  
Location Based Services ◽  
Indoor Location

SiFi

2021 ◽  
Vol 2 (3) ◽  
pp. 1-21
Author(s):  
Deke Guo ◽  
Xiaoqiang Teng ◽  
Yulan Guo ◽  
Xiaolei Zhou ◽  
Zhong Liu
Keyword(s):  
Rapid Development ◽  
Estimation Method ◽  
Likelihood Estimation ◽  
Location Based Services ◽  
Shopping Mall ◽  
Inference Problem ◽  
Indoor Location ◽  
Label Semantics ◽  
Geometrical Constraints ◽  
Indoor Scenes

Due to the rapid development of indoor location-based services, automatically deriving an indoor semantic floorplan becomes a highly promising technique for ubiquitous applications. To make an indoor semantic floorplan fully practical, it is essential to handle the dynamics of semantic information. Despite several methods proposed for automatic construction and semantic labeling of indoor floorplans, this problem has not been well studied and remains open. In this article, we present a system called SiFi to provide accurate and automatic self-updating service. It updates semantics with instant videos acquired by mobile devices in indoor scenes. First, a crowdsourced-based task model is designed to attract users to contribute semantic-rich videos. Second, we use the maximum likelihood estimation method to solve the text inferring problem as the sequential relationship of texts provides additional geometrical constraints. Finally, we formulate the semantic update as an inference problem to accurately label semantics at correct locations on the indoor floorplans. Extensive experiments have been conducted across 9 weeks in a shopping mall with more than 250 stores. Experimental results show that SiFi achieves 84.5% accuracy of semantic update.

scholarly journals Extracting Stops from Spatio-Temporal Trajectories within Dynamic Contextual Features

2021 ◽  
Vol 13 (2) ◽  
pp. 690
Author(s):  
Tao Wu ◽  
Huiqing Shen ◽  
Jianxin Qin ◽  
Longgang Xiang
Keyword(s):  
Moving Objects ◽  
Major Effect ◽  
Location Based Services ◽  
Trajectory Data ◽  
The Road ◽  
Contextual Features ◽  
Novel Approach ◽  
Gps Trajectories ◽  
Time Distance ◽  
Spatio Temporal

Identifying stops from GPS trajectories is one of the main concerns in the study of moving objects and has a major effect on a wide variety of location-based services and applications. Although the spatial and non-spatial characteristics of trajectories have been widely investigated for the identification of stops, few studies have concentrated on the impacts of the contextual features, which are also connected to the road network and nearby Points of Interest (POIs). In order to obtain more precise stop information from moving objects, this paper proposes and implements a novel approach that represents a spatio-temproal dynamics relationship between stopping behaviors and geospatial elements to detect stops. The relationship between the candidate stops based on the standard time–distance threshold approach and the surrounding environmental elements are integrated in a complex way (the mobility context cube) to extract stop features and precisely derive stops using the classifier classification. The methodology presented is designed to reduce the error rate of detection of stops in the work of trajectory data mining. It turns out that 26 features can contribute to recognizing stop behaviors from trajectory data. Additionally, experiments on a real-world trajectory dataset further demonstrate the effectiveness of the proposed approach in improving the accuracy of identifying stops from trajectories.

scholarly journals Performance of Enhanced Multiple-Searching Genetic Algorithm for Test Case Generation in Software Testing

Mathematics ◽  
2021 ◽  
Vol 9 (15) ◽  
pp. 1779
Author(s):  
Wanida Khamprapai ◽  
Cheng-Fa Tsai ◽  
Paohsi Wang ◽  
Chi-En Tsai
Keyword(s):  
Genetic Algorithm ◽  
Software Testing ◽  
Random Search ◽  
Automatic Generation ◽  
Superior Performance ◽  
Test Case Generation ◽  
Test Case ◽  
Test Cases ◽  
Network Systems ◽  
Routing Problem

Test case generation is an important process in software testing. However, manual generation of test cases is a time-consuming process. Automation can considerably reduce the time required to create adequate test cases for software testing. Genetic algorithms (GAs) are considered to be effective in this regard. The multiple-searching genetic algorithm (MSGA) uses a modified version of the GA to solve the multicast routing problem in network systems. MSGA can be improved to make it suitable for generating test cases. In this paper, a new algorithm called the enhanced multiple-searching genetic algorithm (EMSGA), which involves a few additional processes for selecting the best chromosomes in the GA process, is proposed. The performance of EMSGA was evaluated through comparison with seven different search-based techniques, including random search. All algorithms were implemented in EvoSuite, which is a tool for automatic generation of test cases. The experimental results showed that EMSGA increased the efficiency of testing when compared with conventional algorithms and could detect more faults. Because of its superior performance compared with that of existing algorithms, EMSGA can enable seamless automation of software testing, thereby facilitating the development of different software packages.

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