scholarly journals Semantic VPS for Smartphone Localization in Challenging Urban Environments

Sensors ◽  
2021 ◽  
Vol 21 (18) ◽  
pp. 6137
Author(s):  
Max Jwo Lem Lee ◽  
Li-Ta Hsu ◽  
Hoi-Fung Ng
Keyword(s):  
Smart Cities ◽  
Satellite System ◽  
Urban Environments ◽  
Position Estimation ◽  
Information Modeling ◽  
Position Information ◽  
Precise Position ◽  
Segmented Images ◽  
Building Information ◽  
Global Navigation Satellite

Accurate smartphone-based outdoor localization systems in deep urban canyons are increasingly needed for various IoT applications. As smart cities have developed, building information modeling (BIM) has become widely available. This article, for the first time, presents a semantic Visual Positioning System (VPS) for accurate and robust position estimation in urban canyons where the global navigation satellite system (GNSS) tends to fail. In the offline stage, a material segmented BIM is used to generate segmented images. In the online stage, an image is taken with a smartphone camera that provides textual information about the surrounding environment. The approach utilizes computer vision algorithms to segment between the different types of material class identified in the smartphone image. A semantic VPS method is then used to match the segmented generated images with the segmented smartphone image. Each generated image contains position information in terms of latitude, longitude, altitude, yaw, pitch, and roll. The candidate with the maximum likelihood is regarded as the precise position of the user. The positioning result achieved an accuracy of 2.0 m among high-rise buildings on a street, 5.5 m in a dense foliage environment, and 15.7 m in an alleyway. This represents an improvement in positioning of 45% compared to the current state-of-the-art method. The estimation of yaw achieved accuracy of 2.3°, an eight-fold improvement compared to the smartphone IMU.

scholarly journals TDMA Datalink Cooperative Navigation Algorithm Based on INS/JTIDS/BA

Electronics ◽  
2021 ◽  
Vol 10 (7) ◽  
pp. 782
Author(s):  
Shuo Cao ◽  
Honglei Qin ◽  
Li Cong ◽  
Yingtao Huang
Keyword(s):  
Distribution System ◽  
Large Scale ◽  
Satellite System ◽  
Time Of Arrival ◽  
Military Operations ◽  
Position Information ◽  
Cooperative Navigation ◽  
Navigation Algorithm ◽  
Geometric Dilution Of Precision ◽  
Global Navigation Satellite

Position information is very important tactical information in large-scale joint military operations. Positioning with datalink time of arrival (TOA) measurements is a primary choice when a global navigation satellite system (GNSS) is not available, datalink members are randomly distributed, only estimates with measurements between navigation sources and positioning users may lead to a unsatisfactory accuracy, and positioning geometry of altitude is poor. A time division multiple address (TDMA) datalink cooperative navigation algorithm based on INS/JTIDS/BA is presented in this paper. The proposed algorithm is used to revise the errors of the inertial navigation system (INS), clock bias is calibrated via round-trip timing (RTT), and altitude is located with height filter. The TDMA datalink cooperative navigation algorithm estimate errors are stated with general navigation measurements, cooperative navigation measurements, and predicted states. Weighted horizontal geometric dilution of precision (WHDOP) of the proposed algorithm and the effect of the cooperative measurements on positioning accuracy is analyzed in theory. We simulate a joint tactical information distribution system (JTIDS) network with multiple members to evaluate the performance of the proposed algorithm. The simulation results show that compared to an extended Kalman filter (EKF) that processes TOA measurements sequentially and a TDMA datalink navigation algorithm without cooperative measurements, the TDMA datalink cooperative navigation algorithm performs better.

scholarly journals Many Ways Lead to the Goal—Possibilities of Autonomous and Infrastructure-Based Indoor Positioning

Electronics ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 397
Author(s):  
Hossein Shoushtari ◽  
Thomas Willemsen ◽  
Harald Sternberg
Keyword(s):  
Mobile Networks ◽  
Dead Reckoning ◽  
Simulated Data ◽  
Minimum Cost ◽  
Cost Effective ◽  
Satellite System ◽  
Position Estimation ◽  
Robust Solution ◽  
Position Data ◽  
Global Navigation Satellite

There are many ways to navigate in Global Navigation Satellite System-(GNSS) shaded areas. Reliable indoor pedestrian navigation has been a central aim of technology researchers in recent years; however, there still exist open challenges requiring re-examination and evaluation. In this paper, a novel dataset is used to evaluate common approaches for autonomous and infrastructure-based positioning methods. The autonomous variant is the most cost-effective realization; however, realizations using the real test data demonstrate that the use of only autonomous solutions cannot always provide a robust solution. Therefore, correction through the use of infrastructure-based position estimation based on smartphone technology is discussed. This approach invokes the minimum cost when using existing infrastructure, whereby Pedestrian Dead Reckoning (PDR) forms the basis of the autonomous position estimation. Realizations with Particle Filters (PF) and a topological approach are presented and discussed. Floor plans and routing graphs are used, in this case, to support PDR positioning. The results show that the positioning model loses stability after a given period of time. Fifth Generation (5G) mobile networks can enable this feature, as well as a massive number of use-cases, which would benefit from user position data. Therefore, a fusion concept of PDR and 5G is presented, the benefit of which is demonstrated using the simulated data. Subsequently, the first implementation of PDR with 5G positioning using PF is carried out.

scholarly journals Towards Effective BIM/GIS Data Integration for Smart City by Integrating Computer Graphics Technique

2021 ◽  
Vol 13 (10) ◽  
pp. 1889
Author(s):  
Junxiang Zhu ◽  
Peng Wu
Keyword(s):  
Computer Graphics ◽  
Smart City ◽  
Smart Cities ◽  
Information Modeling ◽  
Data Conversion ◽  
Geography Markup Language ◽  
Building Models ◽  
Digital Twins ◽  
Gis Data ◽  
Building Information

The development of a smart city and digital twin requires the integration of Building Information Modeling (BIM) and Geographic Information Systems (GIS), where BIM models are to be integrated into GIS for visualization and/or analysis. However, the intrinsic differences between BIM and GIS have led to enormous problems in BIM-to-GIS data conversion, and the use of City Geography Markup Language (CityGML) has further escalated this issue. This study aims to facilitate the use of BIM models in GIS by proposing using the shapefile format, and a creative approach for converting Industry Foundation Classes (IFC) to shapefile was developed by integrating a computer graphics technique. Thirteen building models were used to validate the proposed method. The result shows that: (1) the IFC-to-shapefile conversion is easier and more flexible to realize than the IFC-to-CityGML conversion, and (2) the computer graphics technique can improve the efficiency and reliability of BIM-to-GIS data conversion. This study can facilitate the use of BIM information in GIS and benefit studies working on digital twins and smart cities where building models are to be processed and integrated in GIS, or any other studies that need to manipulate IFC geometry in depth.

scholarly journals Simulation of GNSS Availability in Urban Environments Using a Panoramic Image Dataset

2017 ◽  
Vol 2017 ◽  
pp. 1-12 ◽  
Author(s):  
Sakpod Tongleamnak ◽  
Masahiko Nagai
Keyword(s):  
Urban Areas ◽  
Accuracy Assessment ◽  
Satellite System ◽  
Urban Environments ◽  
Panoramic Image ◽  
Image Processing Techniques ◽  
Gnss Positioning ◽  
Image Dataset ◽  
Global Navigation Satellite ◽  
Processing Techniques

Performance of Global Navigation Satellite System (GNSS) positioning in urban environments is hindered by poor satellite availability because there are many man-made and natural objects in urban environments that obstruct satellite signals. To evaluate the availability of GNSS in cities, this paper presents a software simulation of GNSS availability in urban areas using a panoramic image dataset from Google Street View. Photogrammetric image processing techniques are applied to reconstruct fisheye sky view images and detect signal obstacles. Two comparisons of the results from the simulation and real world observation in Bangkok and Tokyo are also presented and discussed for accuracy assessment.

scholarly journals Investigation of Tightly Combined Single-Frequency and Single-Epoch Precise Positioning Using Multi-GNSS Data

2020 ◽  
Vol 12 (2) ◽  
pp. 285
Author(s):  
Chenlong Deng ◽  
Qian Liu ◽  
Xuan Zou ◽  
Weiming Tang ◽  
Jianhui Cui ◽  
...  
Keyword(s):  
Satellite System ◽  
Position Estimation ◽  
Single Frequency ◽  
Navigation Satellite ◽  
Typical Situation ◽  
Practical Algorithms ◽  
Ambiguity Fixing ◽  
Global Navigation ◽  
Global Navigation Satellite ◽  
Tc Model

The loose combination (LC) and the tight combination (TC) are two different models in the combined processing of four global navigation satellite systems (GNSSs). The former is easy to implement but may be unusable with few satellites, while the latter should cope with the inter-system bias (ISB) and is applicable for few tracked satellites. Furthermore, in both models, the inter-frequency bias (IFB) in the GLObal NAvigation Satellite System (GLONASS) system should also be removed. In this study, we aimed to investigate the performance difference of ambiguity resolution and position estimation between these two models simultaneously using the single-frequency data of all four systems (GPS + GLONASS + Galileo + BeiDou Navigation Satellite System (BDS)) in three different environments, i.e., in an open area, with surrounding high buildings, and under a block of high buildings. For this purpose, we first provide the definition of ISB and IFB from the perspective of the hardware delays, and then propose practical algorithms to estimate the IFB rate and ISB. Thereafter, a comprehensive performance comparison was made between the TC and LC models. Experiments were conducted to simulate the above three observation environments: the typical situation and situations suffering from signal obstruction with high elevation angles and limited azimuths, respectively. The results show that in a typical situation, the TC and LC models achieve a similar performance. However, when the satellite signals are severely obstructed and few satellites are tracked, the float solution and ambiguity fixing rates in the LC model are dramatically decreased, while in the TC model, there are only minor declines and the difference in the ambiguity fixing rates can be as large as 30%. The correctly fixed ambiguity rates in the TC model also had an improvement of around 10%. Once the ambiguity was fixed, both models achieved a similar positioning accuracy.

scholarly journals Concatenated Coding for GNSS Signals in Urban Environments

2020 ◽  
Vol 10 (18) ◽  
pp. 6397
Author(s):  
Jing Ke ◽  
Xiaochun Lu ◽  
Xue Wang ◽  
Xiaofei Chen ◽  
Sheng Tang
Keyword(s):  
Error Correction ◽  
Additive White Gaussian Noise ◽  
Ldpc Codes ◽  
Ldpc Code ◽  
Satellite System ◽  
Urban Environments ◽  
Shadow Fading ◽  
Concatenated Coding ◽  
Concatenated Code ◽  
Global Navigation Satellite

This work investigated concatenated coding schemes for Global Navigation Satellite System (GNSS) signals in order to increase their error correction capability in urban environments. In particular, a serial concatenated code that combines an outer Reed–Solomon (RS) code with an inner low-density parity-check (LDPC) code was designed, and the performance was investigated over the land mobile satellite (LMS) channel for characterizing multipath and shadow fading in urban environments. The performance of the proposed concatenated coding scheme was compared to that of a B-CNAV1 message, in which two interleaved 64-ary LDPC codes were employed. The simulation results demonstrate that the proposed concatenated code can obtain a similar error correction performance to the two interleaved 64-ary LDPC codes in both the additive white Gaussian noise (AWGN) and LMS channels at a lower complexity level.

scholarly journals AI-Based Sensor Information Fusion for Supporting Deep Supervised Learning

Sensors ◽  
2019 ◽  
Vol 19 (6) ◽  
pp. 1345 ◽  
Author(s):  
Carson Leung ◽  
Peter Braun ◽  
Alfredo Cuzzocrea
Keyword(s):  
Supervised Learning ◽  
Information Fusion ◽  
Smart Cities ◽  
Satellite System ◽  
Sensor Data ◽  
Fusion System ◽  
Sensor Information ◽  
Global Navigation Satellite ◽  
Effective Integration ◽  
The Internet Of Things

In recent years, artificial intelligence (AI) and its subarea of deep learning have drawn the attention of many researchers. At the same time, advances in technologies enable the generation or collection of large amounts of valuable data (e.g., sensor data) from various sources in different applications, such as those for the Internet of Things (IoT), which in turn aims towards the development of smart cities. With the availability of sensor data from various sources, sensor information fusion is in demand for effective integration of big data. In this article, we present an AI-based sensor-information fusion system for supporting deep supervised learning of transportation data generated and collected from various types of sensors, including remote sensed imagery for the geographic information system (GIS), accelerometers, as well as sensors for the global navigation satellite system (GNSS) and global positioning system (GPS). The discovered knowledge and information returned from our system provides analysts with a clearer understanding of trajectories or mobility of citizens, which in turn helps to develop better transportation models to achieve the ultimate goal of smarter cities. Evaluation results show the effectiveness and practicality of our AI-based sensor information fusion system for supporting deep supervised learning of big transportation data.

scholarly journals A Smart Campus’ Digital Twin for Sustainable Comfort Monitoring

2020 ◽  
Vol 12 (21) ◽  
pp. 9196 ◽  
Author(s):  
Agustín Zaballos ◽  
Alan Briones ◽  
Alba Massa ◽  
Pol Centelles ◽  
Víctor Caballero
Keyword(s):  
Information And Communication Technologies ◽  
Environmental Sustainability ◽  
Smart Cities ◽  
Geographical Area ◽  
Information Modeling ◽  
Physical Parameters ◽  
Modeling Tools ◽  
Student Activities ◽  
Increase Energy Efficiency ◽  
Building Information

Interdisciplinary cross-cultural and cross-organizational research offers great opportunities for innovative breakthroughs in the field of smart cities, yet it also presents organizational and knowledge development hurdles. Smart cities must be large towns able to sustain the needs of their citizens while promoting environmental sustainability. Smart cities foment the widespread use of novel information and communication technologies (ICTs); however, experimenting with these technologies in such a large geographical area is unfeasible. Consequently, smart campuses (SCs), which are universities where technological devices and applications create new experiences or services and facilitate operational efficiency, allow experimentation on a smaller scale, the concept of SCs as a testbed for a smart city is gaining momentum in the research community. Nevertheless, while universities acknowledge the academic role of a smart and sustainable approach to higher education, campus life and other student activities remain a mystery, which have never been universally solved. This paper proposes a SC concept to investigate the integration of building information modeling tools with Internet of Things- (IoT)-based wireless sensor networks in the fields of environmental monitoring and emotion detection to provide insights into the level of comfort. Additionally, it explores the ability of universities to contribute to local sustainability projects by sharing knowledge and experience across a multi-disciplinary team. Preliminary results highlight the significance of monitoring workspaces because productivity has been proven to be directly influenced by environment parameters. The comfort-monitoring infrastructure could also be reused to monitor physical parameters from educational premises to increase energy efficiency.

A Hybrid Intelligent Algorithm DGP-MLP for GNSS/INS Integration during GNSS Outages

2018 ◽  
Vol 72 (2) ◽  
pp. 375-388 ◽  
Author(s):  
Yuexin Zhang ◽  
Lihui Wang
Keyword(s):  
Satellite System ◽  
Micro Electro Mechanical System ◽  
Real Field ◽  
Prediction Errors ◽  
Integrated Navigation ◽  
Intelligent Algorithm ◽  
Position Information ◽  
Hybrid Intelligent Algorithm ◽  
Global Navigation Satellite ◽  
Adaptively Adjusting

The performance of Global Navigation Satellite System (GNSS) and Micro-Electro-Mechanical System (MEMS)-based Inertial Navigation System (INS) integrated navigation is reduced during GNSS outages. To bridge the period during GNSS outages, a novel hybrid intelligent algorithm incorporating a Discrete Grey Predictor (DGP) and a Multilayer Perceptron (MLP) neural network (DGP-MLP) is proposed. The DGP-MLP is used to provide a pseudo-GNSS position to correct the INS errors during GNSS outages; the DGP uses the GNSS position information of the latest few moments to predict the position of future moments; in the process of DGP-MLP, the MLP is used to modify the prediction errors of DGP, and the MLP is improved by adding momentum terms and adaptively adjusting the learning rate and momentum factor. To evaluate the effectiveness of the proposed methodology, four GNSS outages in different cases over a real field test data were employed. The experimental results demonstrate that the proposed methodology can significantly improve positioning accuracy during GNSS outages.

4D BIM models for smart utility relocation management in urban infrastructure projects

Facilities ◽  
2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Aneetha Vilventhan ◽  
Sanu Razin ◽  
R. Rajadurai
Keyword(s):  
Construction Projects ◽  
3D Visualization ◽  
Urban Environments ◽  
Information Modeling ◽  
Urban Setting ◽  
Content Type ◽  
Urban City ◽  
Building Information ◽  
Utility Information ◽  
Communication And Coordination

Purpose The relocation of existing underground utilities in urban environments is complex because of the existence of multiple utility agencies being responsible for numerous utilities and over constrained space and time to execute maintenance works. Unfamiliar location and insufficient records of maintenance data hamper the flow of work, causing unnecessary delays and conflicts. The aim of the paper is to explore 4 dimensional Building Information Modeling as a smart solution for the management of multiple utility data for a relocation project in an urban setting. Design/methodology/approach An empirical case-based research methodology is used to collect data and develop the BIM models. Two ongoing construction projects in an urban city are empirically studied, and 4D BIM models of identified utilities are developed to assist management and relocation of existing utilities. Findings The developed BIM models enabled the location of existing sub-surface utilities through 3D visualization and also enabled clash detection. The 4D simulation of BIM model enabled the tracking of actual progress of relocation works and thereby helped in taking necessary actions to minimize forthcoming delays. The evaluation of the developed model showed that the application of 4D BIM improved communication and coordination during utility relocation works. Practical implications 4D BIM for utility infrastructure provides better management of utility information. They provide utility stakeholders an efficient way to coordinate, manage utility relocation processes through improved visualization and communication with a reduction in delays and conflicts. Originality/value Limited efforts were made using 3D BIM for sub-surface utility infrastructure in visualization and management of utility information. Efforts using 4D BIM in coordination and management of utility projects are left unexplored. This study adds value to the current literature through the application of 4D BIM for utility relocation projects.

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