Architecture, Technologies, and Applications of Location-Based Services

Kung, Hsu-Yang; Yue, Xiao-Guang; Chen, Chi-Hua; Hwang, Feng-Jang

doi:https://doi.org/10.1155/2023/9796535

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Architecture, Technologies, and Applications of Location-Based Services

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Editorial | Open Access

Volume 2023 | Article ID 9796535 | https://doi.org/10.1155/2023/9796535

Architecture, Technologies, and Applications of Location-Based Services

Hsu-Yang Kung,¹Xiao-Guang Yue,²Chi-Hua Chen,³and Feng-Jang Hwang⁴

Received14 Jun 2022

Accepted14 Jun 2022

Published28 Jul 2023

Several location-based service (LBS) applications (e.g., navigation [1], location tracking [2], intelligent transportation systems (ITS) [3–6], location-based mobile commerce [7], location-based emergency services [8], and location-based event recommendation [9]) have been designed and implemented based on advanced positioning techniques and mobile/cellular communication techniques. For obtaining the LBS applications, mobile devices (MDs) and LBS servers are designed in the architecture of LBS. The LBS servers can receive and analyze the location information of MDs which can be estimated by advanced positioning techniques (e.g., satellite positioning, and mobile positioning) for providing LBS applications. For improving the accuracy of location information, the network signals including angle of arrival [10], time differences [11–14], and received signal strength indication (RSSI) [15] from satellites networks [16], mobile/cellular networks [17], and wireless networks [18] could be collected and analyzed to obtain more precise location information. Moreover, in recent years, artificial intelligence (AI) techniques including expert systems, rule-based systems, machine learning (ML) methods [19], and deep learning (DL) methods [20] have been adopted for the development of LBS applications. A variety of LBS applications in companies, organizations, and governments have been designed and implemented for obtaining location-based information and LBS to their MDs. This special issue covers LBS architectures [21], satellite positioning techniques [22], mobile positioning techniques [23], positioning techniques based on ML methods [24], communication techniques [25], and ITS [26–28]. This special issue has collected papers on the principles of LBS and LBS technologies including the advanced satellites positioning techniques, advanced mobile/cellular positioning techniques, advanced indoor/outdoor positioning techniques, advanced ITS, advanced positioning techniques based on ML methods, advanced positioning techniques based on DL methods, advanced positioning techniques based on information security and network security techniques, advanced positioning techniques based on parallel computing and distributed computing techniques, and the implementation of LBS applications for smartphones [29–33]. The LBS applications in ITS, indoor/outdoor navigation systems, LBS for industry applications, LBS for education applications, LBS for art applications, and LBS for sport applications have also been mentioned. Topics covered in this special issue are categorized into the following eight themes: (1) mobile positioning methods, (2) navigation applications, (3) logistic applications, (4) core techniques, (5) LBS for industry, (6) LBS for education, (7) LBS for art, and (8) LBS for sports. A total of 32 accepted papers have been published; these papers are categorized into the aforementioned eight themes that are briefly introduced in this paper.

1. Mobile Positioning Methods

This special issue includes five papers on mobile positioning methods which are listed as follows. The RSSIs from mobile/cellular networks, wireless networks, wireless sensor networks, and heterogeneous network were collected and analyzed for indoor positioning [34–37]. Furthermore, the signals from satellites networks were collected and analyzed for outdoor positioning [38]. Detailed information of each article could be found in [34–38].

This special issue includes four papers on navigation applications which are listed as follows. The navigation applications based on LSB were developed for cleaning robots [39] and smart home service robots [40]. Moreover, the LBS and virtual reality techniques were implemented for tourism applications [41, 42]. Detailed information of each article could be found in [39–42].

3. Logistic Applications

This special issue includes three papers on logistic applications which are listed as follows. ML methods [43], game theory [44], and internet of things (IoT) [45] were developed for logistic applications based on LBS. Detailed information of each article regarding logistic applications could be found in [43–45].

4. Core Techniques

This special issue includes five papers on core techniques which are listed as follows. For improving optimization techniques, advanced particle swarm optimization (PSO) [46] and advanced Multiobjective Optimization (MO) [47, 48] were proposed to obtain LBS applications. For improving security and networking techniques, advanced network security technology [49] and advanced satellite channel allocation schemes were proposed to obtain LBS applications. Detailed information of each article on core techniques could be found in [46–50].

5. LBS for Industry

This special issue includes five papers on LBS for industry which are listed as follows. LSB techniques were applied on enterprise management systems [51], improved LSTM models for industry system [52], human-machine interfaces [53], e-commerce services [54], and public safety evaluation system [55] for providing industry applications. Detailed information of each article related to LBS for industry could be found in [51–55].

6. LBS for Education

This special issue includes five papers on LBS for education which are listed as follows. LSB techniques were applied on vertical search methods [56], cloud classrooms [57], speech recognition [58], data stream classification [59], and online learning support service system based on LBS for providing education applications. Detailed information of each article on LBS for education could be found in [56–60].

7. LBS for Art

This special issue includes two papers on LBS for art which are listed as follows. The art applications based on LSB were developed for AI-based computer-aided arts [61] and visual communication art [62]. Detailed information of each article with respect to LBS for art could be found in [61, 62].

8. LBS for Sports

This special issue includes three papers on LBS for sport which are listed as follows. LSB techniques were applied on Athletes’ abnormal training [63], sport performance prediction [64], and biomechanical simulation and simulation [65]. Detailed information of each article on LBS for sports could be found in [63–65].

Conflicts of Interest

The authors declare no conflicts of interest.

Hsu-Yang Kung
Xiao-Guang Yue
Chi-Hua Chen
Feng-Jang Hwang

References

G. Y. Chen, M. Gan, C. L. P. Chen, and L. Chen, “A two-stage estimation algorithm based on variable projection method for GPS positioning,” IEEE Transactions on Instrumentation and Measurement, vol. 67, no. 11, pp. 2518–2525, 2018.
View at: Publisher Site | Google Scholar
Z. Yu, L. Han, C. Chen, W. Guo, and Z. Yu, “Object tracking by the least spatiotemporal searches,” IEEE Internet of Things Journal, vol. 8, no. 16, pp. 12934–12946, 2021.
View at: Publisher Site | Google Scholar
M. He and F. Chen, “Extinction and stability of an impulsive system with pure delays,” Applied Mathematics Letters, vol. 91, pp. 128–136, 2019.
View at: Publisher Site | Google Scholar
C. H. Chen, F. J. Hwang, and H. Y. Kung, “Travel time prediction system based on data clustering for waste collection vehicles,” IEICE Transactions on Information and Systems, vol. E102.D, no. 7, pp. 1374–1383, 2019.
View at: Publisher Site | Google Scholar
M. Pan, Y. Liu, J. Cao, Y. Li, C. Li, and C. H. Chen, “Visual recognition based on deep learning for navigation mark classification,” IEEE Access, vol. 8, pp. 32767–32775, 2020.
View at: Publisher Site | Google Scholar
X. Ke and Y. Zhang, “Fine-grained vehicle type detection and recognition based on dense attention network,” Neurocomputing, vol. 399, pp. 247–257, 2020.
View at: Publisher Site | Google Scholar
P. Ramasamy, V. Ranganathan, V. Palanisamy, and S. Kadry, “Securing one-time password generation using elliptic-curve cryptography with self-portrait photograph for mobile commerce application,” Multimedia Tools and Applications, vol. 79, no. 23-24, pp. 17081–17099, 2020.
View at: Publisher Site | Google Scholar
C. L. Chen, T. T. Yang, Y. Y. Deng, and C. H. Chen, “A secure Internet of Things medical information sharing and emergency notification system based on nonrepudiation mechanism,” Wireless Communications and Mobile Computing, vol. 32, no. 5, 2021.
View at: Publisher Site | Google Scholar
X. Liao, L. Zhang, J. Wei, D. Yang, and G. Chen, “Recommending mobile microblog users via a tensor factorization based on user cluster approach,” Wireless Communications and Mobile Computing, vol. 2018, Article ID 9434239, 11 pages, 2018.
View at: Publisher Site | Google Scholar
Y. Ma, L. Yang, and X. Zheng, “A geometry-based non-stationary MIMO channel model for vehicular communications,” China Communications, vol. 15, no. 7, pp. 30–38, 2018.
View at: Publisher Site | Google Scholar
B. V. Krishnaveni, K. S. Reddy, and P. R. Reddy, “Indoor positioning and tracking by coupling IMU and UWB with the extended Kalman filter,” IETE Journal of Research, pp. 1–10, 2022.
View at: Publisher Site | Google Scholar
M. Martalo, S. Perri, G. Verdano, F. De Mola, F. Monica, and G. Ferrari, “Improved UWB TDoA-based positioning using a single hotspot for industrial IoT applications,” IEEE Transactions on Industrial Informatics, vol. 18, no. 6, pp. 3915–3925, 2022.
View at: Publisher Site | Google Scholar
O. Bialer, D. Raphaeli, and A. J. Weiss, “Unsynchronized OFDM network positioning in multipath,” Signal Processing, vol. 168, p. 107344, 2020.
View at: Publisher Site | Google Scholar
Y. Wang, X. Shang, and K. Peng, “Relocating mining microseismic earthquakes in a 3-D velocity model using a windowed cross-correlation technique,” IEEE Access, vol. 8, pp. 37866–37878, 2020.
View at: Publisher Site | Google Scholar
C. Guo, L. Wu, C. Shi, and C. H. Chen, “Mobile positioning based on TAE-GRU,” in Proceedings of the 2021 Web Conference, Ljubljana, Slovenia, April 2021.
View at: Google Scholar
Q. Guan, C. Fan, J. Zheng, G. Wang, and G. Chen, “Multistep weighted least squares estimation method for improving single-point positioning accuracy,” Wireless Communications and Mobile Computing, vol. 13, no. 3, 2019.
View at: Publisher Site | Google Scholar
H. Y. Kung, C. H. Chen, M. H. Lin, and T. Y. Wu, “Design of seamless handoff control based on vehicular streaming communications,” Journal of Internet Technology, vol. 20, no. 7, pp. 2083–2097, 2019.
View at: Google Scholar
N. N. Xiong, W. Wu, C. Wu, and H. Cheng, “An improved node localization algorithm based on positioning accurately in WSN,” Journal of Internet Technology, vol. 20, no. 5, pp. 1323–1332, 2019.
View at: Google Scholar
R. Cheng, Y. Song, D. Chen, and X. Ma, “Intelligent positioning approach for high speed trains based on ant colony optimization and machine learning algorithms,” IEEE Transactions on Intelligent Transportation Systems, vol. 20, no. 10, pp. 3737–3746, 2019.
View at: Publisher Site | Google Scholar
C. Shi, L. Fang, Z. Lv, and H. Shen, “Improved generative adversarial networks for VHR remote sensing image classification,” IEEE Geoscience and Remote Sensing Letters, vol. 19, pp. 1–5, 2022.
View at: Publisher Site | Google Scholar
Y. Peng, L. Wang, J. Cui, X. Liu, H. Li, and J. Ma, “LS-RQ: a lightweight and forward-secure range query on geographically encrypted data,” IEEE Transactions on Dependable and Secure Computing, vol. 19, no. 1, pp. 388–401, 2022.
View at: Publisher Site | Google Scholar
A. Kaczmarek, W. Rohm, L. Klingbeil, and J. Tchorzewski, “Experimental 2D extended Kalman filter sensor fusion for low-cost GNSS/IMU/Odometers precise positioning system,” Measurement, vol. 193, p. 110963, 2022.
View at: Publisher Site | Google Scholar
L. Altin, R. Ahas, S. Silm, and E. Saluveer, “Megastar concerts in tourism: a study using Mobile phone data,” Scandinavian Journal of Hospitality and Tourism, vol. 22, no. 2, pp. 161–180, 2022.
View at: Publisher Site | Google Scholar
C. Shi, Y. Dang, L. Fang, Z. Lv, and M. Zhao, “Hyperspectral image classification with adversarial attack,” IEEE Geoscience and Remote Sensing Letters, vol. 19, p. 5510305, 2022.
View at: Publisher Site | Google Scholar
W. Guo, J. Li, X. Liu, and Y. Yang, “Privacy-preserving compressive sensing for real-time traffic monitoring in urban city,” IEEE Transactions on Vehicular Technology, vol. 69, no. 12, pp. 14510–14522, 2020.
View at: Publisher Site | Google Scholar
A. A. Abdallah, C. S. Jao, Z. M. Kassas, and A. M. Shkel, “A pedestrian indoor navigation system using deep-learning-aided cellular signals and ZUPT-aided foot-mounted IMUs,” IEEE Sensors Journal, vol. 22, no. 6, pp. 5188–5198, 2022.
View at: Publisher Site | Google Scholar
I. Belhajem, Y. Ben Maissa, and A. Tamtaoui, “Improving low cost sensor based vehicle positioning with machine learning,” Control Engineering Practice, vol. 74, pp. 168–176, 2018.
View at: Publisher Site | Google Scholar
K. Dalton, M. Skrobe, H. Bell et al., “Marine-related learning networks: shifting the paradigm toward collaborative ocean governance,” Frontiers in Marine Science, vol. 7, p. 595054, 2020.
View at: Publisher Site | Google Scholar
H. Chen, H. Jin, and S. Wu, “Minimizing inter-server communications by exploiting self-similarity in online social networks,” IEEE Transactions on Parallel and Distributed Systems, vol. 27, no. 4, pp. 1116–1130, 2016.
View at: Publisher Site | Google Scholar
C. Shi, Y. Dang, L. Fang, Z. Lv, and H. Shen, “Attention-guided multispectral and panchromatic image classification,” Remote Sensing, vol. 13, p. 4823, 2022.
View at: Publisher Site | Google Scholar
W. Guo, Y. Shi, and S. Wang, “A unified scheme for distance metric learning and clustering via rank-reduced regression,” IEEE Transactions on Systems, Man, and Cybernetics, vol. 51, no. 8, pp. 5218–5229, 2021.
View at: Publisher Site | Google Scholar
C. Shi, Z. Lv, H. Shen, L. Fang, and Z. You, “Improved metric learning with the CNN for very-high-resolution remote sensing image classification,” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 14, pp. 631–644, 2021.
View at: Publisher Site | Google Scholar
C. Wu, F. Wu, L. Lyu, Y. Huang, and X. Xie, “Communication-efficient federated learning via knowledge distillation,” Nature Communications, vol. 13, no. 1, p. 2032, 2022.
View at: Publisher Site | Google Scholar
X. Xue, X. Lin, C. Yang, and X. Wu, “An improved indoor positioning technique based on receiving signal’s strength,” Mobile Information Systems, vol. 2020, 8822210 pages, 2020.
View at: Google Scholar
Q. Qin, Y. Tian, and X. Wang, “Three-dimensional UWSN positioning algorithm based on modified RSSI values,” Mobile Information Systems, vol. 2021, Article ID 5554791, 8 pages, 2021.
View at: Publisher Site | Google Scholar
J. Wang, C. Guo, and L. Wu, “Gated recurrent unit with RSSIs from heterogeneous network for mobile positioning,” Mobile Information Systems, vol. 2021, Article ID 6679398, 7 pages, 2021.
View at: Publisher Site | Google Scholar
Y. Yang, C. Xiong, J. Zhuo, and M. Cai, “Detecting home and work locations from mobile phone cellular signaling data,” Mobile Information Systems, vol. 2021, Article ID 5546329, 2021.
View at: Publisher Site | Google Scholar
T. Y. Zhou and B. W. Lian, “A multipath processing technology based on multiparameter-combined observation in GNSS,” Mobile Information Systems, vol. 2021, Article ID 5574443, 11 pages, 2021.
View at: Publisher Site | Google Scholar
B. Hao, H. Du, X. Dai, and H. Liang, “Automatic recharging path planning for cleaning robots,” Mobile Information Systems, vol. 2021, Article ID 5558096, 19 pages, 2021.
View at: Publisher Site | Google Scholar
J. Peng, H. Ye, Q. He, Y. Qin, Z. Wan, and J. Lu, “Design of smart home service robot based on ROS,” Mobile Information Systems, vol. 2021, Article ID 5511546, 14 pages, 2021.
View at: Publisher Site | Google Scholar
J. H. Lo, S. D. Wu, and M. J. You, “Interactive virtual reality touring system: a case study of Shulin Ji’an Temple in Taiwan,” Mobile Information Systems, vol. 2021, Article ID 6651916, 15 pages, 2021.
View at: Publisher Site | Google Scholar
B. Deng, J. Xu, and X. Wei, “Tourism destination preference prediction based on edge computing,” Mobile Information Systems, vol. 2021, Article ID 5512008, 11 pages, 2021.
View at: Publisher Site | Google Scholar
Y. H. Lin, S. Gu, W. S. Wu, R. Wang, and F. Wu, “Analysis and prediction of overloaded extra-heavy vehicles for highway safety using machine learning,” Mobile Information Systems, vol. 2020, Article ID 6667897, 20 pages, 2020.
View at: Publisher Site | Google Scholar
F. Li, S. Luo, Y. Wang, and C. H. Wu, “Rational supplier selection based on two-phase deep analysis considering fuzzy QFD and game theory,” Mobile Information Systems, vol. 2021, Article ID 9979017, 12 pages, 2021.
View at: Publisher Site | Google Scholar
X. Xue, X. Lin, C. Yang, and X. Wu, “A supply chain information pushing method for logistics park based on internet of things technology,” Mobile Information Systems, vol. 2021, Article ID 5544607, 11 pages, 2021.
View at: Publisher Site | Google Scholar
H. Zhu, X. Xue, A. Geng, and H. Ren, “Matching sensor ontologies with simulated annealing particle swarm optimization,” Mobile Information Systems, vol. 2021, Article ID 5510055, 11 pages, 2021.
View at: Publisher Site | Google Scholar
S. Wang, “Design of minimizing expected energy of multisource wireless cooperative network based on multiobjective optimization,” Mobile Information Systems, vol. 2021, Article ID 5517029, 9 pages, 2021.
View at: Publisher Site | Google Scholar
H. Xuan, X. Zhao, L. You, Z. Liu, and Y. Li, “Multiobjective model and improved artificial raindrop algorithm for virtual network mapping,” Mobile Information Systems, vol. 2021, Article ID 5542670, 10 pages, 2021.
View at: Publisher Site | Google Scholar
N. Sun, T. Li, G. Song, and H. Xia, “Network security technology of intelligent information terminal based on mobile internet of things,” Mobile Information Systems, vol. 2021, Article ID 6676946, 9 pages, 2021.
View at: Publisher Site | Google Scholar
F. Zheng, Z. Pi, Z. Zhou, and K. Wang, “LEO satellite channel allocation scheme based on reinforcement learning,” Mobile Information Systems, vol. 2020, Article ID 8868888, 10 pages, 2020.
View at: Publisher Site | Google Scholar
Y. Yang, Z. Mei, B. Zheng, and S. Qiu, “Design of enterprise management system based on edge computing architecture,” Mobile Information Systems, vol. 2021, Article ID 5512958, 12 pages, 2021.
View at: Publisher Site | Google Scholar
T. Zheng, M. Wang, Y. Guo, and Z. Wang, “The bidirectional information fusion using an improved LSTM model,” Mobile Information Systems, vol. 2021, Article ID 5595898, 15 pages, 2021.
View at: Publisher Site | Google Scholar
S. L. Jeng, W. H. Chieng, and Y. Chen, “Web-based human-machine interfaces of industrial controllers in single-page applications,” Mobile Information Systems, vol. 2021, Article ID 6668843, 13 pages, 2021.
View at: Publisher Site | Google Scholar
Y. Si, “Research on the balanced relationship between online consumer behavior and E-commerce service quality based on 5G network,” Mobile Information Systems, vol. 2021, Article ID 5562996, 12 pages, 2021.
View at: Publisher Site | Google Scholar
Z. Zhao, “Community public safety evaluation system based on location information service architecture,” Mobile Information Systems, vol. 2021, Article ID 6694757, 10 pages, 2021.
View at: Publisher Site | Google Scholar
Y. Xie, “Research on vertical search method of multidimensional resources in English discipline based on edge computing,” Mobile Information Systems, vol. 2021, Article ID 5518135, 10 pages, 2021.
View at: Publisher Site | Google Scholar
X. Luo, “Cloud classroom design for English education based on internet of things and data mining,” Mobile Information Systems, vol. 2021, Article ID 5555006, 8 pages, 2021.
View at: Publisher Site | Google Scholar
L. Wu and L. Wu, “Research on business English translation framework based on speech recognition and wireless communication,” Mobile Information Systems, vol. 2021, Article ID 5575541, 11 pages, 2021.
View at: Publisher Site | Google Scholar
L. Lu and J. Zhou, “Research on mining of applied mathematics educational resources based on edge computing and data stream classification,” Mobile Information Systems, vol. article no. 5542718, 2021.
View at: Google Scholar
Y. Zhao and S. Shan, “Online learning support service system architecture based on location service architecture,” Mobile Information Systems, vol. 2021, Article ID 6663934, 11 pages, 2021.
View at: Publisher Site | Google Scholar
J. Deng and X. Chen, “Research on artificial intelligence interaction in computer-aided arts and crafts,” Mobile Information Systems, vol. 2021, Article ID 5519257, 14 pages, 2021.
View at: Publisher Site | Google Scholar
W. Liu, “Research on the application of multimedia elements in visual communication art under the internet background,” Mobile Information Systems, vol. 2021, Article ID 5525648, 10 pages, 2021.
View at: Publisher Site | Google Scholar
Y. Wang, “Real-time collection method of athletes’ abnormal training data based on machine learning,” Mobile Information Systems, vol. 2021, Article ID 9938605, 11 pages, 2021.
View at: Publisher Site | Google Scholar
S. Yang, L. Luo, and B. Tan, “Research on sports performance prediction based on BP neural network,” Mobile Information Systems, vol. 2021, Article ID 5578871, 8 pages, 2021.
View at: Publisher Site | Google Scholar
B. Zhang, “Research on biomechanical simulation and simulation of badminton splitting and hanging action based on edge computing,” Mobile Information Systems, vol. 2021, Article ID 5527879, 8 pages, 2021.
View at: Publisher Site | Google Scholar

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Copyright © 2023 Hsu-Yang Kung et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Mobile Information Systems

Architecture, Technologies, and Applications of Location-Based Services

Architecture, Technologies, and Applications of Location-Based Services

1. Mobile Positioning Methods

2. Navigation Applications

3. Logistic Applications

4. Core Techniques

5. LBS for Industry

6. LBS for Education

7. LBS for Art

8. LBS for Sports

Conflicts of Interest

References

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