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Design of Wearable Prototype Smart Wristband for Remote Health Monitoring Using Internet of Things Read chapter Read first chapter

2020 | OriginalPaper | Chapter

QoE Analysis of Real-Time Video Streaming over 4G-LTE for UAV-Based Surveillance Applications

Authors : Muhammad Naveed, Sameer Qazi

Published in: Intelligent Technologies and Applications

Publisher: Springer Singapore

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Abstract

Drones also known as Unmanned Aerial Vehicles (UAVs) perform an significant role in surveillance at a remote location by streaming real-time video with their attached cameras. A good architecture for such kind of surveillance is required that ensures real-time monitoring at targeted areas. As the streaming video is used in monitoring; it is much important to ensure its quality during transmission so that remote client can view clear insights and could take prompt action on time if required. In this paper, we have proposed a 4G-LTE architecture and examined the effects of different factors in such architecture. We have shown the comparative analysis between two latest codec schemes i.e. H.264 and H.265 (HEVC) in video streaming. Our study is an important step towards exploring the factors that influence the real-time video streaming and degrade the Quality of Experience (QoE) of video viewing in such architecture. To examine the received video quality, two objective metrics, Peak-Signal-to-Noise-Ratio (PSNR) and Structural-Similarity-Index (SSIM) have been considered in this paper. The simulation results are based on the most famous Network simulator in the research community i.e. NS-3. The results have shown that H.265 works better in comparison with H.264 under different circumstances.

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Literature
1.
2.
3.
4.
5.
6.
7.
8.
Amirpour, H., Pinheiro, A.M., Pereira, M., Ghanbari, M.: Reliability of the most common objective metrics for light field quality assessment. In: ICASSP 2019–2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 2402–2406. IEEE (2019)
9.
10.
Avcibaş, I., Sankur, B., Sayood, K.: Statistical evaluation of image quality measures. J. Electron. Imaging 11(2), 206–223 (2002)CrossRef
11.
Bekmezci, I., Sahingoz, O.K., Temel, Ş.: Flying ad-hoc networks (FANETs): a survey. Ad Hoc Netw. 11(3), 1254–1270 (2013)CrossRef
12.
Cadik, M., Slavik, P.: Evaluation of two principal approaches to objective image quality assessment. In: Proceedings of the Eighth International Conference on Information Visualisation, IV 2004, pp. 513–518. IEEE (2004)
13.
Challita, U., Ferdowsi, A., Chen, M., Saad, W.: Artificial intelligence for wireless connectivity and security of cellular-connected UAVs. arXiv preprint arXiv:​1804.​05348 (2018)
14.
Channappayya, S.S., Bovik, A.C., Heath, R.W.: A linear estimator optimized for the structural similarity index and its application to image denoising, October 2006
15.
Dosselmann, R., Yang, X.D.: Existing and emerging image quality metrics. In: Canadian Conference on Electrical and Computer Engineering, pp. 1906–1913. IEEE (2005)
16.
17.
Hore, A., Ziou, D.: Image quality metrics: PSNR vs. SSIM. In: 2010 20th International Conference on Pattern Recognition, pp. 2366–2369. IEEE (2010)
18.
Huynh-Thu, Q., Ghanbari, M.: Scope of validity of PSNR in image/video quality assessment. Electron. Lett. 44(13), 800 (2008)CrossRef
19.
Ivancic, W.D., Kerczewski, R.J., Murawski, R.W., Matheou, K., Downey, A.N.: Flying drones beyond visual line of sight using 4G LTE: issues and concerns. In: 2019 Integrated Communications, Navigation and Surveillance Conference (ICNS), pp. 1–13. IEEE (2019)
20.
Jiang, X., Feng, J., Song, T., Katayama, T.: Low-complexity and hardware-friendly H.265/HEVC encoder for vehicular ad-hoc networks. Sensors 19(8), 1927 (2019)CrossRef
21.
Jung, J., Yoo, S., La, W., Lee, D., Bae, M., Kim, H.: AVSS: airborne video surveillance system. Sensors 18(6), 1939 (2018)CrossRef
22.
Jung, S., Jo, Y., Kim, Y.J.: Aerial surveillance with low-altitude long-endurance tethered multirotor UAVs using photovoltaic power management system. Energies 12(7), 1323 (2019)CrossRef
23.
Karaki, H.S.A., Alomari, S.A., Refai, M.H.: A comprehensive survey of the vehicle motion detection and tracking methods for aerial surveillance videos. IJCSNS 19(1), 93 (2019)
24.
Kim, H., Ben-Othman, J.: A collision-free surveillance system using smart UAVs in multi domain IoT. IEEE Commun. Lett. 22(12), 2587–2590 (2018)CrossRef
25.
Korhonen, J., You, J.: Improving objective video quality assessment with content analysis. In: Proceedings of the International Workshop on Video Processing and Quality Metrics for Consumer Electronics, pp. 1–6 (2010)
26.
Kwak, J., Park, J.H., Sung, Y.: Emerging ICT UAV applications and services: design of surveillance UAVs. Int. J. Commun. Syst. e4023 (2019)
27.
Lee, S., et al.: Design and development of a DDDAMS-based border surveillance system via UVs and hybrid simulations. Expert Syst. Appl. 128, 109–123 (2019)CrossRef
28.
Lei, X., Jiang, X., Wang, C.: Design and implementation of a real-time video stream analysis system based on FFmpeg. In: 2013 Fourth World Congress on Software Engineering, pp. 212–216. IEEE (2013)
29.
30.
Lyon, D.: The Electronic Eye: The Rise of Surveillance Society. University of Minnesota Press, Minneapolis (1994)
31.
MacKenzie, D., Wajcman, J.: The Social Shaping of Technology. Open University Press, London (1999)
32.
Marwat, S.N.K., Meyer, S., Weerawardane, T., Goerg, C.: Congestion-aware handover in LTE systems for load balancing in transport network. ETRI J. 36(5), 761–771 (2014)CrossRef
33.
Medda, A., DeBrunner, V.: Color image quality index based on the UIQI. In: 2006 IEEE Southwest Symposium on Image Analysis and Interpretation, pp. 213–217. IEEE (2006)
34.
Mengzhe, L., Xiuhua, J., Xiaohua, L.: Analysis of H.265/HEVC, H.264 and VP9 coding efficiency based on video content complexity. In: 2015 IEEE International Conference on Computer and Communications (ICCC), pp. 420–424. IEEE (2015)
35.
Motlagh, N.H., Bagaa, M., Taleb, T.: UAV-based IoT platform: a crowd surveillance use case. IEEE Commun. Mag. 55(2), 128–134 (2017)CrossRef
36.
Motlagh, N.H., Bagaa, M., Taleb, T., Song, J.: Connection steering mechanism between mobile networks for reliable UAV’s IoT platform. In: 2017 IEEE International Conference on Communications (ICC), pp. 1–6. IEEE (2017)
37.
38.
Mustaqim, M., Khawaja, B.A., Razzaqi, A.A., Zaidi, S.S.H., Jawed, S.A., Qazi, S.H.: Wideband and high gain antenna arrays for UAV-to-UAV and UAV-to-ground communication in flying ad-hoc networks (FANETs). Microwave Opt. Technol. Lett. 60(5), 1164–1170 (2018)CrossRef
39.
Najiya, K., Archana, M.: UAV video processing for traffic surveillence with enhanced vehicle detection. In: 2018 Second International Conference on Inventive Communication and Computational Technologies (ICICCT), pp. 662–668. IEEE (2018)
40.
Nguyen, T.B., Ziou, D.: Contextual and non-contextual performance evaluation of edge detectors. Pattern Recogn. Lett. 21(9), 805–816 (2000)CrossRef
41.
Park, J.H., Choi, S.C., Ahn, I.Y., Kim, J.: Multiple UAVs-based surveillance and reconnaissance system utilizing IoT platform. In: 2019 International Conference on Electronics, Information, and Communication (ICEIC), pp. 1–3. IEEE (2019)
42.
Qazi, S., Alvi, A., Qureshi, A.M., Khawaja, B.A., Mustaqim, M.: An architecture for real time monitoring aerial adhoc network. In: 2015 13th International Conference on Frontiers of Information Technology (FIT), pp. 154–159. IEEE (2015)
43.
Qazi, S., Siddiqui, A.S., Wagan, A.I.: UAV based real time video surveillance over 4G LTE. In: 2015 International Conference on Open Source Systems & Technologies (ICOSST), pp. 141–145. IEEE (2015)
44.
Sarkar, S., Totaro, M.W., Elgazzar, K.: Intelligent drone-based surveillance: application to parking lot monitoring and detection. In: Unmanned Systems Technology XXI, vol. 11021, p. 1102104. International Society for Optics and Photonics (2019)
45.
Semsch, E., Jakob, M., Pavlicek, D., Pechoucek, M.: Autonomous UAV surveillance in complex urban environments. In: Proceedings of the 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology-Volume 02, pp. 82–85. IEEE Computer Society (2009)
46.
Seshadrinathan, K., Soundararajan, R., Bovik, A.C., Cormack, L.K.: Study of subjective and objective quality assessment of video. IEEE Trans. Image Process. 19(6), 1427–1441 (2010)MathSciNetCrossRef
47.
Sharma, V., Song, F., You, I., Chao, H.C.: Efficient management and fast handovers in software defined wireless networks using UAVs. IEEE Netw. 31(6), 78–85 (2017)CrossRef
48.
Sheikh, H.R., Bovik, A.C., De Veciana, G.: An information fidelity criterion for image quality assessment using natural scene statistics. IEEE Trans. Image Process. 14(12), 2117–2128 (2005)CrossRef
49.
Shin, S.Y., et al.: UAV based search and rescue with honeybee flight behavior in forest. In: Proceedings of the 5th International Conference on Mechatronics and Robotics Engineering, pp. 182–187. ACM (2019)
50.
Vijaykumar, M., Rao, S.: A cross-layer frame work for adaptive video streaming over wireless networks, September 2010
51.
Wang, Z., Bovik, A.C., Sheikh, H.R., Simoncelli, E.P., et al.: Image quality assessment: from error visibility to structural similarity. IEEE Trans. Image Process. 13(4), 600–612 (2004)CrossRef
52.
Yan, B., Bare, B., Ma, C., Li, K., Tan, W.: Deep objective quality assessment driven single image super-resolution. IEEE Trans. Multimed. 21, 2957–2971 (2019)CrossRef
53.
Yang, K., Gong, Y., Ma, M., Wu, H.R.: An efficient rate-distortion optimization method for low-delay configuration in H.265/HEVC based on temporal layer rate and distortion dependency. IEEE Trans. Circuits Syst. Video Technol. 29, 1230–1236 (2019)CrossRef
54.
Yang, T., Li, Z., Zhang, F., Xie, B., Li, J., Liu, L.: Panoramic UAV surveillance and recycling system based on structure-free camera array. IEEE Access 7, 25763–25778 (2019)CrossRef
Metadata
Title
QoE Analysis of Real-Time Video Streaming over 4G-LTE for UAV-Based Surveillance Applications
Authors
Muhammad Naveed
Sameer Qazi
Copyright Year
2020
Publisher
Springer Singapore
Book
Intelligent Technologies and Applications

Print ISBN: 978-981-15-5231-1

Electronic ISBN: 978-981-15-5232-8

Copyright Year: 2020

DOI
https://doi.org/10.1007/978-981-15-5232-8_38

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