Two-Phase Video Encoding for Disaster Management Video Transmission

Authors

  • Sushant M. Mangasuli Rajarambapu Institute of Technology, Rajaramnagar, Shivaji University, Kolhapur, India
  • Arundhati V. Nelli Rajarambapu Institute of Technology, Rajaramnagar, Shivaji University, Kolhapur, India
  • Ramesh Medar Rajarambapu Institute of Technology, Rajaramnagar, Shivaji University, Kolhapur, India
  • Ranjana Battur Department of Computer Science and Engineering, KLS Gogte Institute of Technology, Belagavi, India
  • Sujit N. Deshpande Department of Computer Engineering, Vishwakarma University, Pune, India
Volume: 15 | Issue: 5 | Pages: 27844-27851 | October 2025 | https://doi.org/10.48084/etasr.12825

Received: 19 June 2025 | Revised: 12 July 2025 | Accepted: 23 July 2025 | Online: 6 October 2025


Corresponding author: Sushant M. Mangasuli

Abstract

In disaster management scenarios, efficient video transmission poses significant challenges due to the limitations of existing encoding techniques. This study addresses these challenges by introducing a novel Two-Phase Video Encoding (TPVE) method tailored for disaster management video transmission. TPVE employs a two-phase design, reducing video bits through low-rank approximation in the initial phase, followed by additional compression using an optimized Huffman encoding in the second phase. The introduction of a parallel version of Huffman encoding with reduced coding length speeds up the encoding process, ensuring reduced Bit Error Rates (BERs) and higher coding efficiency. TPVE is particularly effective in Mobile Ad-Hoc Network (MANET) environments with Orthogonal Frequency-Division Multiplexing (OFDM) frames surrounded by noise and interference, and it outperforms Existing Video Encoding (EVE). Results reveal TPVE's superior BER and encoding efficiency, demonstrating a remarkable 65.06% BER improvement for a MANET Edge Device (MED) antenna size of 32 and an outstanding 88.08% improvement for a size of 64. These findings establish TPVE as a transformative solution, significantly enhancing reliability, reducing storage requirements, optimizing bandwidth utilization, and ensuring superior encoding efficiency in disaster management video transmission.

Keywords:

disaster management, video transmission, encoding, Huffman, MANETs

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References

S. Ghaffarian, F. R. Taghikhah, and H. R. Maier, "Explainable artificial intelligence in disaster risk management: Achievements and prospective futures," International Journal of Disaster Risk Reduction, vol. 98, Nov. 2023, Art. no. 104123.

R. Damaševičius, N. Bacanin, and S. Misra, "From Sensors to Safety: Internet of Emergency Services (IoES) for Emergency Response and Disaster Management," Journal of Sensor and Actuator Networks, vol. 12, no. 3, Jun. 2023, Art. no. 41.

V. B. Gadhavi, S. Degadwala, and D. Vyas, "Transfer Learning Approach For Recognizing Natural Disasters Video," in 2022 Second International Conference on Artificial Intelligence and Smart Energy, Coimbatore, India, 2022, pp. 793–798.

S. Afzal, V. Testoni, C. E. Rothenberg, P. Kolan, and I. Bouazizi, "A holistic survey of multipath wireless video streaming," Journal of Network and Computer Applications, vol. 212, Mar. 2023, Art. no. 103581.

A. Benis, M. Haghi, O. Tamburis, S. J. Darmoni, J. Grosjean, and T. M. Deserno, "Digital Emergency Management for a Complex One Health Landscape: the Need for Standardization, Integration, and Interoperability," Yearbook of Medical Informatics, vol. 32, no. 1, pp. 27–35, Dec. 2023.

A. Asif et al., "Automatic analysis of social media images to identify disaster type and infer appropriate emergency response," Journal of Big Data, vol. 8, no. 1, Jun. 2021, Art. no. 83.

K. Siva Kumar, S. Sasi Kumar, and N. Mohan Kumar, "Effcient video compression and improving quality of video in communication for computer endcoding applications," Computer Communications, vol. 153, pp. 152–158, Mar. 2020.

A. J. Qasim, R. Din, and F. Q. A. Alyousuf, "Review on techniques and file formats of image compression," Bulletin of Electrical Engineering and Informatics, vol. 9, no. 2, pp. 602–610, Apr. 2020.

S. Mangasuli and M. Kaluti, "Efficient Multimedia Content Transmission Model for Disaster Management using Delay Tolerant Mobile Adhoc Networks," International Journal of Advanced Computer Science and Applications, vol. 14, no. 1, pp. 479–484, Jan. 2023.

C. He, Z. Xie, and C. Tian, "An Adaptive QP Adjustment of Multimedia over Heterogeneous Wireless Networks," IOP Conference Series: Materials Science and Engineering, vol. 719, no. 1, Jan. 2020, Art. no. 012028.

V. Skosana and A. M. Abu-Mahfouz, "Video Encoding for Wireless Multimedia Sensor Networks: A Review," in 2020 2nd International Multidisciplinary Information Technology and Engineering Conference, Kimberley, South Africa, 2020, pp. 1–6.

G. Bijur, R. Mundugar, V. Mantoor, and K. A Kotegar, "Estimation of Adaptation Parameters for Dynamic Video Adaptation in Wireless Network Using Experimental Method," Computers, vol. 10, no. 4, Apr. 2021, Art. no. 39.

S. M and Y. D. C. R, "Multimedia Transmission Mechanism for Streaming Over Wireless Communication Channel," International Journal of Advanced Computer Science and Applications, vol. 12, no. 9, pp. 242–252, Sep. 2021.

S. Soni and J. S. Shah, "QoS frameworks for Multimedia Traffic in Mobile Adhoc Networks: A Comparative Review," Engineering, Technology & Applied Science Research, vol. 7, no. 3, pp. 1708–1712, Jun. 2017.

H. Xiao et al., "A Transcoding-Enabled 360° VR Video Caching and Delivery Framework for Edge-Enhanced Next-Generation Wireless Networks," IEEE Journal on Selected Areas in Communications, vol. 40, no. 5, pp. 1615–1631, May 2022.

R. Krishna, V. Nayak, and V. K. Tumuluru, "Energy-Efficient Proactive Content Caching For On-Demand Video Streaming Under Uncertainty," IEEE Transactions on Green Communications and Networking, vol. 6, no. 3, pp. 1739–1750, Sep. 2022.

M. Alsmirat, Y. Sharrab, M. Tarawneh, S. Al-shboul, and N. Sarhan, "Video coding deep learning-based modeling for long life video streaming over next network generation," Cluster Computing, vol. 26, no. 2, pp. 1159–1167, Apr. 2023.

A. Erfanian, H. Amirpour, F. Tashtarian, C. Timmerer, and H. Hellwagner, "CD-LwTE: Cost- and Delay-Aware Light-Weight Transcoding at the Edge," IEEE Transactions on Network and Service Management, vol. 20, no. 3, pp. 3104–3118, Sep. 2023.

K. Shanmugham, R. Rangan, S. Dhatchnamurthy, and S. Pundir, "An efficient self-attention-based conditional variational auto-encoder generative adversarial networks based multipath cross-layer design routing paradigm for MANET," Expert Systems with Applications, vol. 238, Mar. 2024, Art. no. 122097.

J. Logeshwaran, N. Shanmugasundaram, and J. Lloret, "Energy-efficient resource allocation model for device-to-device communication in 5G wireless personal area networks," International Journal of Communication Systems, vol. 36, no. 13, Sep. 2023, Art. no. e5524.

A. Fathalla, K. Li, A. Salah, and M. F. Mohamed, "An LSTM-based distributed scheme for data transmission reduction of IoT systems," Neurocomputing, vol. 485, pp. 166–180, May 2022.

F. Wiffen, W. H. Chin, and A. Doufexi, "Distributed Dimension Reduction for Distributed Massive MIMO C-RAN with Finite Fronthaul Capacity," in 2021 55th Asilomar Conference on Signals, Systems, and Computers, Pacific Grove, CA, USA, 2021, pp. 1228–1236.

R. Choupani, S. Wong, and M. Tolun, "Multiple description coding for SNR scalable video transmission over unreliable networks," Multimedia Tools and Applications, vol. 69, no. 3, pp. 843–858, Apr. 2014.

A. M. Hussein, A. K. Idrees, and R. Couturier, "Distributed energy-efficient data reduction approach based on prediction and compression to reduce data transmission in IoT networks," International Journal of Communication Systems, vol. 35, no. 15, Oct. 2022, Art. no. e5282.

R. R. Gajjala, S. Banchhor, A. M. Abdelmoniem, A. Dutta, M. Canini, and P. Kalnis, "Huffman Coding Based Encoding Techniques for Fast Distributed Deep Learning," in Proceedings of the 1st Workshop on Distributed Machine Learning, Barcelona, Spain, 2020, pp. 21–27.

N. Gadde, B. Jakkali, R. B. H. Siddamallaih, and G. Gowrishankar, "Quality of experience aware network selection model for service provisioning in heterogeneous network," International Journal of Electrical and Computer Engineering, vol. 12, no. 2, pp. 1839–1848, Apr. 2022.

G. Nagaraja, H. S. Rameshbabu, and Gowrishankar, "HERA: High-Efficiency Resource Allocation Scheme for Newly Joined Mobile Terminal in Heterogeneous Wireless Network," Indian Journal of Science and Technology, vol. 15, no. 25, pp. 1244–1252, Jul. 2022.

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How to Cite

[1]
S. M. Mangasuli, A. V. Nelli, R. Medar, R. Battur, and S. N. Deshpande, “Two-Phase Video Encoding for Disaster Management Video Transmission”, Eng. Technol. Appl. Sci. Res., vol. 15, no. 5, pp. 27844–27851, Oct. 2025.

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Copyright (c) 2025 Sushant M. Mangasuli, Arundhati V. Nelli, Ramesh Medar, Ranjana Battur, Sujit N. Deshpande

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