Video Compressor and Algorithm For GSM and Satellite Telemetry

DOI

10.2991/978-94-6463-738-0_74How to use a DOI?

Keywords

Video Compression; GSM Communication; Compression Algorithm; Satellite Telemetry; FFmpeg; Video Compression; Machine Learning in Video Processing; Remote Sensing & Surveillance; IoT-Based Video Transmission; 5G and Satellite Integration

Abstract

This work focuses on creating a powerful video compression algorithm tailored for satellite telemetry and GSM systems. The main goal is to optimize compression strategies for low-bandwidth systems without sacrificing video quality, which is crucial for resource-intensive networks like GSM and satellite links. Traditional compression methods often struggle with latency and data loss, making them unsuitable for real-time telemetry applications. To tackle these challenges, this research delves into real-time compression algorithms, adaptive encoding techniques, and error resilience strategies that can adjust to fluctuating network conditions. The proposed method enhances scalability, boosts data transmission efficiency, and improves video streaming reliability, even in challenging communication environments. By reducing bandwidth while preserving vital visual information, this approach supports effective telemetry applications in areas like space exploration, remote monitoring, and surveillance. Additionally, the research integrates error correction techniques to minimize packet loss and maintain data integrity during transmission. With these highly optimized compression algorithms in place, video-based telemetry is expected to become a more efficient solution for real-time data transmission over bandwidth-limited networks. The ongoing research aims to further improve video communication in GSM and satellite telemetry systems. The purpose of this research is to evaluate the ability to improve performance in the compression efficiency and reduce the latency. Future work will focus on incorporating increased adaptability, adding AI-based optimizations to the algorithms, and increasing the scope of application for telemetry. By addressing prominent challenges in this area, this research contributes to the development of robust, high performance video transmission solutions for bandwidth-limited communications systems such as GSM and satellite telemetry systems.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Preeti Tuli
AU  - Himanshu Jha
AU  - Prabhat Chaubey
AU  - Hemprakash Sahu
PY  - 2025
DA  - 2025/06/22
TI  - Video Compressor and Algorithm For GSM and Satellite Telemetry
BT  - Proceedings of the International Conference on Advances and Applications in Artificial Intelligence (ICAAAI 2025)
PB  - Atlantis Press
SP  - 945
EP  - 958
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6463-738-0_74
DO  - 10.2991/978-94-6463-738-0_74
ID  - Tuli2025
ER  -