Citation

Sungheetha, Akey and R., Rajesh Sharma and A, Divyashree (2026) Advanced Hybrid Stream Analytics Framework for Sustainable Asteroid Monitoring Systems. Procedia Computer Science, 282. pp. 1189-1199. ISSN 18770509

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Abstract

Space surveillance systems face unprecedented challenges in processing massive volumes of real-time astronomical data streams from distributed sensor networks monitoring near-Earth objects and potentially hazardous asteroids. Traditional batch processing methodologies prove inadequate for time-critical threat assessment scenarios requiring sub-second latency responses. This research addresses the critical gap in sustainable computing architectures for continuous asteroid tracking by proposing an Advanced Hybrid Stream Analytics Framework that integrates edge computing paradigms with adaptive data fusion mechanisms. The framework employs a novel dual-stage processing architecture combining lightweight feature extraction at sensor nodes with centralized deep learning-based trajectory prediction, achieving 94.7 percent accuracy in orbit determination while reducing energy consumption by 67.3 percent compared to conventional cloud-centric approaches. The methodology introduces a dynamic resource allocation algorithm optimizing computational load distribution across heterogeneous edge devices based on real-time threat priority scoring. Experimental validation using synthesized astronomical datasets demonstrates average processing latency of 187 milliseconds for high-priority object classification with sustained throughput of 15,847 events per second. The proposed system maintains operational efficiency under network disruptions through intelligent caching strategies and provides scalable infrastructure supporting technology transfer initiatives for commercial space monitoring applications and planetary defense programs

Item Type:	Article
Uncontrolled Keywords:	Edge computing, Sustainable space systems
Subjects:	Q Science > QA Mathematics > QA71-90 Instruments and machines > QA75.5-76.95 Electronic computers. Computer science
Divisions:	Faculty of Information Science and Technology (FIST)
Depositing User:	Ms Rosnani Abd Wahab
Date Deposited:	02 Sep 2026 07:30
Last Modified:	02 Sep 2026 07:30
URII:	http://shdl.mmu.edu.my/id/eprint/16540

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