Akey SungheethaRajesh Sharma RSheila MahapatraR TamilarasiA. Ezil Sam Leni2025-08-092025-08-092025-04-1397983503554689798350355475http://doi.org/10.1109/ITIKD63574.2025.11005025https://gnanaganga.alliance.edu.in/handle/123456789/8515This paper presents HESTStream, a novel hybrid edge-stream processing framework that integrates environmental monitoring with real-time data analytics for sustainable smart cities. The framework addresses key challenges in stream pro-cessing by implementing an adaptive hash-based hybrid caching model (HCache) combined with distributed sensor networks. Our approach leverages triboelectric sensors and edge computing to enable real-time environmental monitoring while optimizing power consumption and data processing efficiency. Experimental results across 14 international deployment sites demonstrate that HESTStream achieves 47% improved processing latency, 38% reduced power consumption, and 42% enhanced cache hit ratio compared to existing methods. The framework provides a scalable solution for smart city applications requiring real-time environmental data processing while maintaining sustainability goals. © 2025 IEEE.enEdge ComputingEnvironmental MonitoringReal-Time AnalyticsSmart CitiesStream ProcessingSustainable Computingproceedings-article