Adaptive Energy-Aware Machine Learning Framework for Dynamic IoT Environments - Kamalraj A; Jubitha I; Divya H (The Bioscan, 2026)
The rapid expansion of Internet of Things (IoT) ecosystems has intensified the deployment of machine learning (ML) models at the network edge to enable real-time analytics and intelligent decision-making. However, IoT devices are inherently resource-constrained, operating under limited battery capacity, restricted memory, and dynamic workload conditions.