This research focuses on optimizing data transmission in Internet of Things (IoT) sensor networks by implementing a smart approach to dynamic node selection. Leveraging predictive analytics, the proposed system facilitates efficient and accurate targeting of data transmission nodes. By dynamically selecting nodes based on predictive models, the network enhances resource utilization, reduces latency, and conserves energy, contributing to overall system efficiency. The study explores the integration of predictive analytics into IoT sensor networks, evaluates the performance of the dynamic node selection strategy, and highlights its effectiveness in achieving reliable and timely data transmission.
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