Polling systems are critical components in various queue based communication environments such as wireless sensor networks, industrial automation, and embedded systems. This paper provides a comprehensive comparative analysis of three representative polling strategies: traditional cyclic polling, adaptive skip-empty polling, and a novel adaptive polling algorithm based on real-time arrival rate estimation. We show that the proposed algorithm is inherently responsive to fluctuations in traffic patterns and avoids unnecessary polling overhead. We implement a simulation framework to evaluate the performance of all strategies under various traffic conditions, including bursty and unbalanced loads. Additionally, we examine the trade-offs between responsiveness and computational overhead, demonstrating the suitability of our method for real-time and resource-constrained systems.