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Title	A Comprehensive Survey On Energy-Efficient Wireless Sensor Network Protocols For Real-Time Applications
ID_Doc	989
Authors	Saradha K.R.; Sakthy S.S.
Year	2025
Published	2025 International Conference on Computing and Communication Technologies, ICCCT 2025
DOI	http://dx.doi.org/10.1109/ICCCT63501.2025.11018906
Abstract	Wireless Sensor Networks (WSNs) play a critical role in real-time applications, such as healthcare monitoring, industrial automation, and smart cities. However, energy efficiency remains a significant challenge due to the limited power resources of sensor nodes. This paper presents an AI-based energy-efficient routing protocol leveraging Machine Learning (ML) techniques to optimize cluster head selection, routing paths, and data transmission. The proposed method integrates K-Means clustering, reinforcement learning-based routing, and AI-driven anomaly detection to enhance network lifetime, minimize energy consumption, and improve security. © 2025 IEEE.
Author Keywords	Adaptive Routing; AI- Based Routing; Anomaly Detection; Cluster Head Selection; Data Transmission Optimization; Deep Learning; Energy-Efficient Protocols; Internet of Things (IoT); Machine Learning (ML); Network Lifetime Enhancement; Real-Time Applications; Reinforcement Learning; Security in WSNs; Smart Networks; Wireless Sensor Networks (WSNs)

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