… resource utilization and prolong the lifespan of the network. In this paper, we present …
machine learning methods that were used to address common issues in wireless sensor networks (…

… reinforcement learning for wireless sensor networks,” Ad Hoc Netw., vol. 101, Apr. 2020, Art.
… based on deep reinforcement learning in wireless sensor networks,” IEEE Sensors J., vol. 19…

… This paper provides a convenient reference for wireless sensor network infrastructure and
… from machine learning algorithms by reducing the security costs of wireless sensor networks …

… nodes are deployed in hazardous environments where we leave the network run … various
challenges in Wireless Sensor Networks that are handled by machine learning techniques. We …

… , network lifetime maximization, communication protocols and state of the art infrastructure. In
this paper, the authors propose machine learning … the supervised learning algorithms have …

Wireless sensor network (WSN) is one of the most promising technologies for some real-time
applications because of its size, cost-effective and easily deployable nature. Due to some …

… the network are deployed. In this paper, we present numerous challenges that exist in wireless
sensor networks and … to overcome these challenges using machine learning techniques. …

… As sensor nodes have limited power, information transmission, packet latency and … network.
This review discusses various WSNs challenges with the system based on machine learning…

… machine learning algorithms for network-wide localization in large wireless sensor
networks… Section 3 presents a brief overview of suitability of machine learning algorithms for …

… We present a survey on machine learning techniques for energy efficient routing. … machine
learning techniques properties are more appropriate for optimize the wireless sensor network. …