… (OSI) model layer data communication network protocols of an upper higher … protocols are
message query telemetry transport (MQTT) protocol [24], advanced message queuing protocol …

… In this section, we discuss various challenges in Wireless Sensor Networks that are handled
by machine learning techniques. We have classified WSN challenges into 3 types. These …

… Prediction based data sensing and fusion approach are used to minimize the data transmission
and maintain record of the sensor node's coverage. GM-KRLS uses the feature of Grey …

… mesh router is used as an IoT gateway where all the sensor data is saved in a … wireless
communication protocols, but this project uses a ZigBee protocol to communicate with the sensor …

… consumption in wireless sensor networks, this review focus on clustering methods based
on … In single-hop data transfer, CHs transfer the obtained data directly to the BS, whereas in …

… Abstract—In this letter, we present a comprehensive analysis of the use of machine and
deep learning solutions for IDS systems in Wireless Sensor Networks (WSNs). To accomplish …

… While in [20], the applications of machine learning in wireless sensor networks (WSNs) are
… Specifically, by deriving proper paths for data transmission, transmission delay and other …

… In this study, the authors delve into the world of wireless sensor networks (WSNs) and
explore the potential of machine learning-driven data fusion alongside virtual replicas. This …

… This poses additional requirements on the efficiency of data transfer to avoid the
transmission and storage of massive amounts of data that may never be utilized over network …

… Second, they mostly restrict their scope to a single wireless application such as sensor
networks [53], cognitive radio networks [52], machine-to-machine (M2M) communication [3], …