Machine learning for advanced wireless sensor networks: A review
Wireless sensor networks (WSNs) are typically used with dynamic conditions of task-related
environments for sensing (monitoring) and gathering of raw sensor data for subsequent …
environments for sensing (monitoring) and gathering of raw sensor data for subsequent …
A short‐term load forecasting method based on GRU‐CNN hybrid neural network model
L Wu, C Kong, X Hao, W Chen - Mathematical problems in …, 2020 - Wiley Online Library
Short‐term load forecasting (STLF) plays a very important role in improving the economy
and stability of the power system operation. With the smart meters and smart sensors widely …
and stability of the power system operation. With the smart meters and smart sensors widely …
A review of current prediction techniques for extending the lifetime of wireless sensor networks
WB Nedham, AKM Al-Qurabat - International Journal of …, 2023 - inderscienceonline.com
The possibility for broad usage of Wireless Sensor Networks (WSNs) in many various
sectors, such as environmental monitoring, security, home automation and many others, has …
sectors, such as environmental monitoring, security, home automation and many others, has …
A water quality prediction method based on the multi-time scale bidirectional long short-term memory network
Q Zou, Q Xiong, Q Li, H Yi, Y Yu, C Wu - Environmental Science and …, 2020 - Springer
As an important factor affecting the mangrove wetland ecosystem, water quality has become
the focus of attention in recent years. Therefore, many studies have focused on the …
the focus of attention in recent years. Therefore, many studies have focused on the …
An intelligent big data collection technology based on micro mobile data centers for crowdsensing vehicular sensor network
The fast development of Internet of Things (IoT) has greatly driven the development of
mobile crowdsensing vehicular sensor network (CVSN). A lot of fascinating big data–based …
mobile crowdsensing vehicular sensor network (CVSN). A lot of fascinating big data–based …
MSCR: Multidimensional secure clustered routing scheme in hierarchical wireless sensor networks
For hierarchical wireless sensor network (WSN), the clustered routing protocol can
effectively deal with large-scale application requirements, thereby, how to efficiently elect the …
effectively deal with large-scale application requirements, thereby, how to efficiently elect the …
Image compression techniques in wireless sensor networks: A survey and comparison
BA Lungisani, CK Lebekwe, AM Zungeru… - IEEE Access, 2022 - ieeexplore.ieee.org
There is continuous intensive research on image compression techniques in wireless
sensor networks (WSNs) in the literature. Some of the image compression techniques in …
sensor networks (WSNs) in the literature. Some of the image compression techniques in …
Data-driven RAN slicing mechanisms for 5G and beyond
One of the main challenges when it comes to deploying Network Slices is slicing the Radio
Access Network (RAN). Indeed, managing RAN resources and sharing them among network …
Access Network (RAN). Indeed, managing RAN resources and sharing them among network …
Modeling for the prediction of soil moisture in litchi orchard with deep long short-term memory
Soil moisture is an important factor determining yield. With the increasing demand for
agricultural irrigation water resources, evaluating soil moisture in advance to create a …
agricultural irrigation water resources, evaluating soil moisture in advance to create a …
Data prediction-based energy-efficient architecture for industrial iot
This article presents an energy-efficient industrial Internet of Things (IIoT) architecture that
minimizes the data transmission process based on sensor data prediction. While current IIoT …
minimizes the data transmission process based on sensor data prediction. While current IIoT …