An energy efficient IoT data compression approach for edge machine learning
Many IoT systems generate a huge and varied amount of data that need to be processed
and responded to in a very short time. One of the major challenges is the high energy …
and responded to in a very short time. One of the major challenges is the high energy …
A survey of data collaborative sensing methods for smart agriculture
Data is becoming increasingly pivotal and foundational in the development of smart
agriculture, underscoring the importance of efficient methods for obtaining high-value data …
agriculture, underscoring the importance of efficient methods for obtaining high-value data …
A sensor-based data analytics for patient monitoring in connected healthcare applications
Nowadays, keeping a strong and good health is one of the main concern of the general
public or governments. The Internet of Things (IoT) has been emerged as an efficient …
public or governments. The Internet of Things (IoT) has been emerged as an efficient …
A computational model for adaptive recording of vital signs through context histories
JAS Aranda, RS Bavaresco, JV de Carvalho… - Journal of Ambient …, 2023 - Springer
Wearable devices emerged from the advancement of communication technology and the
miniaturization of electronic components. These devices periodically monitor the user's vital …
miniaturization of electronic components. These devices periodically monitor the user's vital …
Learning to schedule joint radar-communication with deep multi-agent reinforcement learning
Radar detection and communication are two essential sub-tasks for the operation of next-
generation autonomous vehicles (AVs). The forthcoming proliferation of faster 5G networks …
generation autonomous vehicles (AVs). The forthcoming proliferation of faster 5G networks …
Energy‐saving multisensor data sampling and fusion with decision‐making for monitoring health risk using WBSNs
The necessity of developing sufficient systems to monitor health conditions has increased
due to the aging of the population and the prevalence of chronic diseases, creating a …
due to the aging of the population and the prevalence of chronic diseases, creating a …
A hadoop-based platform for patient classification and disease diagnosis in healthcare applications
Nowadays, the increasing number of patients accompanied with the emergence of new
symptoms and diseases makes heath monitoring and assessment a complicated task for …
symptoms and diseases makes heath monitoring and assessment a complicated task for …
Multibiosensor data sampling and transmission reduction with decision-making for remote patient monitoring in IoMT networks
The rise in chronic diseases and the aging of the population led to an increase in the
demand for remote healthcare systems that employ biosensors to monitor people's health …
demand for remote healthcare systems that employ biosensors to monitor people's health …
Intelligent resource allocation in joint radar-communication with graph neural networks
Autonomous vehicles produce high data rates of sensory information from sensing systems.
To achieve the advantages of sensor fusion among different vehicles in a cooperative …
To achieve the advantages of sensor fusion among different vehicles in a cooperative …
A review of research on industrial time series classification for machinery based on deep learning
This research investigates detecting machine failures in a manufacturing process using
multivariate time series data. From a methodological standpoint, fault detection and …
multivariate time series data. From a methodological standpoint, fault detection and …