Anomaly detection in autonomous electric vehicles using AI techniques: A comprehensive survey

P Dixit, P Bhattacharya, S Tanwar, R Gupta - Expert Systems, 2022 - Wiley Online Library
The next wave in smart transportation is directed towards the design of renewable energy
sources that can fuel automobile sector to shift towards the autonomous electric vehicles …

The rise and fall of cryptocurrencies: defining the economic and social values of blockchain technologies, assessing the opportunities, and defining the financial and …

P Radanliev - Financial Innovation, 2024 - Springer
This study examines blockchain technologies and their pivotal role in the evolving
Metaverse, shedding light on topics such as how to invest in cryptocurrency, the mechanics …

Improving the communication and computation efficiency of split learning for iot applications

A Ayad, M Renner, A Schmeink - 2021 IEEE Global …, 2021 - ieeexplore.ieee.org
Distributed machine learning systems train neural network models by utilizing the devices
and resources in the network. One such system that was recently introduced is split learning …

A survey of using machine learning in IoT security and the challenges faced by researchers

KM Harahsheh, CH Chen - Informatica, 2023 - digitalcommons.odu.edu
Abstract The Internet of Things (IoT) has become more popular in the last 15 years as it has
significantly improved and gained control in multiple fields. We are nowadays surrounded by …

Accurate detection of IoT sensor behaviors in legitimate, faulty and compromised scenarios

K Sood, MR Nosouhi, N Kumar… - … on Dependable and …, 2021 - ieeexplore.ieee.org
In smart farming sector, Internet of Things (IoT) based smart sensing systems are vulnerable
to failure, malfunction, and malicious attacks. Also, sensors are deployed often in an alien …

[HTML][HTML] Complex methods detect anomalies in real time based on time series analysis

AS Alghawli - Alexandria Engineering Journal, 2022 - Elsevier
Real time anomaly detection is important to performance and efficiency in many areas. This
paper offers a complex method for detecting abnormal telecommunication traffic. The …

Bushfire risk detection using Internet of Things: An application scenario

MR Nosouhi, K Sood, N Kumar… - IEEE Internet of …, 2021 - ieeexplore.ieee.org
With rising temperatures and events contributing to climate change, the world is facing
extreme weather patterns. Recently, Australia was hit hard by bushfires, the most …

An efficient and private ecg classification system using split and semi-supervised learning

A Ayad, M Barhoush, M Frei, B Völker… - IEEE Journal of …, 2023 - ieeexplore.ieee.org
Electrocardiography (ECG) is a standard diagnostic tool for evaluating the overall heart's
electrical activity and is vital for detecting many cardiovascular diseases. Classifying ECG …

Botnet attacks detection in IoT environment using machine learning techniques

M AL-Akhras, A Alshunaybir, H Omar… - … Journal of Data and …, 2023 - growingscience.com
IoT devices with weak security designs are a serious threat to organizations. They are the
building blocks of Botnets, the platforms that launch organized attacks that are capable of …

[HTML][HTML] Predicting abnormalities in laboratory values of patients in the intensive care unit using different deep learning models: comparative study

A Ayad, A Hallawa, A Peine, L Martin… - JMIR medical …, 2022 - medinform.jmir.org
Background In recent years, the volume of medical knowledge and health data has
increased rapidly. For example, the increased availability of electronic health records …