Review on deep learning approaches for anomaly event detection in video surveillance
In the last few years, due to the continuous advancement of technology, human behavior
detection and recognition have become important scientific research in the field of computer …
detection and recognition have become important scientific research in the field of computer …
Machine learning-based anomaly detection in NFV: A comprehensive survey
Network function virtualization (NFV) is a rapidly growing technology that enables the
virtualization of traditional network hardware components, offering benefits such as cost …
virtualization of traditional network hardware components, offering benefits such as cost …
Technology-enabled financing of sustainable infrastructure: A case for blockchains and decentralized oracle networks
The capital required to maintain infrastructure in good repair falls short globally. This is
commonly referred to as the “infrastructure finance gap”. To address climate change …
commonly referred to as the “infrastructure finance gap”. To address climate change …
Unsupervised deep learning for IoT time series
Internet of Things (IoT) time-series analysis has found numerous applications in a wide
variety of areas, ranging from health informatics to network security. Nevertheless, the …
variety of areas, ranging from health informatics to network security. Nevertheless, the …
Hybrid Bayesian optimization hypertuned catboost approach for malicious access and anomaly detection in IoT nomalyframework
The successful applications and diversified popularity of the Internet of Things (IoT) present
various advantages and opportunities in broad characteristics of our lives. However …
various advantages and opportunities in broad characteristics of our lives. However …
Anomaly detection of water level using deep autoencoder
IT Nicholaus, JR Park, K Jung, JS Lee, DK Kang - Sensors, 2021 - mdpi.com
Anomaly detection is one of the crucial tasks in daily infrastructure operations as it can
prevent massive damage to devices or resources, which may then lead to catastrophic …
prevent massive damage to devices or resources, which may then lead to catastrophic …
Predictive maintenance for smart industrial systems: a roadmap
The advent of Industry 4.0 and propelled the application of Artificial Intelligence in different
industrial fields and contexts, such as predictive maintenance (PdM). Through its ability to …
industrial fields and contexts, such as predictive maintenance (PdM). Through its ability to …
A high-throughput architecture for anomaly detection in streaming data using machine learning algorithms
C Surianarayanan, S Kunasekaran… - International Journal of …, 2024 - Springer
Detection of anomaly in streaming data requires continuous analysis of the stream in real
time. This process turns out to be difficult due to varied volume and velocity of data streams …
time. This process turns out to be difficult due to varied volume and velocity of data streams …
[HTML][HTML] Extension of lora coverage and integration of an unsupervised anomaly detection algorithm in an iot water quality monitoring system
ADB Jáquez, MTA Herrera, AEM Celestino… - Water, 2023 - mdpi.com
High cost, long-range communication, and anomaly detection issues are associated with IoT
systems in water quality monitoring. Therefore, this work proposes a prototype for a water …
systems in water quality monitoring. Therefore, this work proposes a prototype for a water …
[HTML][HTML] AIDA—A holistic AI-driven networking and processing framework for industrial IoT applications
Industry 4.0 is characterized by digitalized production facilities, where a large volume of
sensors collect a vast amount of data that is used to increase the sustainability of the …
sensors collect a vast amount of data that is used to increase the sustainability of the …