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5,749 Results Found

  • Review
  • Open Access
9 Citations
8,957 Views
24 Pages

A Review of Anomaly Detection in Spacecraft Telemetry Data

  • Asma Fejjari,
  • Alexis Delavault,
  • Robert Camilleri and
  • Gianluca Valentino

19 May 2025

Telemetry data play a pivotal role in ensuring the success of spacecraft missions and safeguarding the integrity of spacecraft systems. Therefore, the timely detection and subsequent notification of any abnormal events related to the functionality of...

  • Article
  • Open Access
10 Citations
9,894 Views
15 Pages

19 November 2023

Anomalies are infrequent in nature, but detecting these anomalies could be crucial for the proper functioning of any system. The rarity of anomalies could be a challenge for their detection as detection models are required to depend on the relations...

  • Review
  • Open Access
46 Citations
15,798 Views
43 Pages

Review of Anomaly Detection Algorithms for Data Streams

  • Tianyuan Lu,
  • Lei Wang and
  • Xiaoyong Zhao

22 May 2023

With the rapid development of emerging technologies such as self-media, the Internet of Things, and cloud computing, massive data applications are crossing the threshold of the era of real-time analysis and value realization, which makes data streams...

  • Article
  • Open Access
6 Citations
5,567 Views
20 Pages

Context—Anomaly detection in a data center is a challenging task, having to consider different services on various resources. Current literature shows the application of artificial intelligence and machine learning techniques to either log file...

  • Article
  • Open Access
43 Citations
6,780 Views
16 Pages

2 October 2020

Recently, wireless sensor networks (WSNs) have been extensively deployed to monitor environments. Sensor nodes are susceptible to fault generation due to hardware and software failures in harsh environments. Anomaly detection for the time-series stre...

  • Article
  • Open Access
36 Citations
7,040 Views
17 Pages

Anomaly Detection on Data Streams for Smart Agriculture

  • Juliet Chebet Moso,
  • Stéphane Cormier,
  • Cyril de Runz,
  • Hacène Fouchal and
  • John Mwangi Wandeto

2 November 2021

Smart agriculture technologies are effective instruments for increasing farm sustainability and production. They generate many spatial, temporal, and time-series data streams that, when analysed, can reveal several issues on farm productivity and eff...

  • Article
  • Open Access
29 Citations
6,925 Views
18 Pages

20 November 2017

Anomaly detection has been widely used in a variety of research and application domains, such as network intrusion detection, insurance/credit card fraud detection, health-care informatics, industrial damage detection, image processing and novel topi...

  • Article
  • Open Access
248 Views
37 Pages

14 December 2025

Anomaly detection in safety-critical systems often operates under severe label constraints, where only a small subset of normal and anomalous samples can be reliably annotated, while large unlabeled data streams are contaminated and high-dimensional....

  • Article
  • Open Access
10 Citations
2,248 Views
11 Pages

Anomaly Detection of Metallurgical Energy Data Based on iForest-AE

  • Zhangming Xiong,
  • Daofei Zhu,
  • Dafang Liu,
  • Shujing He and
  • Luo Zhao

4 October 2022

With the proliferation of the Internet of Things, a large amount of data is generated constantly by industrial systems, corresponding in many cases to critical tasks. It is particularly important to detect abnormal data to ensure the accuracy of data...

  • Article
  • Open Access
2 Citations
1,840 Views
15 Pages

Anomaly Detection Using Puzzle-Based Data Augmentation to Overcome Data Imbalances and Deficiencies

  • Eunkyeong Kim,
  • Seunghwan Jung,
  • Minseok Kim,
  • Jinyong Kim,
  • Baekcheon Kim,
  • Jonggeun Kim and
  • Sungshin Kim

20 November 2023

Machine tools are used in a wide range of applications, and they can manufacture workpieces flexibly. Furthermore, they require maintenance; the overall costs include maintenance costs, which constitute a significant portion, and the costs involved i...

  • Review
  • Open Access
55 Citations
11,168 Views
18 Pages

Anomaly Detection Framework for Wearables Data: A Perspective Review on Data Concepts, Data Analysis Algorithms and Prospects

  • Jithin S. Sunny,
  • C. Pawan K. Patro,
  • Khushi Karnani,
  • Sandeep C. Pingle,
  • Feng Lin,
  • Misa Anekoji,
  • Lawrence D. Jones,
  • Santosh Kesari and
  • Shashaanka Ashili

19 January 2022

Wearable devices use sensors to evaluate physiological parameters, such as the heart rate, pulse rate, number of steps taken, body fat and diet. The continuous monitoring of physiological parameters offers a potential solution to assess personal heal...

  • Article
  • Open Access
33 Citations
8,481 Views
16 Pages

Data-Driven Thermal Anomaly Detection in Large Battery Packs

  • Kiran Bhaskar,
  • Ajith Kumar,
  • James Bunce,
  • Jacob Pressman,
  • Neil Burkell and
  • Christopher D. Rahn

18 January 2023

The early detection and tracing of anomalous operations in battery packs are critical to improving performance and ensuring safety. This paper presents a data-driven approach for online anomaly detection in battery packs that uses real-time voltage a...

  • Article
  • Open Access
1,421 Views
20 Pages

Genomic Anomaly Detection with Functional Data Analysis

  • Ria Kanjilal,
  • Andre Luiz Campelo dos Santos,
  • Sandipan Paul Arnab,
  • Michael DeGiorgio and
  • Raquel Assis

15 June 2025

Background: Genetic variation provides a foundation for understanding evolution. With the rise of artificial intelligence, machine learning has emerged as a powerful tool for identifying genomic footprints of evolutionary processes through simulation...

  • Article
  • Open Access
10 Citations
5,552 Views
18 Pages

28 September 2016

The spatial–temporal correlation is an important feature of sensor data in wireless sensor networks (WSNs). Most of the existing works based on the spatial–temporal correlation can be divided into two parts: redundancy reduction and anomaly detection...

  • Article
  • Open Access
6 Citations
2,953 Views
14 Pages

Financial Data Anomaly Discovery Using Behavioral Change Indicators

  • Audrius Lopata,
  • Saulius Gudas,
  • Rimantas Butleris,
  • Vytautas Rudžionis,
  • Liutauras Žioba,
  • Ilona Veitaitė,
  • Darius Dilijonas,
  • Evaldas Grišius and
  • Maarten Zwitserloot

In this article we present an approach to financial data analysis and anomaly discovery. In our view, the assessment of performance management requires the monitoring of financial performance indicators (KPIs) and the characteristics of changes in KP...

  • Article
  • Open Access
40 Citations
5,189 Views
19 Pages

There is a growing interest in safety warning of underground mining due to the huge threat being faced by those working in underground mining. Data acquisition of sensors based on Internet of Things (IoT) is currently the main method, but the data an...

  • Article
  • Open Access
2 Citations
4,193 Views
25 Pages

30 September 2023

Given the complexity of spacecraft system structures and functions, existing data-driven methods for anomaly detection face issues of insufficient interpretability and excessive dependence on historical data. To address these challenging problems, th...

  • Article
  • Open Access
7 Citations
2,202 Views
11 Pages

28 June 2023

Structural health inspection systems are widely used to manage and maintain infrastructure that involves massive sensor devices. However, these sensors receive the natural environment or external factors in the long-term exposure to the outdoor envir...

  • Article
  • Open Access
2,445 Views
15 Pages

Data Quality Tools to Enhance a Network Anomaly Detection Benchmark

  • José Camacho and
  • Rafael A. Rodríguez-Gómez

25 February 2025

Network traffic datasets are essential for the construction of traffic models, often using machine learning (ML) techniques. Among other applications, these models can be employed to solve complex optimization problems or to identify anomalous behavi...

  • Article
  • Open Access
147 Citations
16,621 Views
24 Pages

Anomaly Detection Based on Sensor Data in Petroleum Industry Applications

  • Luis Martí,
  • Nayat Sanchez-Pi,
  • José Manuel Molina and
  • Ana Cristina Bicharra Garcia

27 January 2015

Anomaly detection is the problem of finding patterns in data that do not conform to an a priori expected behavior. This is related to the problem in which some samples are distant, in terms of a given metric, from the rest of the dataset, where these...

  • Article
  • Open Access
16 Citations
4,252 Views
20 Pages

Anomaly Detection Based on Time Series Data of Hydraulic Accumulator

  • Min-Ho Park,
  • Sabyasachi Chakraborty,
  • Quang Dao Vuong,
  • Dong-Hyeon Noh,
  • Ji-Woong Lee,
  • Jae-Ung Lee,
  • Jae-Hyuk Choi and
  • Won-Ju Lee

2 December 2022

Although hydraulic accumulators play a vital role in the hydraulic system, they face the challenges of being broken by continuous abnormal pulsating pressure which occurs due to the malfunction of hydraulic systems. Hence, this study develops anomaly...

  • Article
  • Open Access
15 Citations
7,395 Views
22 Pages

1 December 2023

Big data has emerged as a fundamental component in various domains, enabling organizations to extract valuable insights and make informed decisions. However, ensuring data quality is crucial for effectively using big data. Thus, big data quality has...

  • Article
  • Open Access
36 Citations
9,269 Views
18 Pages

TGAN-AD: Transformer-Based GAN for Anomaly Detection of Time Series Data

  • Liyan Xu,
  • Kang Xu,
  • Yinchuan Qin,
  • Yixuan Li,
  • Xingting Huang,
  • Zhicheng Lin,
  • Ning Ye and
  • Xuechun Ji

12 August 2022

Anomaly detection on time series data has been successfully used in power grid operation and maintenance, flow detection, fault diagnosis, and other applications. However, anomalies in time series often lack strict definitions and labels, and existin...

  • Article
  • Open Access
19 Citations
5,941 Views
20 Pages

Anomaly Detection and Identification in Satellite Telemetry Data Based on Pseudo-Period

  • Haixu Jiang,
  • Ke Zhang,
  • Jingyu Wang,
  • Xianyu Wang and
  • Pengfei Huang

20 December 2019

To effectively detect and identify the anomaly data in massive satellite telemetry data sets, the novel detection and identification method based on the pseudo-period was proposed in this paper. First, the raw data were compressed by extracting the s...

  • Article
  • Open Access
25 Citations
3,194 Views
20 Pages

Machine Learning-Based Ensemble Classifiers for Anomaly Handling in Smart Home Energy Consumption Data

  • Purna Prakash Kasaraneni,
  • Yellapragada Venkata Pavan Kumar,
  • Ganesh Lakshmana Kumar Moganti and
  • Ramani Kannan

30 November 2022

Addressing data anomalies (e.g., garbage data, outliers, redundant data, and missing data) plays a vital role in performing accurate analytics (billing, forecasting, load profiling, etc.) on smart homes’ energy consumption data. From the litera...

  • Article
  • Open Access
7 Citations
2,865 Views
22 Pages

15 December 2023

Cyber threats to industrial control systems (ICSs) have increased as information and communications technology (ICT) has been incorporated. In response to these cyber threats, we are implementing a range of security equipment and specialized training...

  • Article
  • Open Access
13 Citations
7,344 Views
15 Pages

Machine Tools Anomaly Detection Through Nearly Real-Time Data Analysis

  • Gorka Herranz,
  • Alfonso Antolínez,
  • Javier Escartín,
  • Amaia Arregi and
  • Jon Kepa Gerrikagoitia

This work presents a new methodology for machine tools anomaly detection via operational data processing. The previous methodology has been field tested on a milling-boring machine in a real production environment. This paper also describes the data...

  • Article
  • Open Access
13 Citations
6,810 Views
14 Pages

15 February 2020

The development and integration of information technology and industrial control networks have expanded the magnitude of new data; detecting anomalies or discovering other valid information from them is of vital importance to the stable operation of...

  • Article
  • Open Access
20 Citations
8,853 Views
21 Pages

Recently, OT (operational technology) networks of industrial control systems have been combined with IT networks. Therefore, OT networks have inherited the vulnerabilities and attack paths existing in IT networks. Consequently, attacks on industrial...

  • Article
  • Open Access
2 Citations
2,080 Views
22 Pages

Industrial anomaly detection, which relies on the analysis of industrial internet of things (IIoT) sensor data, is a critical element for guaranteeing the quality and safety of industrial manufacturing. Current solutions normally apply edge–clo...

  • Article
  • Open Access
26 Citations
8,662 Views
18 Pages

24 August 2022

Anomaly detection based on telemetry data is a major issue in satellite health monitoring which can identify unusual or unexpected events, helping to avoid serious accidents and ensure the safety and reliability of operations. In recent years, sparse...

  • Article
  • Open Access
15 Citations
4,482 Views
18 Pages

Hybrid Machine Learning–Statistical Method for Anomaly Detection in Flight Data

  • Sameer Kumar Jasra,
  • Gianluca Valentino,
  • Alan Muscat and
  • Robert Camilleri

12 October 2022

This paper investigates the use of an unsupervised hybrid statistical–local outlier factor algorithm to detect anomalies in time-series flight data. Flight data analysis is an activity carried out by airlines primarily as a means of improving t...

  • Article
  • Open Access
8 Citations
4,363 Views
19 Pages

12 November 2019

The data validity of safe driving in the Internet of Vehicles (IoV) is the basis of improving the safety of vehicles. Different from a traditional information systems, the data anomaly analysis of vehicle safety driving faces the diversity of data an...

  • Article
  • Open Access
6 Citations
3,960 Views
14 Pages

Data-Driven Anomaly Detection Framework for Complex Degradation Monitoring of Aero-Engine

  • Zichen Yan,
  • Jianzhong Sun,
  • Yang Yi,
  • Caiqiong Yang and
  • Jingbo Sun

Data analysis is an important part of aero engine health management. In order to complete accurate condition monitoring, it is necessary to establish more effective analysis tools. Therefore, an integrated algorithm library dedicated for engine anoma...

  • Article
  • Open Access
67 Citations
9,453 Views
20 Pages

Anomaly Detection with Machine Learning Algorithms and Big Data in Electricity Consumption

  • Simona-Vasilica Oprea,
  • Adela Bâra,
  • Florina Camelia Puican and
  • Ioan Cosmin Radu

2 October 2021

When analyzing smart metering data, both reading errors and frauds can be identified. The purpose of this analysis is to alert the utility companies to suspicious consumption behavior that could be further investigated with on-site inspections or oth...

  • Article
  • Open Access
3 Citations
2,752 Views
20 Pages

AIoT-Based Visual Anomaly Detection in Photovoltaic Sequence Data via Sequence Learning

  • Qian Wei,
  • Hongjun Sun,
  • Jingjing Fan,
  • Guojun Li and
  • Zhiguang Zhou

29 October 2024

Anomaly detection is a common analytical task aimed at identifying rare cases that differ from the majority of typical cases in a dataset. In the management of photovoltaic (PV) power generation systems, it is essential for electric power companies t...

  • Article
  • Open Access
11 Citations
5,589 Views
25 Pages

Anomaly Detection Paradigm for Multivariate Time Series Data Mining for Healthcare

  • Abdul Razaque,
  • Marzhan Abenova,
  • Munif Alotaibi,
  • Bandar Alotaibi,
  • Hamoud Alshammari,
  • Salim Hariri and
  • Aziz Alotaibi

5 September 2022

Time series data are significant, and are derived from temporal data, which involve real numbers representing values collected regularly over time. Time series have a great impact on many types of data. However, time series have anomalies. We introdu...

  • Article
  • Open Access
2 Citations
2,493 Views
19 Pages

20 February 2025

Flight Operations Quality Assurance (FOQA) is an internationally recognized solution to ensure the safety of civil aircraft flights based on Quick Access Recorder (QAR) data. The traditional approach to anomaly detection in civil aviation is to detec...

  • Article
  • Open Access
8 Citations
2,901 Views
17 Pages

29 December 2023

Industrial control systems (ICS) are critical networks directly linked to the value of core national and societal assets, yet they are increasingly becoming primary targets for numerous cyberattacks today. The ICS network, a fusion of operational tec...

  • Article
  • Open Access
25 Citations
6,596 Views
21 Pages

17 October 2023

Structural health monitoring (SHM) has been extensively utilized in civil infrastructures for several decades. The status of civil constructions is monitored in real time using a wide variety of sensors; however, determining the true state of a struc...

  • Article
  • Open Access
16 Citations
4,513 Views
17 Pages

Anomaly Detection in Endemic Disease Surveillance Data Using Machine Learning Techniques

  • Peter U. Eze,
  • Nicholas Geard,
  • Ivo Mueller and
  • Iadine Chades

Disease surveillance is used to monitor ongoing control activities, detect early outbreaks, and inform intervention priorities and policies. However, data from disease surveillance that could be used to support real-time decisionmaking remain largely...

  • Article
  • Open Access
36 Citations
5,685 Views
25 Pages

28 July 2020

Multivariate time-series data with a contextual spatial attribute have extensive use for finding anomalous patterns in a wide variety of application domains such as earth science, hurricane tracking, fraud, and disease outbreak detection. In most set...

  • Article
  • Open Access
3 Citations
3,391 Views
25 Pages

This study deals with a method for anomaly detection in seawater temperature data using machine learning methods with oversampling techniques. Data were acquired from 2017 to 2023 using a Conductivity–Temperature–Depth (CTD) system in the...

  • Article
  • Open Access
10 Citations
9,417 Views
14 Pages

5 July 2018

The effect of the application of machine learning on data streams is influenced by concept drift, drift deviation, and noise interference. This paper proposes a data stream anomaly detection algorithm combined with control chart and sliding window me...

  • Article
  • Open Access
1 Citations
1,011 Views
27 Pages

Anomaly-based attack detection methods depend on some form of machine learning to detect data falsification attacks in smart living cyber–physical systems. However, there is a lack of studies that consider the presence of attacks during the tra...

  • Article
  • Open Access
1,850 Views
19 Pages

Multivariate time series data (MTSD) anomaly detection due to complex spatio-temporal dependencies among sensors and pervasive environmental noise. The existing methods struggle to balance anomaly detection accuracy with robustness against data conta...

  • Review
  • Open Access
36 Citations
11,803 Views
37 Pages

29 August 2021

Blockchain and Data Mining are not simply buzzwords, but rather concepts that are playing an important role in the modern Information Technology (IT) revolution. Blockchain has recently been popularized by the rise of cryptocurrencies, while data min...

  • Article
  • Open Access
2 Citations
2,885 Views
15 Pages

3 October 2024

Detecting anomalies in engine and machinery data during ship operations is crucial for maintaining the safety and efficiency of the vessel. We conducted experiments using device data from the maritime industry, consisting of time series records from...

  • Feature Paper
  • Article
  • Open Access
1 Citations
2,072 Views
19 Pages

26 March 2025

Anomaly detection in structured data presents significant challenges, particularly in scenarios with extreme class imbalance. The Siamese Neural Network (SNN) is traditionally recognized for its ability to measure pairwise similarities, rather than b...

  • Article
  • Open Access
22 Citations
6,326 Views
24 Pages

Anomaly Detection for Data from Unmanned Systems via Improved Graph Neural Networks with Attention Mechanism

  • Guoying Wang,
  • Jiafeng Ai,
  • Lufeng Mo,
  • Xiaomei Yi,
  • Peng Wu,
  • Xiaoping Wu and
  • Linjun Kong

19 May 2023

Anomaly detection has an important impact on the development of unmanned aerial vehicles, and effective anomaly detection is fundamental to their utilization. Traditional anomaly detection discriminates anomalies for single-dimensional factors of sen...

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