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Anomaly detection‐based intelligent computing in internet of things and network applications
2021
Internet Technology Letters
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in the scenario of smart city, 8 and abnormal events in smart agriculture. 9 Anomaly detection has been researched for several decades and many anomaly detection methods have been proposed so far. ...
Artificial intelligence (AI)-driven IoT and network applications has been widely recognized as a promising solution for smart scenarios. 1,2 For IoT and emerging smart applications (eg, smart city, smart ...
In order to solve this issues, it is worth to introduce anomaly detection methods into IoT applications and services. ...
doi:10.1002/itl2.293
fatcat:wa7rfulktjdxlacscv545w74ya
Detecting Sensor Faults, Anomalies and Outliers in the Internet of Things: A Survey on the Challenges and Solutions
2020
Electronics
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A comprehensive guideline to select an adequate outlier detection model for the sensors in the IoT context for various applications is discussed. ...
In this paper, we present a comprehensive review of the detecting sensor faults, anomalies, outliers in the Internet of Things and the challenges. ...
• The sensor faults and outliers can be detected by using temporal correlation. ...
doi:10.3390/electronics9030511
fatcat:zzjuiacd7zg3bmezds45vey7em
A Real-time Complex Event Discovery Platform for Cyber-Physical-Social Systems
2014
Proceedings of International Conference on Multimedia Retrieval - ICMR '14
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EvIM includes two components (1) EventWarehouse: is built for harvesting, storing, and analysing data coming from large scale heterogeneous sensors, and (2) EventShop: plays as a real-time complex spatio-temporal ...
Since data is not information, methods for discovering useful and correlative information from data and utilising them for the better life, in real-time mode, are the utmost requirements. ...
: (1) semantic decoupling, (2) spatial-correlative sensors clustering, (3) anomaly detecting, and (4) patterns discovering. ...
doi:10.1145/2578726.2578755
dblp:conf/mir/DaoPJKJZ14
fatcat:o6mg423d6zashi53ijcz2x6jza
Smart Water Management for Cities
2019
Zenodo
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Bottom layer of the platform provides data gather- ing and provision infrastructure based on IoT standards. ...
Data-driven approach to groundwater levels analysis, which is important for de- cision support in flood and groundwater management, has shown promising results and could replace or complement traditional ...
The authors would like to thank Filip Koprivec and Matej Čerin for their valuable contribution to the development of data-driven methods presented in this paper. ...
doi:10.5281/zenodo.3233008
fatcat:ekdhr5wfsfckhaxas6ibrre33i
Smart Water Management for Cities
2019
Zenodo
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Bottom layer of the platform provides data gathering and provision infrastructure based on IoT standards. ...
Data-driven approach to groundwater levels analysis, which is important for decision support in flood and groundwater management, has shown promising results and could replace or complement traditional ...
The authors would like to thank Filip Koprivec and Matej Čerin for their valuable contribution to the development of data-driven methods presented in this paper. ...
doi:10.5281/zenodo.2646310
fatcat:xmqbmtbjhvajhmf2glupyevkp4
Anomaly Detection Approach for Urban Sensing Based on Credibility and Time-Series Analysis Optimization Model
2019
IEEE Access
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In this paper, we propose an anomaly detection method for urban sensing based on sequential data and credibility. ...
First, based on Bayesian methods, a reputation model is established for the selection of credible sample points. ...
ACKNOWLEDGMENT The authors would like to thank Miss Jun Ma for useful discussions and consultations. ...
doi:10.1109/access.2019.2909967
fatcat:bvtpn7hx6zcufo4jp4jiqrlmlq
Importance of Small Probability Events in Big Data: Information Measures, Applications, and Challenges
2019
IEEE Access
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In addition, based on rare events detection, some open challenges related to information measures, such as smart cities, autonomous driving, and anomaly detection in the IoT, are introduced which can be ...
., anomaly detection and security systems) of smart cities, rare events dominate the importance of the total information on big data collected by the Internet of Things (IoT). ...
In addition, spatio-temporal data mining is also considered in urban anomaly detection. ...
doi:10.1109/access.2019.2926518
fatcat:xjsacklrhrglfplqmttrfk6eda
A Spatiotemporal and Multivariate Attribute Correlation Extraction Scheme for Detecting Abnormal Nodes in WSNs
2021
IEEE Access
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Many heterogeneous sensors exhibit strong spatio-temporal correlations that can be used to enhance the abnormal node detection problem in a wireless sensor network (WSN). ...
Based on the ST correlations, the cross-correlation is extracted in both space and time by conducting shape-based logical subclustering and two-phase analysis methods. ...
Most anomaly detection methods proposed for the IoT, particularly for WSNs, focus only on specific types of network attacks. ...
doi:10.1109/access.2021.3115819
fatcat:jtbncubmafg6poibzc5kzs75ai
Computer Vision, IoT and Data Fusion for Crop Disease Detection Using Machine Learning: A Survey and Ongoing Research
2021
Remote Sensing
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A growing body of literature recognizes the importance of using data from different types of sensors and machine learning approaches to build models for detection, prediction, analysis, assessment, etc ...
It lists traditional and deep learning methods associated with the main data acquisition modalities, namely IoT, ground imaging, unmanned aerial vehicle imaging and satellite imaging. ...
Advances in sensor technologies and data processing have opened new perspectives for the detection and diagnosis of crop anomalies. ...
doi:10.3390/rs13132486
fatcat:f6u2vvmgvjggrhoqsph6odas3i
Smart anomaly detection in sensor systems: A multi-perspective review
2020
Information Fusion
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2020 pre-print arXiv:2010.14946v1 fatcat:6b2mcpbdbbecri4j3bmhejlntaOther Versions
Herein, we review state-of-the-art methods that may be employed to detect anomalies in the specific area of sensor systems, which poses hard challenges in terms of information fusion, data volumes, data ...
Anomaly detection is concerned with identifying data patterns that deviate remarkably from the expected behaviour. ...
Chong and Tay have applied this approach for the detection of anomalies in video data using, a spatio-temporal autoencoder [44] . ...
doi:10.1016/j.inffus.2020.10.001
fatcat:r65qp56ipzebnasd33o3wxkfo4
A Federated Learning Approach to Anomaly Detection in Smart Buildings
[article]
2021
arXiv
pre-print
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These devices sense the environment and generate multivariate temporal data of paramount importance for detecting anomalies and improving the prediction of energy usage in smart buildings. ...
Internet of Things (IoT) sensors in smart buildings are becoming increasingly ubiquitous, making buildings more livable, energy efficient, and sustainable. ...
In order to detect spatial, temporal, and spatio-temporal anomalies in real-time sensor measurement data streams, Chen et al. ...
arXiv:2010.10293v3
fatcat:zmwqhebvrbgcrgc3pjr6eqchcu
IEEE Access Special Section Editorial: Artificial Intelligence (AI)-Empowered Intelligent Transportation Systems
2021
IEEE Access
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In the article "nLSALog: An anomaly detection framework for log sequence in security management," by Yang et al., a general anomaly detection framework is proposed. ...
(V2V) and Vehicle-to-Infrastructure (V2I) communication modes; and how to provide efficient computing capabilities for resource-consumption applications and reasonable resource allocation for vehicles ...
They would also like to thank the reviewers, as well as the Editor-in-Chief, editors, and staff members of the journal for their great efforts and outstanding support. ...
doi:10.1109/access.2021.3074996
fatcat:dfyrghfswff6vmdlpa55jxtkjm
Table of Contents
2020
IEEE Transactions on Industrial Informatics
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She 7658 Wireless Sensor Network-Based Distributed Approach to Identify Spatio-Temporal Volterra Model for Industrial Distributed Parameter Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . ...
Cao 7469 Fault-Attention Generative Probabilistic Adversarial Autoencoder for Machine Anomaly Detection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ...
doi:10.1109/tii.2020.3022301
fatcat:7n2bzwx72bcencda27ey54zj6m
IEEE Access Special Section Editorial: Data Mining for Internet of Things
2021
IEEE Access
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In the article ''ASTIR: Spatio-temporal data mining for crowd flow prediction,'' by Mourad et al. ...
towards industrial Internet of Things,'' by Gou et al.; ''Detecting a business anomaly based on QoS benchmarks of resource-service chains for collaborative tasks in the IoT,'' by Li et al.; ''Formal verification ...
doi:10.1109/access.2021.3090137
fatcat:cnleukmukfgexmkwx7tino2k5y
Ambient Assisted Living: A Review of Technologies, Methodologies and Future Perspectives for Healthy Aging of Population
2021
Sensors
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AAL can provide an arrary of solutions for improving the quality of life of individuals, for allowing people to live healthier and independently for longer, for helping people with disabilities, and for ...
supporting caregivers and medical staff. ...
:
tri-axial accelerometer
23 adults and 15 elders
performing several
daily activities and
falls
[40,103]
ANN
Spatio-Temporal
Features
Anomaly detection
in daily activities
Wearable sensors ...
doi:10.3390/s21103549
pmid:34069727
fatcat:huc56ric2zfw5htw7nmd6mlh6m
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