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Cited by 1Context-Aware Activity Recognition SystemsSmart Agriculture and AIIoT and Edge/Fog Computing

Video Camera and Sensor Status Monitoring System in IoT Environments

Open access
Besednyi, Nikita, Harkovchuk, Artur, Korzun, Dmitry·2022·Zenodo
DOI 10.5281/zenodo.7368473
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Abstract

Recent progress in Ambient Intelligence (AmI) technology leads to many proposals of sensing systems in the physical, informational, and social worlds. Such systems focus primarily on the sensed data retrieval, including advanced cases of Internet of Things (IoT) sensors and video capture. Operation of a sensor is subject to faults, anomalies, and outliers. In this work-in-progress paper, we consider the problem of tracking the operation of a video camera or environment sensor to recognize deviations from the expected function. The recognition is based on neural network and context analysis. We implemented a module that makes a sensor smart in terms of operation status recognition and its self-understanding. Our demo shows the applicability of the module in IoT monitoring systems.

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Authors
Besednyi, N., Harkovchuk, A., & Korzun, D.
Affiliations
Petrozavodsk State University (RU)
ORCID
Korzun, Dmitry
Venue
Zenodo
Publisher
Zenodo
Published
2022-11-11
DOI
10.5281/zenodo.7368473
OpenAlex
W4310005000
Cited by
1
References
0
Citations by year
2022: 1
FWCI
0.10
Type
conference paper
Language
en
Open access
Licence
Locations
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • Zenodo (CERN European Organization for Nuclear Research) (cc-by)
Topics
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Context-Aware Activity Recognition Systems
  • Life Sciences › Agricultural and Biological Sciences › Plant Science › Smart Agriculture and AI
  • Physical Sciences › Computer Science › Computer Networks and Communications › IoT and Edge/Fog Computing
Keywords
video camera monitoring, Internet of Things, ambient intelligence, sensor fault detection, anomaly detection, artificial neural networks, contextual analysis, smart sensors

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