Simple Anomaly Detection Technique from Long-term Time-series Data by ATSC 3.0 Single Frequency Broadcast Network Monitoring System

S. Jeon, Seongman Min, Dawoon Chung, Kangsoo Kim, Jahoon Ku, Sunhyung Kwon, Sung-Ik Park
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Abstract

Long-term Time Series Data from ATSC 3.0 single frequency broadcast network operation is important to understand anomaly patterns by measurement metrics because it provides a comprehensive view of the performance and behavior of the ATSC 3.0 network over time. This information can help identify and analyze patterns, trends, and outliers in the data, which can provide valuable insights into the health and stability of the network. By understanding these anomaly patterns, engineers and technicians can improve the network’s performance, troubleshoot issues, and make informed decisions about future upgrades and maintenance.
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基于ATSC 3.0单频广播网络监测系统的长期时间序列数据简单异常检测技术
ATSC 3.0单频广播网络运行的长期时间序列数据对于通过测量指标了解异常模式非常重要,因为它提供了ATSC 3.0网络随时间变化的性能和行为的全面视图。这些信息有助于识别和分析数据中的模式、趋势和异常值,从而对网络的健康和稳定性提供有价值的见解。通过了解这些异常模式,工程师和技术人员可以提高网络的性能,排除问题,并对未来的升级和维护做出明智的决策。
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