View source for 18281454. METHODS AND APPARATUSES FOR REPORTING ANOMALIES AND FORECASTING KEY PERFORMANCE INDICATOR (KPI) MEASUREMENTS IN A TELECOMMUNICATIONS NODE simplified abstract (Telefonaktiebolaget LM Ericsson (PUBL))

=METHODS AND APPARATUSES FOR REPORTING ANOMALIES AND FORECASTING KEY PERFORMANCE INDICATOR (KPI) MEASUREMENTS IN A TELECOMMUNICATIONS NODE=


==Organization Name==

[[:Category:Telefonaktiebolaget LM Ericsson (PUBL)|Telefonaktiebolaget LM Ericsson (PUBL)]]


[[Category:Telefonaktiebolaget LM Ericsson (PUBL)]]

==Inventor(s)==

[[:Category:Saman Bashbaghi of Candiac (CA)|Saman Bashbaghi of Candiac (CA)]][[Category:Saman Bashbaghi of Candiac (CA)]]

[[:Category:Jean-Michel Sellier of Montreal (CA)|Jean-Michel Sellier of Montreal (CA)]][[Category:Jean-Michel Sellier of Montreal (CA)]]

[[:Category:Mostefa Golea of Ottawa (CA)|Mostefa Golea of Ottawa (CA)]][[Category:Mostefa Golea of Ottawa (CA)]]

[[:Category:Sathi Marath of Kanata (CA)|Sathi Marath of Kanata (CA)]][[Category:Sathi Marath of Kanata (CA)]]

==METHODS AND APPARATUSES FOR REPORTING ANOMALIES AND FORECASTING KEY PERFORMANCE INDICATOR (KPI) MEASUREMENTS IN A TELECOMMUNICATIONS NODE - A simplified explanation of the abstract==


This abstract first appeared for US patent application 18281454 titled 'METHODS AND APPARATUSES FOR REPORTING ANOMALIES AND FORECASTING KEY PERFORMANCE INDICATOR (KPI) MEASUREMENTS IN A TELECOMMUNICATIONS NODE

The patent application describes a method for reporting anomalies in a telecommunications node by utilizing key performance indicators (KPIs) and polynomial functions.

* Obtaining a measurement of a KPI of the telecommunication node.
* Updating coefficients of a polynomial function upon receiving the measurement of the KPI.
* Computing an expected measurement of the KPI based on the updated coefficients of the polynomial function.
* Computing a confidence band for the expected measurement of the KPI.
* Reporting the anomaly when the measurement of the KPI is outside of the confidence band.

Potential Applications:
- Telecommunications network monitoring and maintenance.
- Predictive maintenance in telecommunications infrastructure.
- Quality assurance in telecommunications services.

Problems Solved:
- Efficient anomaly detection in telecommunications nodes.
- Improved accuracy in forecasting KPI measurements.
- Timely identification of performance issues in the network.

Benefits:
- Enhances network reliability and performance.
- Reduces downtime and service disruptions.
- Optimizes resource allocation and maintenance schedules.

Commercial Applications:
Title: "Advanced Telecommunications Anomaly Detection System"
This technology can be utilized by telecommunications companies to improve network performance, reduce maintenance costs, and enhance customer satisfaction. It can also be integrated into network monitoring tools and software for real-time anomaly detection and predictive maintenance.

Prior Art:
Readers can explore prior research on anomaly detection in telecommunications networks, predictive maintenance algorithms, and KPI forecasting methods to gain a deeper understanding of the technology landscape in this field.

Frequently Updated Research:
Stay informed about the latest developments in anomaly detection algorithms, machine learning applications in telecommunications, and advancements in network monitoring technologies to enhance the effectiveness of this innovation.

Questions about Telecommunications Anomaly Detection:
1. How does this method improve upon traditional anomaly detection techniques in telecommunications networks?
2. What are the key advantages of using polynomial functions for forecasting KPI measurements in telecommunications nodes?


==Original Abstract Submitted==

The disclosure relates to a method, for reporting an anomaly in a telecommunications node. The method comprises obtaining a measurement of a key performance indicator (KPI) of the telecommunication node. The method comprises, upon receiving the measurement of the KPI, updating coefficients of a polynomial function. The method comprises, based on the updated coefficients of the polynomial function, computing an expected measurement of the KPI coefficient. The method comprises computing a confidence band for the expected measurement of the KPI. The method comprises reporting the anomaly when the measurement of the KPI is outside of the confidence band. The disclosure also relates to a method for forecasting a plurality of expected measurements for a key performance indicator (KPI) in a telecommunications node, as well as to apparatuses for executing these methods.



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