View source for 18130596. Anomaly Alerts Accreditation simplified abstract (Google LLC)

=Anomaly Alerts Accreditation=


==Organization Name==

[[:Category:Google LLC|Google LLC]]


[[Category:Google LLC]]

==Inventor(s)==

[[:Category:Harish Kumar Bheemarthi Anjaneyulu of London (GB)|Harish Kumar Bheemarthi Anjaneyulu of London (GB)]][[Category:Harish Kumar Bheemarthi Anjaneyulu of London (GB)]]

==Anomaly Alerts Accreditation - A simplified explanation of the abstract==


This abstract first appeared for US patent application 18130596 titled 'Anomaly Alerts Accreditation

The technology described in the patent application involves generating an alert based on the direction and depth of a detected anomaly. The direction of the anomaly can indicate whether it is broadening or normalizing, while the depth of the anomaly can provide insight into the magnitude of the direction compared to the detected anomaly. 

* The direction of the anomaly may be positive, indicating normalization or movement towards an expected value, or negative, indicating broadening or moving further from the expected value.
* Based on the determined direction and depth, a trend of the anomaly can be established.
* A normalizing trend suggests the anomaly is likely to normalize, thus no alert is needed.
* A broadening trend suggests the anomaly is likely to broaden, prompting the generation of an alert.

Potential Applications:
- This technology can be applied in various industries such as finance, healthcare, and cybersecurity to monitor and detect anomalies in data.
- It can be used in predictive maintenance systems to anticipate equipment failures based on anomaly trends.

Problems Solved:
- Helps in early detection of anomalies in data, allowing for timely intervention and prevention of potential issues.
- Provides a systematic approach to analyzing anomalies and determining their trends for better decision-making.

Benefits:
- Enhances data monitoring and analysis processes.
- Improves overall system reliability and performance.
- Enables proactive measures to address anomalies before they escalate.

Commercial Applications:
Title: Anomaly Detection System for Enhanced Data Monitoring
This technology can be utilized by financial institutions for fraud detection, healthcare providers for patient monitoring, and IT companies for network security.

Questions about Anomaly Detection System:
1. How does the direction and depth of an anomaly impact the generation of alerts?
2. What are the key industries that can benefit from this anomaly detection technology?

Frequently Updated Research:
Stay updated on advancements in anomaly detection algorithms and machine learning models for improved anomaly detection accuracy.


==Original Abstract Submitted==

The technology is generally directed to generating an alert based on a direction and depth of a detected anomaly. The direction of the anomaly may provide an indication as to whether the anomaly is broadening or normalizing, and the depth of the anomaly may provide an indication of the magnitude of the direction as compared to the detected anomaly. The direction may be positive, indicating that the anomaly is normalizing or moving towards an expected value, or negative, indicating that the anomaly is broadening or moving further from the expected value. Based on the determined direction and depth, a trend of the anomaly may be determined. A normalizing trend may indicate that the anomaly is likely to normalize and, therefore, an alert is not necessary. A broadening trend may indicate that the anomaly is likely to broaden and, therefore, an alert should be generated.



[[Category:G06F11/07]]
[[Category:CPC_G06F11/079]]