PATENT CLAIM ANALYSIS

Application Number: 16125263
Application Type: Utility
Filing Date: 2018-09
Publication Date: 2019-01
Patent Classification: ["709", "224000"]

Abstract:
An apparatus and a method are disclosed herein for improving predictive and preventive analytics, event tracking and processing of large combinations of data. In one embodiment, a method comprising, receiving a first data set, the first data set including data from a plurality of sources; applying a first rule set to the first subset; responsive to detecting an emergency as a result of the application of the first rule set, generating an emergency notification; generating an intuition by (a) applying a second rule set to a second subset of the first data set, the second rule set selected from one or more rule sets based on the emergency notification, and (b) selecting a course of action based on a result of the application of the second predefined rule set; and providing the course of action to a user is disclosed.

Claim (Index 8):
The computer-implemented method of  claim 6 , further comprising:\n receiving sensor data to determine if one or more sensors providing sensor data meet compliance or regulatory requirements based on or more rule sets; providing a compliance alert to a user via a UI if one or more sensors do not meet compliance or regulatory requirements.

Metadata:
- Claim Count in Document: 23.0
- Percentile: 97.0
- Lexical Diversity: 2.34328
- Patent Class: 709.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['14735975', '14497105', '11639985', '14517554', '14956403']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.2111369591672626
- 35 USC 102 Novelty (BERT): 0.579756897413526
- Combined Prediction Score: 0.2479989529918889
- Mean Citation Score: 213.4972848
- Max Citation Score: 464.14218
- Similarity Product: 444.8309379534745

Labels:
- Claim Label 101: 1
- Claim Label 102: 1
- Claim Label 103: 1
- Claim Label 112: 1
- Combined Label: 1
- Label 101 Adjusted: 1

Dataset: test