PATENT CLAIM ANALYSIS

Application Number: 16055361
Application Type: Utility
Filing Date: 2018-08
Publication Date: 2019-02
Patent Classification: ["342", "451000"]

Abstract:
Systems and methods of using a machine learning model to detect physical characteristics of an environment based on radio signal data include at a radio signal receiver, collecting noise floor signal data comprising radio signal data from an environment within a predetermined proximity of the radio signal receiver; implementing a trained deep machine learning classifier that is trained to classify one or more physical characteristics of the environment based on the radio signal data; generating machine learning input based on the radio signal data collected by the radio signal receiver; receiving the machine learning input at the trained deep machine learning classifier; and generating by the trained deep machine learning model one or more classification labels identifying the one or more physical characteristics of the environment based on the noise floor signal data.

Claim (Index 6):
The method according to  claim 5 , wherein:\n the trained deep machine learning classifier is trained to classify a plurality of distinct physical characteristics of the environment or a plurality of distinct sensory conditions within the environment.

Metadata:
- Claim Count in Document: 41.0
- Percentile: 96.0
- Lexical Diversity: 2.62264
- Patent Class: 342.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['15955485', '14330202', '15961465', '14879787', '15604473']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.5768847433949886
- 35 USC 102 Novelty (BERT): 0.5002564839910462
- Combined Prediction Score: 0.5692219174545944
- Mean Citation Score: 190.833904
- Max Citation Score: 201.8988
- Similarity Product: 118.22137507009506

Labels:
- Claim Label 101: 1
- Claim Label 102: 1
- Claim Label 103: 0
- Claim Label 112: 1
- Combined Label: 1
- Label 101 Adjusted: 1

Dataset: test