PATENT CLAIM ANALYSIS

Application Number: 16293827
Application Type: Utility
Filing Date: 2019-03
Publication Date: 2019-06
Patent Classification: ["455", "422100"]

Abstract:
Collection of crowd-sourced access point quality and selection data for intelligent network selection can be utilized by mobile devices to self-learn and optimize access point device selection. A cloud-based application can be utilized in conjunction with the mobile device to build a database of access point quality and thresholds suitable for real-time and other jitter-sensitive services. The mobile device jitter measurements and selection thresholds can be collected and sent to a cloud platform, which creates an access point performance and selection threshold profile.

Claim (Index 1):
A method, comprising:\n receiving, by a mobile device comprising a processor, a first signal from an access point device of a wireless network; based on the first signal, determining, by the mobile device, that the access point device has not previously sent a second signal to the mobile device, the second signal being different than the first signal; in response to the determining, generating, by the mobile device, threshold data associated with a threshold of signal strength quality of the first signal, wherein the threshold is associated with a packet flow jitter of a control protocol; in response to the first signal being terminated, refreshing, by the mobile device, expired access point data associated with the access point device and the packet flow jitter of the control protocol; and updating, by the mobile device, a data structure of the mobile device with the threshold data and time data associated with the threshold data.

Metadata:
- Claim Count in Document: 50.0
- Percentile: 99.0
- Lexical Diversity: 1.64151
- Patent Class: 455.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['15721326', '15721335', '16251404', '15721308', '14892377']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.7205701924332502
- 35 USC 102 Novelty (BERT): 0.5043693739877092
- Combined Prediction Score: 0.6989501105886962
- Mean Citation Score: 255.575178
- Max Citation Score: 306.22614
- Similarity Product: 284.7963539678978

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