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 8):
A system, comprising:\n a processor; and a memory that stores executable instructions that, when executed by the processor, facilitate performance of operations, comprising:\n determining that an access point device has not previously sent a first signal to a mobile device of a wireless network; \n in response to the determining, generating threshold data associated with a threshold of signal strength quality of a second signal sent from the access point device to the mobile device, wherein the threshold is associated with a packet flow jitter associated with a control protocol; \n in response to the second signal being terminated, refreshing expired access point data associated with the access point device and the packet flow jitter associated with the control protocol; and \n in response to the refreshing the expired access point data, updating time data with associated with the threshold of the signal strength quality of the second signal, resulting in updated time 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): 0.7203626052776713
- 35 USC 102 Novelty (BERT): 0.5063214490343088
- Combined Prediction Score: 0.698958489653335
- Mean Citation Score: 255.575178
- Max Citation Score: 306.22614
- Similarity Product: 273.0813517031479

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