PATENT CLAIM ANALYSIS

Application Number: 15777609
Application Type: Utility
Filing Date: 2018-05
Publication Date: 2018-11
Patent Classification: ["455", "456100"]

Abstract:
When access point signals are altered, conventional fingerprint-based indoor localization techniques are note accuracy. Localization with altered access point and fingerprint updating can achieves accurate indoor localization and automatically update a fingerprint database with altered access points. Using subset sampling, the system detect the altered access points, filter them out by a received signal strength vector and find the location of a client. Given the received signal strength vectors received and the estimated location, the system can update a fingerprint database with the signal changes by applying a non-parametric Gaussian process regression method.

Claim (Index 1):
A method, comprising:\n identifying, by a wireless network device comprising a processor, a first location associated with an access point device of access point devices; in response to identifying a second location associated with the access point device and different than the first location, determining, by the wireless network device, that the access point device has become an altered access point device; associating, by the wireless network device, a reference location with the altered access point device; filtering, by the wireless network device, the altered access point device from the access point devices; and in response to the filtering, updating, by the wireless network device, the reference location associated with the altered access point device.

Metadata:
- Claim Count in Document: 32.0
- Percentile: 93.0
- Lexical Diversity: 1.80357
- Patent Class: 455.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['15316140', '11302311', '12966493', '14576586', '15784287']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.6739671775039238
- 35 USC 102 Novelty (BERT): 0.4800140589196739
- Combined Prediction Score: 0.6545718656454989
- Mean Citation Score: 162.40104
- Max Citation Score: 181.30699
- Similarity Product: 131.0951427090943

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