PATENT CLAIM ANALYSIS

Application Number: 16203299
Application Type: Utility
Filing Date: 2018-11
Publication Date: 2019-03
Patent Classification: ["370", "252000"]

Abstract:
Apparatus, systems and methods for recognizing and classifying events in a venue based on a wireless signal are disclosed. In one example, a disclosed system comprises a first transmitter, a second transmitter, at least one first receiver, at least one second receiver, and an event recognition engine, in the venue. The first transmitter transmits a training wireless signal through a wireless multipath channel impacted by a known event in the venue in a training time period associated with the known event. Each first receiver receives asynchronously the training wireless signal, and obtains, asynchronously based on the training wireless signal, at least one time series of training channel information of the wireless multipath channel between the first receiver and the first transmitter. The second transmitter transmits a current wireless signal through the wireless multipath channel impacted by a current event in a current time period associated with the current event. Each second receiver receives asynchronously the current wireless signal, and obtains, asynchronously based on the current wireless signal, at least one time series of current channel information of the wireless multipath channel between the second receiver and the second transmitter. The event recognition engine trains a classifier based on the training channel information; and apples the classifier to: classify the current channel information and associate the current event with at least one of: a known event, an unknown event and another event.

Claim (Index 19):
The method of  claim 17 , wherein:\n a particular representative training CI time series associated with a particular known event has a particular time duration; the particular representative training CI time series of the particular time duration is aligned with each of the at least one training CI time series associated with the known event and a respective mismatch cost is computed; the particular representative training CI time series minimizes an aggregate mismatch with respect to the at least one training CI time series; the aggregate mismatch of a CI time series is a function of at least one mismatch cost between the CI time series and each of the at least one training CI time series aligned with the CI time series; and the function comprises at least one of: average, weighed average, mean, trimmed mean, median, mode, arithmetic mean, geometric mean, harmonic mean, truncated mean, generalized mean, power mean, f-mean, interquartile mean, and another mean.

Metadata:
- Claim Count in Document: 35.0
- Percentile: 98.0
- Lexical Diversity: 3.80597
- Patent Class: 370.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['16203317', '16200616', '16101444', '15873806', '16060710']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.5789475000750369
- 35 USC 102 Novelty (BERT): 0.5055377915780169
- Combined Prediction Score: 0.571606529225335
- Mean Citation Score: 255.455284
- Max Citation Score: 274.34125
- Similarity Product: 196.87614049434663

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