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 30):
A receiver of a wireless monitoring system, comprising:\n a wireless circuitry configured to:\n for each of at least one known event happening in a venue in a respective training time period, receive a respective training wireless signal through a wireless multipath channel impacted by the known event, wherein the respective training wireless signal is transmitted by a first transmitter through the wireless multipath channel between the receiver and the first transmitter in the training time period associated with the known event, and \n for a current event happening in the venue in a current time period, receive a current wireless signal through the wireless multipath channel impacted by the current event, wherein the current wireless signal is transmitted by a second transmitter through the wireless multipath channel between the receiver and the second transmitter in the current time period associated with the current event; \n a processor communicatively coupled with the wireless circuitry; a memory communicatively coupled with the processor; and a set of instructions stored in the memory which, when executed, causes the processor to:\n for each of the at least one known event happening in the venue, obtain, asynchronously based on the respective training wireless signal, at least one time series of training channel information (training CI time series) of the wireless multipath channel, and \n for the current event happening in the venue in the current time period, obtain, asynchronously based on the current wireless signal, at least one time series of current channel information (current CI time series) of the wireless multipath channel, wherein: \n the at least one training CI time series is used by an event recognition engine of the wireless monitoring system to train at least one classifier for the at least one known event, and the at least one classifier is applied to:\n classify at least one of: the at least one current CI time series, a portion of a particular current CI time series, and a combination of the portion of the particular current CI time series and a portion of an additional CI time series, and \n associate the current event with at least one of: a known event, an unknown event and another event.

Metadata:
- Claim Count in Document: 35.0
- Percentile: 98.0
- Lexical Diversity: 3.80597
- Patent Class: 370.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['16203317', '16200616', '16101444', '15873806', '16060710']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.548883528084013
- 35 USC 102 Novelty (BERT): 0.5076134931610664
- Combined Prediction Score: 0.5447565245917183
- Mean Citation Score: 255.455284
- Max Citation Score: 274.34125
- Similarity Product: 181.0461493960023

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