PATENT CLAIM ANALYSIS

Application Number: 16101444
Application Type: Utility
Filing Date: 2018-08
Publication Date: 2018-12
Patent Classification: ["342", "451000"]

Abstract:
Methods, apparatus and systems for object motion detection are disclosed. In one example, a system having at least a processor and a memory with a set of instructions stored therein for detecting object motion in a venue is disclosed. The system comprises: a first wireless device configured for transmitting a wireless signal through a wireless multipath channel impacted by a motion of an object in the venue; and a second wireless device that has a different type from that of the first wireless device and is configured for: receiving the wireless signal through the wireless multipath channel impacted by the motion of the object in the venue, and obtaining a time series of channel information (CI) of the wireless multipath channel based on the wireless signal; and a motion detector configured for detecting the motion of the object in the venue based on motion information related to the motion of the object, wherein the motion information associated with the first and second wireless devices is computed based on the time series of CI by at least one of: the motion detector and the second wireless device.

Claim (Index 16):
The method of the wireless monitoring system of  claim 14 , further comprising:\n for each Type 2 wireless device, and for each of the at least one respective particular pair of Type 1 and Type 2 devices comprising the Type 2 wireless device:\n computing asynchronously a respective heterogeneous similarity score between a respective current window and a respective past window of the at least one respective CI time series associated with the respective particular pair of wireless devices,\n wherein the respective heterogeneous similarity score is computed based on at least one of:\n a distance score, an absolute distance (e.g. l_1 norm), a Euclidean distance, a norm, a metric, a statistical characteristic, a time reversal resonating strength (TRRS), a cross-correlation, an auto-correlation, a covariance, an auto-covariance, an inner product of two vectors, \n a preprocessing, a signal conditioning, a denoising, a phase correction, a timing correction, a timing compensation, a phase offset compensation, a transformation, a projection, a filtering, \n a feature extraction, a finite state machine, a history of past similarity score, another past window of the at least one CI time series, a component-wise operation, machine learning, a neural network, a deep learning, a training, a discrimination, \n a weighted averaging, and another operation; and \n \n \n at least one of:\n monitoring the motion of the object in the venue individually and asynchronously based on asynchronously computed heterogeneous similarity score associated with the pair of Type 1 and Type 2 devices comprising the particular Type 2 device, \n monitoring the motion of the object jointly and asynchronously based on asynchronously computed heterogeneous similarity score associated with any of the at least one pair of Type 1 and Type 2 devices associated with the particular Type 2 wireless device, \n monitoring the motion of the object jointly and asynchronously based on asynchronously computed heterogeneous similarity score associated with any of the at least one pair of Type 1 and Type 2 devices associated with the respective particular Type 1 wireless device, and \n monitoring the motion of the object globally and asynchronously based on asynchronously computed heterogeneous similarity score associated with any of the at least one pair of Type 1 and Type 2 devices.

Metadata:
- Claim Count in Document: 67.0
- Percentile: 96.0
- Lexical Diversity: 2.77778
- Patent Class: 342.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['15873806', '15384217', '16060710', '15867932', '14650763']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.4982840417662468
- 35 USC 102 Novelty (BERT): 0.5085742767438104
- Combined Prediction Score: 0.4993130652640032
- Mean Citation Score: 160.907082
- Max Citation Score: 292.44373
- Similarity Product: 200.19177643902896

Labels:
- Claim Label 101: 1
- Claim Label 102: 1
- Claim Label 103: 1
- Claim Label 112: 1
- Combined Label: 1
- Label 101 Adjusted: 0

Dataset: test