PATENT CLAIM ANALYSIS

Application Number: 15883206
Application Type: Utility
Filing Date: 2018-01
Publication Date: 2019-08
Patent Classification: ["348", "143000"]

Abstract:
A data fusion based safety surveillances system has a first through N th  virtual monitoring systems and a data fusion and decision device. The data fusion and decision device defines an i th  detection model of the i th  virtual monitoring system, and estimates an i th  detection loss probability of the i th  virtual monitoring system according to detection loss sample numbers of batches of i th  monitored data of the i th  virtual monitoring system under conditions corresponding to the locations, batches of context data and existence of intruder, the i th  detection model, the batches of i th  monitored data corresponding to locations of the i th  virtual monitoring system and the batches of context data. The data fusion and decision device determines a fusion parameter set according to the first through N th  detection loss probabilities, and performs data fusion on a first through N th  detection results to generate a decision result.

Claim (Index 5):
The data fusion based safety surveillances system of  claim 1 , wherein each of the batches of context data is a weather data defining variables of a rainfall, a wind speed, a temperature and a brightness.

Metadata:
- Claim Count in Document: 3.0
- Percentile: 86.0
- Lexical Diversity: 3.05556
- Patent Class: 348.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['14686420', '15224679', '14343244', '15813750', '15390134']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.6239576178910023
- 35 USC 102 Novelty (BERT): 0.5042613400095973
- Combined Prediction Score: 0.6119879901028619
- Mean Citation Score: 168.517094
- Max Citation Score: 174.18088
- Similarity Product: 96.70602063373089

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