PATENT CLAIM ANALYSIS

Application Number: 16086966
Application Type: Utility
Filing Date: 2018-09
Publication Date: 2019-04
Patent Classification: ["455", "456300"]

Abstract:
According to various embodiments, there is provided a passenger load prediction system including: a component configured to detect a wireless device carried by a passenger on a train or a train station platform, the train including a plurality of train cars; a passenger to train car mapper configured to determine a location of the passenger, based on a location of the wireless device; a destination predictor configured to predict a destination of the passenger, based at least in part on an identifier code of the wireless device; and a train car load level estimator configured to predict a respective passenger load of each train car of the plurality of train cars, based on the predicted destination and further based on the determined location of the passenger.

Claim (Index 14):
The passenger load prediction system of  claim 1 , further comprising a passenger load distributor configured to compute an optimal distribution of further passengers to each train car, based on the predicted respective passenger load of each train car and further based on identification of passengers travelling as a group, wherein the identification of passengers travelling as a group is obtained from historical records of identifier codes of wireless devices which simultaneously undertook common journeys.

Metadata:
- Claim Count in Document: 4.0
- Percentile: 97.0
- Lexical Diversity: 2.42857
- Patent Class: 455.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['15267474', '12745418', '15104010', '14879666', '13522454']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.6848982688541189
- 35 USC 102 Novelty (BERT): 0.5022609226497056
- Combined Prediction Score: 0.6666345342336776
- Mean Citation Score: 198.098542
- Max Citation Score: 236.6689
- Similarity Product: 152.96781804172994

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