PATENT CLAIM ANALYSIS

Application Number: 16166945
Application Type: Utility
Filing Date: 2018-10
Publication Date: 2019-02
Patent Classification: ["246", "121000"]

Abstract:
The present disclosure relates generally to vegetation detection and, in particular, to a vegetation detection and alert system for a railway vehicle

Claim (Index 2):
A method comprising detecting vegetation using an acquisition device mountable to a railway vehicle, the acquisition device including imaging sensors and a geospatial position sensor, the method comprising:\n capturing, by the imaging sensor, images of an environment of the railway vehicle including a clearance zone around a railroad track on which a railway vehicle moves, the imaging sensor capturing the images from the railway vehicle as the railway vehicle moves on the railroad track; determining, by the geospatial positioning sensor, a geolocation of the geospatial position sensor and thereby the environment imaged by the imaging sensor; referencing the images captured by the imaging sensor to the geolocation determined by the geospatial position sensor to form geospatial images of the environment including the clearance zone; and for one or more geospatial images of the geospatial images, processing the one or more geospatial images to produce a geometric computer model of the environment in which objects in the environment are represented by a collection of geometry; detecting vegetation in the clearance zone based on the geometric computer model; and uploading the one or more geospatial images and a notification of detected vegetation from which a backend server is configured to generate an alert for a client.

Metadata:
- Claim Count in Document: 11.0
- Percentile: 97.0
- Lexical Diversity: 1.33333
- Patent Class: 246.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['14982212', '16039106', '14982312', '14555501', '15790968']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.6337442721204855
- 35 USC 102 Novelty (BERT): 0.4585768531174454
- Combined Prediction Score: 0.6162275302201814
- Mean Citation Score: 176.29339399999995
- Max Citation Score: 211.35211
- Similarity Product: 141.20772071813704

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

Dataset: test