PATENT CLAIM ANALYSIS

Application Number: 15919033
Application Type: Utility
Filing Date: 2018-03
Publication Date: 2018-07
Patent Classification: ["340", "937000"]

Abstract:
The present disclosure relates to artificial intelligence based systems and method for determination of traffic violations. The present disclosure provides systems and methods that use deep convolutional neural networks and machine vision based algorithms to perform a task of detection and recognition to provide complete solution to safe, legal and comfortable parking, driving and riding for commuters on the roadways. Roadway stewardship systems, Parking management systems when made on-demand and crowdsourced, can play a very strong role in regulating driving conditions in cities and highways. By allowing the on-demand, crowdsourced, roadway stewardship system to be automated, through the use of Artificial Intelligence (AI) sub-systems, users can be trained to recognize and be educated as well in the laws & regulations around the use of roadways; can help the process through an interactive console/game-play, which can also be used for monetization for individuals to earn money for their contribution. The AI assisted with Human Intelligence (HI) together called HAI in particular, can play a valuable role in reducing traffic density, traffic movement restrictions and fuel and time waste in large cities. Also proper driving on the roads can lead to faster and safer commute. In Addition, multiple other objects of interest can also be identified and trained to be recognized using the Stewardship System disclosed herein.

Claim (Index 15):
The method of  claim 14 , wherein the visual markings are given a score based on number of persons who witness the markings; wherein the scores are used to qualify the efficacy of placement of the visual marking(s) and the efficacy of the content(s) of the visual marking(s).

Metadata:
- Claim Count in Document: 20.0
- Percentile: 90.0
- Lexical Diversity: 1.70714
- Patent Class: 340.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['15689350', '10161942', '14832584', '10338247', '13441253']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.6984719321762021
- 35 USC 102 Novelty (BERT): 0.519987186812389
- Combined Prediction Score: 0.6806234576398207
- Mean Citation Score: 218.234328
- Max Citation Score: 263.98392
- Similarity Product: 166.77120880047795

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

Dataset: test