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 1):
An artificial intelligence (AI) based system, part of a Roadway Stewardship Network, comprising:\n a non-transitory storage device having embodied therein one or more routines operable to detect objects in images using Artificial Neural Networks; and one or more processors coupled to the non-transitory storage device and operable to execute the one or more routines, wherein the one or more routines include:\n a receiver module, which when executed by the one or more processors, receives at least an object detection signal from one or more vision sensing systems, said object detection signal comprises or is accompanied by said images or series of images or a video associated with said objects; \n a detector module, which when executed by the one or more processors, determines, for said objects, a region of interest (ROI) selected from the received images or a series of images or a video; \n a training module which takes the manually classified objects, obtained from the images or a series of images or a video and trains the Neural Network to improve the detector performance; \n a logic module which takes as input the detected objects of interest in a series of one or more images or videos and determines various actions or events of interest.

Metadata:
- Claim Count in Document: 20.0
- Percentile: 90.0
- Lexical Diversity: 1.70714
- Patent Class: 340.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['15689350', '10161942', '14832584', '10338247', '13441253']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.6718717781590986
- 35 USC 102 Novelty (BERT): 0.5230918162863576
- Combined Prediction Score: 0.6569937819718245
- Mean Citation Score: 218.234328
- Max Citation Score: 263.98392
- Similarity Product: 149.7442212885189

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

Dataset: test