PATENT CLAIM ANALYSIS

Application Number: 16113421
Application Type: Utility
Filing Date: 2018-08
Publication Date: 2019-02
Patent Classification: ["340", "436000"]

Abstract:
Using object detection in potentially dangerous areas (such as road crossings, intersections, streets with high pedestrian or cyclist activity) and existing vulnerable road user EBA algorithms, the events leading up to a collision, as well as the actual collision event may be recorded such that an accurate account of the accident is achieved, and local law enforcement agencies may be immediately notified. Since EBA systems have sensors that may accurately determine the location, speed, and direction of objects (pedestrians, cyclists, etc), and may be equipped with V2x technologies and communicate with the smart city infrastructures, key information may be obtained and sent to various servers for companies to determine pre-crash scenario accidents occurring in near real-time using cloud type services via cellular, wifi, and other networks, such that developers of safety technologies may use this information quickly implement new safety technologies or improve existing ones.

Claim (Index 2):
The apparatus of  claim 1 , wherein the at least one signal device sends the signal to a law enforcement agency, alerting the law enforcement agency that an accident has occurred.

Metadata:
- Claim Count in Document: 4.0
- Percentile: 96.0
- Lexical Diversity: 1.52778
- Patent Class: 340.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['15448562', '10818432', '14042100', '10557915', '12403962']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.6351930135969382
- 35 USC 102 Novelty (BERT): 0.5001430408495946
- Combined Prediction Score: 0.6216880163222038
- Mean Citation Score: 141.414256
- Max Citation Score: 149.21258999999995
- Similarity Product: 96.56175066765364

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

Dataset: test