PATENT CLAIM ANALYSIS

Application Number: 15938799
Application Type: Utility
Filing Date: 2018-03
Publication Date: 2019-10
Patent Classification: ["701", "019000"]

Abstract:
A Fit-For-Duty network system and method that integrates several drowsiness detection devices with software analytics engine to more accurately predict, monitor and/or detect an actual unfit-for-duty condition or “positive event” in real time. The system monitors behavior based on changing operational conditions (such as speed of vehicle and pre-defined conditions, such as time of day and geographic conditions) to dynamically estimate both seriousness and probability of a positive event. Moreover, based on estimated seriousness and probability of a positive event the system self-initiates different levels of alerts ranging from light and sound, to connection to a third party intervener (such as an operations center), to stopping the vehicle.

Claim (Index 1):
A Fit-For-Duty system, comprising:\n a local monitoring system configured for monitoring a vehicle and comprising at least one video camera in operable communication with a central processor, non-transitory computer memory, computer program code stored on said non-transitory computer memory, a data communication interface for sending and receiving data, and a user interface for display and data entry to/from a vehicle operator, said processor being in operable communication with the non-transitory computer memory and controlled by the computer program code to execute the steps of, authenticating said vehicle operator, presenting a psychomotor vigilance task (PVT) software module to said vehicle operator and measuring the speed with which the vehicle operator responds to a visual stimulus, and compiling a pass/fail result, capturing a video stream of said vehicle operator including a sequence of frames from said at least one video camera, analyzing a frame of said captured video stream to locate the vehicle operator's eyes, analyzing a sequence of frames of said captured video using a PERcentage of eye CLOSure (PERCLOS) algorithm to track the vehicle operator's eyes, compiling a PERCLOS metric based on said analyzing step, analyzing the combined metrics of the PVT software module and PERCLOS software module, vehicle operator data, and external data using an analytical Fit-for-Duty software module and compiling a categorical severity metric corresponding to said vehicle operator's fitness-for-duty, and when the categorical severity metric exceeds a first predetermined threshold, transmitting an alert to a remote location.

Metadata:
- Claim Count in Document: 47.0
- Percentile: 90.0
- Lexical Diversity: 1.5443
- Patent Class: 701.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['13397410', '14820281', '10946396', '14900363', '14733446']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3529049656040993
- 35 USC 102 Novelty (BERT): 0.5072456515484457
- Combined Prediction Score: 0.368339034198534
- Mean Citation Score: 128.8215972
- Max Citation Score: 168.38579
- Similarity Product: 90.3709590461117

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